Final Report - UNDP v 1.… · Low Carbon Growth in Ukraine Final Report iv 3. Impact assessment of identified policies and measures and development of BAU scenarios until 2020 and

The consulting company of DIW Berlin

Final Report

June 2014

Project

“Capacity Building for Low Carbon Growth in Ukraine”

Low Carbon Growth in Ukraine

Final Report

ii

DIW ECON GmbH

Dr. Lars Handrich

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Germany

Phone +49.30.20 60 972 - 0

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www.diw-econ.de

DIW ECON GmbH

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mailto:[email protected]

http://www.diw-econ.de/


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Table of Contents

Management-oriented summary ............................................................................................ 1

Executive summary ............................................................................................................... 3

1. Sectoral economic analysis ............................................................................................ 7

1.1 Introduction and summary of main results................................................................. 7

1.2 The Benchmarking Approach ................................................................................... 9

1.3 Benchmarking the metal industry ............................................................................ 11

1.3.1 Database .........................................................................................................11

1.3.2 The metal industry in selected countries ..........................................................13

1.3.3 Efficiency benchmarking ..................................................................................15

1.3.4 Adjustment for structural characteristics ...........................................................17

1.3.5 Summary and implications for the metal industry in Ukraine ............................21

1.4 Benchmarking the non-metallic minerals industry ................................................... 23

1.4.1 Database .........................................................................................................23

1.4.2 The non-metallic minerals industry in selected countries ..................................24



1.4.5 Summary and implications for the minerals industry in Ukraine ........................31

1.5 Benchmarking the chemical industry....................................................................... 32

1.5.1 Database .........................................................................................................32

1.5.2 The chemicals industry in selected countries ...................................................33



1.5.5 Summary and implications for the chemicals industry in Ukraine .....................41

1.6 Conclusion .............................................................................................................. 41

2. Short analytical papers on economic analysis of policy options to support low carbon

policies ..........................................................................................................................43

2.1 Towards a low carbon growth strategy for Ukraine ................................................. 43

2.2 Assessing the innovation potential in Ukraine ......................................................... 44

2.3 Policy options for LCD in industry ........................................................................... 45

2.3.1 Introduction ......................................................................................................45

2.3.2 Status quo and the planned policies in industry ...............................................46

2.3.3 Potential for emission reduction in industry: Assessments from the literature ...51

2.3.4 What can the government do for the low carbon development? .......................51


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3. Impact assessment of identified policies and measures and development of BAU

scenarios until 2020 and 2050 .......................................................................................53

3.1 How to assess the potential of identified policies for low-carbon economic growth

in Ukraine ............................................................................................................... 53

3.2 Model description .................................................................................................... 54

3.2.1 Building blocks .................................................................................................54

3.2.2 Production technology .....................................................................................55

3.2.3 Power sector ....................................................................................................57

3.2.4 Heat supply sector ...........................................................................................58

3.2.5 Taxes and subsidies ........................................................................................59

3.2.6 GHG emissions ................................................................................................60

3.2.7 Rest of the world ..............................................................................................60

3.2.8 Behavioural setup and equilibrium ...................................................................61

3.2.9 Dynamic elements ...........................................................................................62

3.2.10 Model closure ..................................................................................................63

3.2.11 Database .........................................................................................................64

3.3 Scenario analyses .................................................................................................. 70

3.3.1 The Business-as-Usual (BAU) Scenario ..........................................................70

3.3.2 Results of the Business-as-Usual scenario ......................................................82

3.3.3 The Energy-Efficient-Investments (EEI) scenario .............................................86

3.3.4 Results of the Energy-Efficient-Investments (EEI) scenario .............................91

4. Short-term, ad hoc expertise and consulting to decision makers and key stakeholders for

current topics on the political agenda .............................................................................97

4.1 Introduction ............................................................................................................. 97

4.2 The challenge ......................................................................................................... 98

4.3 Analysis .................................................................................................................. 99

4.3.1 Expected yearly levels of GDP growth until 2020 .............................................99

4.3.2 The intensity of GHG emissions per GPD until 2020 ...................................... 100

4.3.3 Expected national GHG emissions: new adjusted estimations ....................... 101

4.3.4 Costs of reaching the 2012 Doha Amendment ............................................... 101

4.4 Conclusions .......................................................................................................... 102

5. Revised concept of a low carbon development plan of Ukraine: From Stabilisation to

Sustainable Economic Growth ..................................................................................... 103

6. Findings from the economic assessment of a domestic ETS and possibilities for linking

the ETS in Ukraine with other FSU countries ............................................................... 105


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References ......................................................................................................................... 107

Appendix A ......................................................................................................................... 114

Appendix B-1 ...................................................................................................................... 117

Appendix B-2 ...................................................................................................................... 129

Appendix C-1

Benchmarking for sustainable and economically viable technology options

Appendix C-2

Towards a low carbon growth strategy for Ukraine

Appendix C-3

Assessing the innovation potential in Ukraine

Appendix C-4

The 2012 Doha Amendment to the Kyoto Protocol: Implications and Recommendations

for Ukraine

Appendix C-5


Appendix C-6

Towards ratification of the 2012 Doha Amendment to the Kyoto Protocol by Ukraine: The

revised projections of national GHG emissions

Appendix C-7

MRV and linking a potential ETS in Ukraine with other systems

Appendix C-8

From Stabilisation to Sustainable Economic Growth


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List of Figures

Figure 1: Technical efficiency levels of metal industries in selected countries (in 2007) ........ 16

Figure 2: Structural characteristics of the metal industry in selected countries (2007) .......... 19

Figure 3: Technical efficiency levels adjusted for structural characteristics ........................... 21

Figure 4: Technical efficiency levels of minerals industries in selected countries (2007) ....... 26

Figure 5: Structural characteristics of the minerals industry across countries (2007) ............ 30

Figure 6: Technical efficiency levels of chemicals industries in selected countries (2007) .... 35

Figure 7: Structural characteristics of the chemicals industry in selected countries (2007) ... 38

Figure 8: Technical efficiency levels adjusted for structural characteristics ........................... 41

Figure 9: GHG Emissions by the Ukrainian industry, million tons of CO2-equivalents .......... 47

Figure 10: Direct GHG emissions and the demand for energy by industrial enterprises, as

foreseen by different ministries. Yearly expected percentage changes over 2010-

2017. .................................................................................................................. 50

Figure 11: Schematic representation of a multi-level CES production function ..................... 56

Figure 12: Schematic representation of the CES production function electricity sector ......... 58

Figure 13: Gross value added by key sectors in Ukraine (2011) ........................................... 65

Figure 14: GHG emission intensity in Ukraine and OECD Europe (1990-2010) .................... 73

Figure 15: Primary energy intensity of sectoral output in BAU (TJ per mln UAH in constant

prices of 2001) ................................................................................................... 74

Figure 16: Electricity intensity of sectoral output in BAU (GWh per mln UAH in constant

prices of 2001) ................................................................................................... 76

Figure 17: Installed generation capacity in the BAU scenario ............................................... 78

Figure 18: Fuel mix of produced electricity (in percent of total generation, BAU scenario) .... 79

Figure 19: Fuel mix of produced heat (in percent of total generation, BAU scenario) ............ 80

Figure 20: Assumed development of the import price (in real terms) for natural gas (USD per

thousand cubic meters) ...................................................................................... 81

Figure 21: Real GDP growth rates in BAU scenario ............................................................. 82

Figure 22: Growth of sectoral gross value added in the BAU scenario ................................. 83

Figure 23: Structure of gross value added in the BAU scenario ............................................ 83

Figure 24: GHG emissions intensity of GDP in the BAU scenario (kt CO2eq per bln UAH in

prices of 2011) ................................................................................................... 84

Figure 25: GHG emissions in the BAU scenario (kt CO2eq) ................................................. 85

Figure 26: Primary energy intensity of sectoral output in manufacturing in the EEI scenario

(TJ per mln UAH in constant prices of 2001) ...................................................... 89


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Figure 27: Primary energy intensity of sectoral output in transport in the EEI scenario (TJ per

mln UAH in constant prices of 2001) .................................................................. 89

Figure 28: Primary energy intensity of sectoral output in heat supply in the EEI scenario (TJ

per mln UAH in constant prices of 2001) ............................................................ 90

Figure 29: Composition of the required energy efficiency investments (total net present value,

in bln UAH of 2011) ............................................................................................ 91

Figure 30: Dynamics of key indicators (EEI relative to BAU scenario in each year) .............. 92

Figure 31: Decomposition of the total GDP impact of the EEI scenario in 2050 (in % relative

to the baseline level of 2011) .............................................................................. 93

Figure 32: Decomposition of the total emissions impact of the EEI scenario in 2050 (in %

relative to the baseline level of 2011) ................................................................. 93

Figure 33: Sectoral GVA impacts of the EEI scenario (difference in GVA between EEI and

BAU in 2050 relative to the level of 2011, %) ..................................................... 94

Figure 34: Profitability of economic sectors in the EEI scenario (net present value of

incremental profits, as compared to BAU) .......................................................... 95

Figure 35: Profitability of key manufacturing sectors in the partial EEI scenario with only

manufacturing measures (net present value of incremental profits, as compared

to BAU) .............................................................................................................. 96

Figure 36: GHG Emissions in Ukraine and available AAUs for CP2 based on Doha

Amendment ........................................................................................................ 98

Figure 37: Available AAUs for CP2 (Doha Amendment) and estimated GHG Emissions in

Ukraine............................................................................................................... 99

Figure 38: Expected yearly levels of GDP until 2020: Outlook of 2011 vs. outlook 2013. .... 100

Figure 39: Abatements needed to keep with requirements of the Doha Amendment .......... 102


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List of Tables

Table 1: Comparison of capital and emission intensities across countries, metal industry

(2007) ...................................................................................................................14

Table 2: Comparison of capital and emission intensities across countries, minerals industry

(2007) ...................................................................................................................25

Table 3: Comparison of capital and emission intensities across countries, chemicals industry

(2007) ...................................................................................................................34

Table 4: Programme for Energy Efficiency and Energy Saving in Industry (2009-2017),

selected numbers .................................................................................................48

Table 5: Demand for energy in industry: Official forecast ......................................................49

Table 6: NERA estimations of GHG emissions from industry until 2030. Yearly % change. ..51

Table 7: Energy use and GHG emissions by activity ............................................................67

Table 8: GDP growth 2012-2019 ..........................................................................................71

Table 9: GHG abatement volume and incremental investments in Ukraine by activity ..........88


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List of Abbreviations

AAU Assigned amount unit

BAU-scenario Business-as-usual scenario

CAGR Compound annual growth rate

CP1 First Commitment Period (Kyoto Protocol)

CP2 Second Commitment Period (Kyoto Protocol)

EE Energy efficiency

EEI-scenario Energy-efficiency-investments scenario

ETS Emissions trading system

FSU Former Soviet Union

GDP Gross domestic product

GHG Greenhouse gas

LCD Low-carbon development

LULUCF Land Use, Land-Use Change and Forestry

MAC Marginal abatement cost

QELRO Quantified emission limitation or reduction objective

UAH Ukrainian Hryvna

UNDP United Nations Development Program

UNFCCC United Nations Framework Convention on Climate Change


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Management-oriented summary

This Final Report has been prepared by DIW ECON as part of the project “Capacity Building

for Low Carbon Growth in Ukraine.” Commissioned by the United Nations Development

Program (hereinafter referred to as "UNDP"), supported by the International Climate Initiative

of the Federal Ministry for the Environment, Nature Conservation and Nuclear Safety of

Germany and in service to the Ukrainian government, this report provides the results of the

economic analysis of a low carbon economic growth trajectory for Ukraine.

In particular, the report summarises the work of the consultants on the construction of a

Computable General Equilibrium (CGE) model for the economy of Ukraine, the

accompanying analytical work, as well the results of policy modelling and policy advice. The

project was implemented from June 2012 until June 2014.

The Final Report presents the deliverables as specified as # 6 and # 7 of the contract

concluded between UNDP and the consultants. The deliverables contain the following

output:

1. Sectoral Economic Analysis - development of the specific forecasting models of

certain sectors Ukrainian economy (energy, heat supply, etc.)

Chapter 1 of this report contains the final version of the sectoral economic analysis of

Ukrainian industries. The analysis covers the most important industrial sectors of the

Ukrainian economy - the metals industry, the non-metallic minerals industry and the

chemical industry in Ukraine. The developments in the energy sector are discussed in

detail in Chapter 3 of this Final Report.

2. Short analytical papers on economic analysis of policy options to support low

carbon policy analysis

Chapter 2 presents three short analytical papers:

Policy Paper No. 2 “Towards a low carbon growth strategy for Ukraine”

Technical paper No. 1 “Assessing the innovation potential in Ukraine”

“Policy options for low-carbon development in industry” (earlier version presented in

Chapter 3 of the Third Project Report)


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3. Impact assessment of identified policies and measures at the macroeconomic and

sectoral levels; development of BAU economic scenarios of Ukraine’s

development to 2020 and 2050, including but not limited to official government

forecasts and development strategies.

Chapter 3 contains the description of the computational tool that we apply for the analysis

of the low carbon development options as well as the results of the comprehensive future

baseline (BAU) scenario and of the additional energy-efficient-investments (EEI)

scenario, both covering the period 2011-2050. The results cover main macroeconomic

and sectoral indicators, energy use and GHG emissions.

This section also contains an analysis of the differentiated (by scenario) development

paths of energy efficiency for several selected energy intensive industries of the

agricultural, energy and manufacturing sectors of the Ukrainian economy (agreed as # 7

within the contract amendment 1).

4. Short-term, ad hoc expertise and consulting to decision-makers and key

stakeholders for current topics on the political agenda

Chapter 4 discusses the implications of the climate talks in Doha for Ukraine.

5. Concept of a low carbon development plan of Ukraine setting out a vision of the

country’s new development path up to 2020 and 2050.

Chapter 5 contains the executive summary of Policy Paper 6 “From Stabilisation to

Sustainable Economic Growth” (s. Appendix C-1) that sets out the plan of economic

development for Ukraine.

6. Findings from the economic assessment of the proposed domestic emissions

trading system and possibilities for linking the Emissions Trading System (ETS) in

Ukraine with other Former Soviet Union countries, particularly Kazakhstan.

Chapter 6 discusses the issue of measurement, reporting and verification in case of

linking a future linking a potential ETS in Ukraine with other systems.


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Executive summary

This is the final report prepared by the consultants of DIW ECON in the frame of the on-going

project on development of a low carbon growth strategy for Ukraine. The project was

commissioned by UNDP and is funded under the international climate change initiative of the

German Federal Ministry for the Environment, Nature Conservation and Nuclear Safety. The

project is jointly implemented by DIW ECON and Thompson Reuters. The beneficiaries of

the consulting services are the State Environmental Investment Agency (SEIA) of Ukraine

and the Government of Ukraine.

The project aims to strengthen the institutional capacity of Ukraine to design and implement

long-term policies and measures directed at reducing emissions of greenhouse gases and

enhancing absorption by sinks. In particular the project will support the Government of

Ukraine in developing a low emission pathway for Ukraine‟s long-term economic

development. To this effect the project aimed to:

Develop new generation GHG models and comprehensive projections of GHG

emissions;

Prepare the concept of Ukraine's low carbon growth strategy until 2020 and 2050;

Prepare an enabling environment for the introduction of a domestic emissions

trading scheme in Ukraine;

Improve the measurement, reporting and verification of greenhouse gas emissions;

Strengthen the institutional capacity to implement climate change policies in Ukraine.

The final project report by DIW ECON summarizes the work done in order to reach these

goals.

Chapter 1 contains the final version of the sectoral analysis of Ukrainian industries. We

apply the methodology of international efficiency benchmarking. As a result, a technological

yardstick allowing to quantify the potential for reducing greenhouse gas emissions is

determined for each sector. For the metal industry, we estimate an emission reduction

potential of up to 30 percent when taking into account the specific production structure of the

metal industry in Ukraine. In absolute terms, this corresponds to a GHG emission reduction

potential of up to 27 Mt of CO2 equivalent per year. For the non-metallic mineral products

industry a full realisation of the reduction potential would result in abating 11 Mt of CO2


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equivalent per year. For the chemicals and chemical products industry our analysis shows

that there is an emission savings potential of at least 1 Mt of CO2 equivalent per year through

technical improvement. The analysis also shows an additional emission savings potential

through scale adjustments.

Chapter 2 includes three papers that were presented in the earlier reports.

Policy Paper No. 2 “Towards a low carbon growth strategy for Ukraine” argues that promising

sectoral policies leading to sustainable growth include the modernization of the capital stock

in the industrial sectors, the liberalization of the energy market, deregulations in the heating

and electricity sectors as well as improved heat containment in residential buildings and the

introduction of fuel taxes for private transport.

Technical Paper No. 1 “Assessing the innovation potential in Ukraine: Recent track record

and implications for low-carbon development” evaluates the capacity of patented technology

in Ukraine to induce economic growth and concludes that growth of Ukrainian GDP was

driven much less by R&D than in other nations, implying that Ukraine‟s domestic capacity for

a growth path driven by technological innovation is still limited at the moment. We conclude

that the switch of the Ukrainian economy towards a low carbon economic growth trajectory

will require initially large transfers of technology from abroad. This should be accompanied

by efforts to increase domestic research capacity.

Paper “Policy options for low-carbon development in industry” reviews the existing policy

proposals for future development in Ukraine‟s industry and shows that the current policies of

Ukraine are not well coordinated and do not rely strongly enough on exploring the existing

high potentials for energy saving in industry. It then formulates a set of energy efficiency

policies consisting of fiscal, financial, market and informational policies, and measures to be

implemented by the government

Chapter 3 contains the description of the computational tool that we apply for the analysis of

the low carbon development options as well as the results of the comprehensive business-

as-usual (BAU) scenario and an additional energy-efficient-investments (EEI) scenario

covering the period 2011-2050. The BAU scenario is characterized by 4% annual average

growth rate of GDP and decreasing GHG intensity of the economy. The latter is achieved by

the continuing improvements of energy efficiency in the industry as well as by the massive


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investment in the modernization of the power sector. The BAU scenario assumes the

realization of the current IMF support program in the part of the reduction of energy subsidies

and increase of heat and gas tariffs.

The energy-efficient-investments (EEI) scenario investigates the economic effects of

additional investments into measures improving energy efficiency in industry, heating, and

transport. The scenario is constructed based on the results provided by Thomson Reuters

Point Carbon in the framework of this project. The results suggest the advantage of

investments into energy efficiency in industry a compared to energy efficiency of residential

buildings due to more rich feedback effects on the overall economy.

Chapter 4 discusses the implications of the climate talks in Doha for Ukraine. The presented

analysis (finished before the unfolding of the political crisis in Ukraine) shows that the

emission target imposed by 2012 Doha Amendment for the second commitment period from

2013 to 2020 is achievable with some additional political efforts and is economically

reasonable for Ukraine.

Chapter 5 illuminates how liberalizing the energy market, including abolishing subsidies, can

ignite sustainable economic growth. To unlock Ukraine‟s growth potential, investments for

economic diversification and capital stock modernization are needed. Such investments can

be spurred in the long-term by government measures that underpin property rights, fight

corruption and minimize red-tape, along cost-covering energy tariffs. As neither the economic

nor the political situation in Ukraine allow to wait, a complementary policy of public support

for kick-starting private investments in capital stock modernization, infrastructure and

buildings is essential for energy efficiency and economic diversification. As public budgets

will not be able to provide the necessary funds, the government needs to secure funding

through international donors willing to support economic reconstruction and reduce carbon

emissions that mitigate pressures on global warming along the way.

Currently no further steps have been undertaken in Ukraine to implement an ETS. Instead,

the actual political discussion is focusing on introducing a CO2-tax. Therefore, the

assessment of possibilities for linking the ETS in Ukraine with other FSU countries is of

hypothetic value. The contribution of DIW ECON included in Chapter 6 covers the major

issues in case an ETS would be developed and implemented in the future. It is

predominantly dealing with linking of systems allowing for trading of emissions on the level of


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companies. The term “linking” is treated as full direct connection of existing emissions trading

systems allowing non-restricted bi- or multilateral trading.


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1. Sectoral economic analysis

This section presents the findings of a detailed sectoral analysis on GHG mitigation

potentials in the metal, the non-metallic minerals and the chemical industry in Ukraine.

1.1 Introduction and summary of main results

Determining green growth potentials in Ukraine requires detailed analyses at the sector level.

This includes assessing economic viability as well as environmental sustainability of different

industrial activities. The focus of the analysis is on the metal industry, the non-metallic

mineral products industry (i.e. production of clinker, lime, glass and soda ash) and the

chemical industry in Ukraine.

We use an international benchmarking approach based on the economic concept of

efficiency. Our yardstick for comparing the performance of industrial activities in different

countries is given by:

High levels of desired outputs (production volumes or revenues),

Low levels of undesired outputs (greenhouse gas emissions), and

Low levels of factor inputs (labour, capital, energy).

Our international benchmark approach includes the following steps:

First, we compare the different industrial activities across relevant countries to identify

the countries with the highest level of efficiency (i.e. with the highest volumes of gross

output with lowest level of emissions from a given set of inputs).

We then analyze whether and to what extent special characteristics of the production

structure (such as the volume of aluminium production in the metal industry) need to be

considered when comparing the estimated efficiency levels.

Third, we assess whether the efficiency levels are determined by the general level of

economic development in the country (i.e. whether the country is a high-, medium or low-

income country) or by specific regulatory conditions in the energy sector.


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Based on these three steps we determine a technological yardstick of international best

practices. Against this benchmark, we then quantify the potential for reducing greenhouse

gas (GHG) emissions in each of the three industrial sectors in Ukraine.

The analysis yields the following results:

Metal Industry

Structural characteristics (primary steel making and the production of aluminium and

ferroalloys) need to be considered when comparing efficiency levels across

countries.

For the metal industry in Ukraine, we identify significant potentials for reducing GHG

emissions:

As long as Ukraine‟s current level of economic development and its specific

conditions in the energy sector are considered, the emission reduction

potential is estimated at up to 23 Mt of CO2 equivalents (or equivalently 25

percent of the emission level in the metal sector in 2007);

Without explicit consideration of the country‟s level of economic development

and its specific conditions in the energy sector, the estimated emission

reduction potential amounts to 27 Mt of CO2 equivalents (or equivalently 30

percent of the emission level in the metal sector in 2007).

Non-metallic minerals industry

Structural characteristics are found to have no impact for an international

comparison of efficiency levels.

The emission reduction potential of the non-metallic minerals industry in Ukraine is

estimated at up to 11 Mt of CO2 equivalents (or equivalently 47 percent of the

emission level in the minerals sector in 2007).

Chemical Industry

Structural characteristics (the production of ammonia) need to be considered when

comparing efficiency levels across countries.

The emission reduction potential of the chemicals industry in Ukraine is estimated at

up to 1 Mt of CO2 equivalents (or equivalently 5 percent of the emission level in

the chemicals industry in 2007).

The approach of the analysis and its results are described in more detail below.


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1.2 The Benchmarking Approach

The key objective of the benchmarking approach is to identify technology options for a given

industrial sector to best combine economic viability and sustainability. The yardstick for this is

a balanced combination of:

High levels of desired outputs such as production volumes (in physical units) or revenues

(values),

Low levels of undesired outputs like emissions or pollution, and

Low levels of factor inputs like labour or energy use, or production costs.

The focus of the benchmarking approach is on technologies that are currently in use in

Ukraine, while theoretical solutions and technologies that are not yet implemented are not

considered. Thus, only technically as well as economically feasible and viable solutions are

considered as benchmarks.

In economic terms, a combination of high (desired) outputs and low inputs (as well as

undesired outputs) is considered to be efficient. In principle, efficiency levels can be related

to technology scale as well as price levels (see Box 1). For practical applications, however,

such a comparison is strongly limited to the availability of data and relevant information. In

particular, micro-level benchmarking of different installations or companies within a country

requires access to private and often confidential information. Alternatively, we propose

benchmarking the same industry across different countries. That way, detailed company- or

even installation-specific information is compensated by aggregate information from a range

of countries, which is more easily available. Moreover, such an international benchmarking

also allows for identifying international best practices.


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Box 1: The concept of economic efficiency

Efficiency is an economic concept that describes the optimal use of production factors in

production processes. In economic terms, efficiency is evaluated as the relationship

between the quantities of primary factor inputs such as labour, capital or energy (henceforth

inputs) and specific goods such as steel, chemicals or food (henceforth outputs) which are

produced from these inputs. Efficiency is typically defined as either:

The lowest-possible amount of inputs for the production of a given set of outputs (input-

oriented efficiency); or

The highest-possible level of outputs that can be produced from a given set of inputs

(output-oriented efficiency).

Modern efficiency measurement starts by decomposing overall economic efficiency levels

into several subcomponents that can be measured separately:

Technical efficiency describes the ability of a firm to obtain optimal combinations of

input and output quantities.

Scale efficiency describes the ability of a firm to produce output while optimising all

scale economies.

Overall efficiency describes the ability of a firm to obtain optimal combinations of input

and output quantities while optimising all scale economies.

Price efficiency is the most restrictive criterion which also reflects the ability of a firm to

combine inputs and outputs in optimal proportions, given their respective price levels.

In the present analysis, the focus will be on technical efficiency.

In order to determine the countries with the most-efficient combination of inputs and outputs

(i.e. the most efficient technologies) we apply a specific empirical estimation technique, the

Data Envelopment Analysis (DEA). This is a well-established methodology for estimating

different efficiency measures (as described in Box 1) based on a large variety of different

input and output measures. For each country, it estimates the share of input factors that are

used efficiently or, in other words, in line with international best practice. Hence, a value of

one refers to a fully-efficient country while all values below one indicate an inefficient use of

input factors.


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In practice, it is common to estimate these efficiency scores in two steps. The first step

calculates efficiency levels based on the number of outputs that are produced from a given

set of inputs (as described above). In a second step, these efficiency results are related to a

variety of contextual factors which might have an impact on efficiency. These can include for

example the level of development of a country, its resource endowment or its production

structure. This allows taking into account specific country-related or activity-related

characteristics to explain differences in efficiency across countries and for determining

emission reduction potentials in the different countries.

1.3 Benchmarking the metal industry

This section describes the results from applying the international benchmarking approach to

the basic and fabricated metals industry in Ukraine. The focus of interest is the relationship

between the inputs used in the production processes in different countries (i.e. labour, capital

and energy) and the respective outputs in terms of gross output and greenhouse gas (GHG)

emissions. For ease of notation the basic and fabricated metals industry is henceforth

referred to as metals industry.

1.3.1 Database

The data on the metal industry in different countries stems from four key sources:

the World Input Output Database (WIOD) which has been compiled by a consortium of

scientific organizations with financial support of the European Union1,

the Steel Statistical Yearbook of the Worldsteel Association2,

the United States Geological Survey Mineral Resources Program3, and

the United Nations Framework Convention on Climate Change (UNFCCC)4.

The WIOD database is broken down by various industries that are based on the International

Standard Industrial Classification (ISIC) of the United Nations Statistics Division. In this

standard, the metal industry is classified into “Manufacturing of basic metals” and

1 http://www.wiod.org/

2 http://www.worldsteel.org/

3 Minerals Yearbook, http://minerals.usgs.gov/

4 National Inventory Submissions 2012, http://unfccc.int/national_reports/annex_i_ghg_inventories/

http://www.wiod.org/

http://www.worldsteel.org/

http://unfccc.int/national_reports/annex_i_ghg_inventories/


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“Manufacturing of fabricated metals”.5 This includes the production of pig iron, crude steel

(primary or secondary fusion), precious and non-ferrous metals as well as metal casting and

the production of fabricated metal products.6 The UNFCCC database contains detailed

information on the different industrial sections as well as on industrial products. The USGS

Minerals Yearbook and the Steel Statistics Yearbook of the Worldsteel Association solely

provide data on industrial products.

The choice of countries to be included in the international benchmarking exercise is based

on the objective to primarily cover potential technological leaders of the sector. The chosen

country sample includes 16 European Union (EU) countries and 11 non-EU countries (as

listed in Table 1) for which the following information is available:

GHG emissions (in thousand tonnes of CO2 equivalent, source: WIOD 2012)7,

Energy Use, Emission Relevant (in TJ, source: WIOD 2012)8,

Gross Output (in millions of US dollars, source: WIOD 2012),

Number of persons employed (in thousand persons, source: WIOD 2012),

Real fixed capital stock (in millions of US dollars, source: WIOD 2012),

GDP per capita in Purchasing Power Parities (PPP) (in international US Dollar, source:

WEO 20139)

Total primary energy consumption per dollar of GDP (energy intensity) (Source: EIA

201310)

Production of pig iron (in thousand metric tonnes, source: Worldsteel Association),

Production of crude steel (in total and by production process, all in thousand metric

tonnes, source: Worldsteel Association),

Production of non-ferrous metals (aluminium and ferroalloys, in thousand metric tonnes,

source: United States Geological Survey Mineral Resources Program)

The most recent information available for all countries is of the year 2007 which therefore is

chosen as base year in the benchmarking analysis.11 Ukraine is included in all sources

5 ISIC Rev 3.1 division 27 and 28. http://unstats.un.org/unsd/cr/registry/regcst.asp?Cl=17.

6 Note that the analysis does not include the mining of metal ore and the production of coke.

7 UNFCCC for Kazakhstan and Ukraine.

8 UNFCCC for Kazakhstan and Ukraine.

9 IMF World Economic Outlook Database (WEO) 2013. http://www.imf.org/external/ns/cs.aspx?id=28.

10 U.S. Energy Information Administration (EIA). International Energy Statistics. http://www.eia.gov/cfapps/ipdbproject/iedindex3.cfm?tid=90&pid=44&aid=8


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except from WIOD. The missing levels of gross output, persons employed and capital stock

are therefore taken from national statistics.

1.3.2 The metal industry in selected countries

Table 1 gives a first impression of the performance of different countries in the metal

industry. The first two columns (I and II) refer to sustainability (emissions per output) and the

third and fourth column to economic viability (output per capital input) of the production

processes in the different countries. For ease of comparison, the three top performers of

each column are shaded in grey. With respect to sustainability (columns I and II) Brazil,

France, Italy, Spain and Turkey show top performance, while Bulgaria, Canada, Finland,

Poland, Romania and Russia are the top countries with respect to economic viability

(columns III and IV)12.

11 In fact, 2007 is a good choice for a base year since it is the last year before the start of the global economic crisis.

12 Note that values for columns III and IV are not available for Kazakhstan since there is no reliable estimate on capital stocks.


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Table 1: Comparison of capital and emission intensities across countries, metal industry (2007)

2007

Emissions per revenue

Emissions per volume of production

Revenue per capital stock

Volume of production per capital stock

(tons of CO2-eq per thousand US-

$)

(tons of CO2-eq per ton of metal

product) (US-$ per US-$)

(tons of metal products per

thousand US- $)

(I) (II) (III) (IV)

Australia 0.84 2.03 1.28 0.71

Austria 0.47 1.00 2.15 0.79

Belgium 0.33 0.83 1.91 1.16

Brazil 0.70 0.40 0.47 1.08

Bulgaria 6.25 2.13 0.81 5.09

Canada 0.47 1.07 3.30 1.38

Czech Republic 0.96 1.08 1.57 1.63

Finland 0.35 0.87 2.84 1.24

France 0.18 0.76 2.27 0.64

Germany 0.29 0.90 2.32 0.82

Hungary 0.46 1.00 1.89 1.15

India 1.28 1.15 0.80 0.94

Italy 0.14 0.60 1.31 0.38

Japan 0.28 0.80 1.03 0.36

Kazakhstan 6.31 2.81

Korea 0.53 1.02 1.98 1.23

Mexico 0.53 0.91 1.97 1.15

Netherlands 0.28 0.64 2.17 1.05

Poland 0.63 1.39 3.31 2.15

Romania 1.79 1.05 1.85 3.91

Russia 3.68 1.56 2.02 4.35

Slovakia 1.05 1.06 2.16 2.69

Spain 0.19 0.61 1.50 0.42

Sweden 0.24 0.70 1.86 0.81

Turkey 0.20 0.57 1.73 0.94

Ukraine 3.88 1.15 1.87 1.09

United Kingdom 0.45 1.27 2.55 0.78

United States of America 0.34 2.29 2.25 0.66

Source: DIW ECON based on WIOD, Worldsteel Association, UNFCCC,

State Statistics Service of Ukraine, Agency of Statistics of the Republic of Kazakhstan


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The isolated comparison of the different indicators does allow identifying the leaders in each

respective category, but not for deriving conclusions about the overall performance of a

country with respect to efficiency, i.e. about the best combination of sustainability and

economic viability. This is the objective of the benchmarking approach to be carried out in the

next section (section 1.3.3). Two further issues have to be considered:

First, the costs of production (inputs) do not only include capital but also other key inputs

such as labour and energy use. These three inputs will be considered in the international

benchmark analysis.

Second, a range of different products are produced in the metal industry including pig

iron, crude steel, non-ferrous metals (aluminium) based on different production

processes. A feasible efficiency measure must therefore take into account the relevant

structural characteristics of the metal industry. This is to be done in section 1.3.4.

1.3.3 Efficiency benchmarking

The efficiency benchmarking of the metal industry is based on output-oriented efficiency

measures of technical efficiency (see Box 1). In other words, we identify the countries that

are able to produce the highest volume of gross output with the lowest level of emissions

from a given set of inputs (output-oriented efficiency). All efficiency estimates are given as

indices ranging from zero to one, with one indicating best performance. For example, a

technical efficiency score of one for a given country indicates that in no other country within

the sample the metal industry produces more outputs from the same combination of inputs.

Likewise, a technical efficiency score below one suggests that in at least one other country

the metal industry is capable to produce more outputs from the same inputs.

The following set of inputs and outputs is used for benchmarking the metal industry:

Inputs

Real fixed capital stock in the metal industry

Number of persons employed in the metal industry

Energy used in the metal industry

Outputs

Gross output generated in the metal industry

GHG emissions generated by the metal industry


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Figure 1 shows the estimated technical efficiency levels of the metal industry in selected

countries for the year 2007. Separate results for scale efficiency and overall efficiency

(technical & scale efficiency) are shown in the Appendix A.

Figure 1: Technical efficiency levels of metal industries in selected countries (in 2007)

Source: DIW ECON

The results of the efficiency benchmark with respect to technical efficiency can be

summarized as follows:

In 15 out of the 27 countries in the sample (Belgium, Bulgaria, Canada, Finland, France,

Germany, Hungary, Italy, Japan, Korea, Poland, Spain, Sweden, the United Kingdom

and the United States) the metal industry operates technically efficient. These countries

determine the technology frontier of the metal industry in an international comparison.

In the remaining countries (i.e. Australia, Austria, Brazil, Czech Republic, India, Mexico,

the Netherlands, Romania, Russia, Slovakia, Turkey and Ukraine) the metal industry

suffers from technical inefficiency.

The estimated technical efficiency level for Ukraine is 0.57. Only Brazil, the Czech

Republic and India have a lower technical efficiency level in the metal industry.


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Out of the 15 technically efficient countries 6 countries (Germany, Italy, Japan, Korea,

The United Kingdom and the United States) are technically efficient but not overall

efficient (see Appendix A). This is due to the fact that these countries operate at a too

large scale, i.e. underutilization of available production capacities.

Productivity measurement over time

In order to assess the change of productivity over time a special index is used. It measures

the technical and productivity changes over time and can be explicitly decomposed into a

measure of efficiency change and the rate of technological progress. Applying this index to

our model, a yearly improvement of total productivity of on average 1.6 percent is estimated

for the period 1998 to 2007. This change is driven by a reduction in efficiency of on average

0.5 percent per year and a technological progress of on average 2.2 percent per year.

1.3.4 Adjustment for structural characteristics

This section is aimed at analyzing the relationship between technical efficiency and the

production structure of the metal industry across countries. That is, we want to assess

whether differences in the efficiency scores may be attributable to differences in the

production structure of the metal industries across countries. If that is the case, the estimated

efficiency scores of section 1.3.3 have to be adjusted for country specific structural

characteristics.

The choice of production variables for our analysis is based on the classification of UNFCCC

for metal products as presented in the GHG emissions inventory submissions13. This

classification includes the following metal products:

Pig iron

Crude steel

Crude steel produced in oxygen blown converters (OBC)

Crude steel produced in open hearth furnaces (OHF)

Crude Steel produced in electric arc furnaces (EAF)

Aluminium

Ferroalloys

13 United Nations Framework Convention on Climate Change (UNFCCC) (2013): Annex I Party GHG Inventory Submissions. Sectoral report for industrial processes.


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The production of crude steel can be divided into primary and secondary steelmaking.

Oxygen blown converters (OBCs) and open hearth furnaces (OHFs) are methods of primary

steelmaking in which pig iron is transformed into crude steel. Electric arc furnaces (EAFs) in

contrast are mostly used for secondary steelmaking based on metal scrap. The difference

between primary and secondary steelmaking is of particular relevance since they represent

different production chains and differ strongly in energy consumption and generation of

greenhouse gas emissions.

Taking into account these differences in production chains and energy consumption, we

group the different metal products into three categories:

Pig iron & primary steel (OBC and OHF)

Secondary steel (EAF)

Aluminium & ferroalloys

Figure 2 gives an overview across countries of the production volumes of these product

groups in a) absolute and b) relative terms. Japan, the United States and Russia are the

biggest metal producers in absolute terms with production volumes of more than 120 million

tons. Bulgaria and Hungary are the countries with the lowest volumes of metal production

with less than 10 million tons. In Ukraine, total metal production amounts to about 80 million

tons in 2007. In relative terms, the share of pig iron & primary steel is on average the highest

across countries, ranging from 35 percent in Spain to over 95 percent in the Netherlands. In

Ukraine, the share of pig iron and primary steel amounts to over 95 percent. The second

biggest share of production across countries is secondary steel. The countries with the

highest share of secondary steel are Mexico, Spain, Turkey and Italy. In Ukraine, secondary

steel production has a share of 2 percent. While primary and secondary steel are produced

in all countries14, aluminium and ferroalloys are only produced in 19 of the 28 countries and

with shares of less than 5 percent in most cases. In Ukraine, the production of aluminium and

ferroalloys accounts for 2.5 percent of total production15. Only in Kazakhstan, Canada and

Australia the production of aluminium and ferroalloys exceeds 10 percent of total metal

production.

14 Except from Kazakhstan where no secondary steel is produced.

15 In the context of our analysis total metal production refers to the sum of production of pig iron, crude steel, aluminium and ferroalloys.


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Figure 2: Structural characteristics of the metal industry in selected countries (2007)

a) Output composition in absolute terms

Source: DIW ECON

* Volumes of production for Japan cut from above for better representation. Full data: 176 million tons of pig iron and primary steel, 31 million tons of secondary steel, 0.9 million tons of non-ferrous metals.

b) Output composition in relative terms

Source: DIW ECON


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Apart from the shares of production, the following variables are included in the estimation:

GDP per capita as a measure for the stage of economic and technical development of

the country;

Energy intensity as a measure for the regulatory framework conditions in the energy

sector;

The time period considered is from 1997 to 2007. Apart from a positive influence of GDP and

energy intensity on technical efficiency our estimation yields the following results:

A negative influence of the share of pig iron and primary steelmaking on technical

efficiency.

A positive influence of the share of secondary steelmaking on technical efficiency

A negative influence of the share of aluminium and ferroalloys on technical efficiency.

These results imply that a focus in production on pig iron, primary steelmaking, aluminium

and ferroalloys – all of them highly energy intensive products – goes to the disadvantage of

efficiency while a focus of production on secondary steelmaking is positively related to

technical efficiency. Due to this statistically measurable influence of the production structure

on efficiency, structural characteristics need to be considered when comparing efficiency

levels across countries.

Figure 3 shows the technical efficiency scores adjusted for country-specific structural

characteristics. The green bars represent the efficiency scores as estimated by the

international benchmark analysis (see also Figure 1). The grey and red marks represent the

adjusted efficiency scores for each country. The grey marks represent the adjusted efficiency

scores when taking account of the specific production structure of each country. The red

marks represent the adjusted efficiency scores when additionally taking into account the level

of economic development of each country and the regulatory conditions in the energy sector.

In case of Ukraine, the adjustment for structural characteristics (i.e. taking account of the

focus on primary steelmaking and aluminium production) leads to an increase in the

efficiency score from 0.57 to 0.7 (see grey mark Figure 3). This implies that given the specific

production structure of its metal industry, Ukraine has an efficiency improvement potential of


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0.3.16 If we do not only take into account the specific production structure of the metals

industry in Ukraine, but also its relatively low level of GDP per capita and its high level of

energy intensity, we estimate an adjusted technical efficiency score of 0.75 (see red mark in

Figure 3). In that case, Ukraine has an efficiency improvement potential of 0.2517 in the metal

industry.

Figure 3: Technical efficiency levels adjusted for structural characteristics

Source: DIW ECON

1.3.5 Summary and implications for the metal industry in Ukraine

The international benchmark analysis of the metal industry has placed Ukraine among the

countries with poor performance in terms of technical efficiency. A closer look at the

production structure of the metal industries across countries has given evidence that

structural characteristics are relevant for an international comparison of efficiency. Given

Ukraine‟s specific production structure in the metal industry, i.e. its focus on highly energy

16 Maximum value of technical efficiency minus adjusted efficiency score (1 – 0.70 = 0.3).



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intensive products, the estimation results imply the following emission reduction potentials

through technological improvement:

An emission reduction potential of up to 30 percent when taking into account the specific

production structure of the metal industry in Ukraine. In absolute terms, this corresponds

to a GHG emission reduction potential of up to 27 Mt of CO2 equivalents.18

An emission reduction potential of up to 25 percent when taking into account the specific

production structure of the metal industry in Ukraine as well as its level of economic

development and the regulatory framework conditions in the energy sector. In absolute

terms, this corresponds to a GHG emission reduction potential of up to 23 Mt of CO2

equivalents.19

18 As exemplary calculated for the year 2007.



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1.4 Benchmarking the non-metallic minerals industry


the non-metallic minerals industry, i.e. the production of clinker, lime, glass and soda ash. As

before, the focus of interest is on the relationship between inputs used in the production

processes in different countries (labour, capital stock and energy used) and outputs in terms

of gross output and GHG emissions. For ease of notation the non-metallic mineral products

industry is henceforth referred to as minerals industry.

1.4.1 Database

The two main sources providing data on the minerals industry in different countries are:

The World Input Output Database (WIOD) which has been compiled by a consortium of

scientific organizations with financial support of the European Union20, and

The United Nations Framework Convention on Climate Change (UNFCCC)21.

Additional data stems from:

The United States Geological Survey (USGS) Mineral Resources Program22, and

The Organisation for Economic Cooperation and Development (OECD) 23

The choice of countries to be included in the benchmarking analysis is based on the

objective to primarily cover potential technological leaders of this sector. The chosen country

sample for the minerals industry includes 18 European Union countries and 10 non-EU

countries (as listed in Table 2) for which the following information is available:

GHG emissions (in thousand tonnes of CO2 equivalent, source: WIOD 2012)24,

Energy Use, Emission Relevant (in TJ, source: WIOD 2012),

Gross Output (in millions of US dollars, source: WIOD 2012),




22 Minerals Yearbook, http://minerals.usgs.gov/

23the SDBS Structural Business Statistics (ISIC Rev 3), http://stats.oecd.org/Index.aspx?DataSetCode=SSIS_BSC

24 For Kazakhstan and Ukraine GHG emissions are calculated based on UNFCCC data.




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Total production of clinker (in kilo tonnes, source: UNFCCC, USGS),

Total production of glass (in kilo tonnes, source: UNFCCC, OECD),

Production of lime (in kilo tonnes, source: UNFCCC, USGS),

Production of soda ash (aluminium kilo tonnes, source: UNFCCC, USGS)


WEO 201325)


201326)

Since the most recent information for all countries is available for 2007, this year is chosen

as base year for the benchmarking analysis. 27 Ukraine is included in all sources except from

WIOD. The missing levels of gross output, capital stock, persons employed and energy used

in the minerals industry are therefore taken from national statistics.

1.4.2 The non-metallic minerals industry in selected countries

Table 2 gives a first impression of the performance of different countries in the non-metallic

minerals industry. The first two columns (I and II) refer to sustainability (emissions per output)

and the third and fourth column to economic viability (output per capital input) of the

production processes in the different countries.28 For ease of comparison the three top

performers in each column are shaded in grey. With respect to the sustainability (columns I

and II) Czech Republic, Finland, Ireland, the Netherlands and Romania show top

performance while Canada, Romania, Russia, Ukraine and the United Kingdom are the top

countries with respect to economic viability (columns III and IV). Since the production data is

not completely available for all countries, some of the entries in Table 2 are left blank.



27 In fact, 2007 is a good choice for a base year since it is the last year before the start of the global economic crisis.

28 For countries where data on production is not completely available, values for columns II and IV could not be provided.


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Table 2: Comparison of capital and emission intensities across countries, minerals industry (2007)

2007





(tons of CO2-eq per thousand US-

$)

(tons of CO2-eq per ton of mineral

products) (US-$ per US-$)

(tons of mineral products per

thousand US-$)

(I) (II) (III) (IV)

Australia 1.08 0.83

Austria 0.85 1.15 1.42 1.05

Belgium 1.43 1.04 1.05 1.44

Brazil 1.56 0.94

Canada 1.09 2.05

Czech Republic 0.85 0.60 1.05 1.48

Denmark 1.17 1.25 1.26 1.18

Finland 0.61 0.82 1.77 1.32

France 0.77 0.98 1.68 1.32

Germany 0.78 0.92 1.46 1.22

Hungary 1.48 0.97 1.03 1.56

India 3.32 0.58

Ireland 0.73 0.55 1.09 1.44

Italy 1.07 1.13 1.00 0.95

Japan 0.81 0.85 0.69 0.66

Kazakhstan 5.78 1.08

Korea 1.30 1.33

Netherlands 0.32 0.89 1.64 0.60

Poland 1.41 0.91 1.52 2.35

Portugal 1.34 0.88 1.13 1.73

Romania 3.82 0.70 1.27 6.99

Russia 5.04 1.14 1.79 7.91

Slovakia 1.33 0.88 1.72 2.58

Spain 1.35 1.29 1.23 1.28

Sweden 0.94 0.97 1.59 1.54

Turkey 1.45 1.16

Ukraine 4.41 1.26 1.09 3.80

United Kingdom 0.85 0.93 1.95 1.78

United States of America 1.65 1.17 1.57 2.21

Source: DIW ECON based on wiod.org, UNFCCC, USGS,

OECD, State Statistics Service of Ukraine


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The isolated comparison of the different indicators does allow identifying the leaders in each

respective category, but not for deriving conclusions about the overall performance of a

country with respect to efficiency, i.e. about the best combination of sustainability and

economic viability. This is the objective of the benchmarking approach to be carried out in the

next section (section 1.4.3).


The efficiency benchmarking of the minerals industry is based on output-oriented efficiency

measures of technical efficiency (see Box 1). All efficiency estimates are given as indices

ranging from zero to one, with one indicating best performance.

Figure 4 shows the outcome of the international efficiency benchmark analysis with respect

to technical efficiency of the minerals industries across countries. The estimation results for

scale efficiency and overall efficiency are shown in the Appendix A.

Figure 4: Technical efficiency levels of minerals industries in selected countries (2007)

Source: DIW ECON


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The technical efficiency performance of the countries in the sample can be summarized as

follows (for the year 2007):

In 12 of the 28 countries in the sample (Australia, Canada, Finland, France, Germany,

Ireland, Japan, the Netherlands, Slovakia, Sweden, the United Kingdom and the United

States) the minerals industry operates technically efficient. These countries determine

the technology frontier of the minerals industry in an international comparison.

In the remaining 16 countries (Austria, Belgium, Brazil, Czech Republic, Denmark,

Hungary, India, Italy, Korea, Poland, Portugal, Romania, Russia, Spain, Turkey and

Ukraine) the minerals industry is technically inefficient.

The estimated technical efficiency level for Ukraine is 0.53. Only India has a lower

technical efficiency level in the minerals industry.

Out of the 12 technically efficient countries, Germany, Slovakia, Sweden, the United

Kingdom and the United States are technically efficient but not overall efficient (see

Appendix A). This is due to an inefficient scale of production which means that these

countries operate at a too large scale, i.e. underutilization of available production

capacities.


In order to assess the change of productivity over time a special productivity index is used. It

measures the technical and productivity changes over time and can be explicitly

decomposed into a measure of efficiency change and the rate of technological progress.

Applying this index to our model, a yearly improvement of total productivity of on average 2.2

percent is estimated for the period 1998 to 2007. This change is driven by an average

efficiency change of 0.3 percent per year and an average technological progress of 1.9

percent per year.


This section is aimed at analyzing the relationship between technical efficiency and the

production structure of the minerals industry across countries. We take a closer look at

structural characteristics of the non-metallic minerals sector in order to assess whether

differences in the efficiency levels across countries may be attributable to differences in the

production structure of the non-metallic minerals sectors. If that is the case, the efficiency


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scores estimated in section 1.4.3 have to be adjusted for country specific structural

characteristics.

According to the International Standard Industrial Classification (ISIC) of the United Nations

Statistics Division the minerals industry is described as “Manufacturing of other non-metallic

mineral products”.29 This includes among others the production of cement, glass and glass

products, ceramic products, lime, plaster as well as articles of concrete, plaster and cement.

For the purpose of our analysis we will focus on the production of clinker, lime, glass and

soda ash. This choice of variables is based on the classification of UNFCCC for mineral

products as presented in the GHG emissions inventory submissions.30

Clinker is an intermediate product in the production of cement and is made of limestone

and clay or shale. When these raw materials are heated in the cement kilns, they are

formed into lumps or nodules which are called clinker. To produce cement, the clinker -

sometimes together with a small portion of calcium sulphate - is pulverized into fine

powder. This procedure is used to produce Portland and other types of hydraulic

cements.

Lime is calcium oxide or calcium hydroxide and is made out of limestone. The limestone

is heated in different types of lime kilns to decompose the carbonates. Inter alia it is used

as building and engineering material and as chemical feedstock.

Glass production can be divided into four major manufactured products: containers, flat

(window) glass, fibre glass, and specialty glass. The first two types are the most common

ones and are almost completely soda-lime glass. This glass is produced by melting

silicon dioxide, sodium carbonate, and lime with a small amount of aluminium oxide and

other alkalis and alkaline earth.

Soda ash production can be divided into the production of natural and synthetic soda

ash. The natural soda ash is produced from trona or sodium-carbonate-bearing brines

whereas the synthetic soda ash is produced by one of several chemical processes that

use limestone, salt and coal as feedstock. It is commonly used as raw material in glass,

chemicals, detergents, and other important industrial products.

29 ISIC Rev 3.1 division 26. http://unstats.un.org/unsd/cr/registry/regcst.asp?Cl=17.

30 United Nations Framework Convention on Climate Change (UNFCCC) (2013): Annex I Party GHG Inventory Submissions. Report for industrial processe.


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Figure 5 gives an overview of the production volumes of these four non-metallic mineral

products across countries.31 Russia and Japan are the countries with the highest volume of

minerals production in absolute terms reaching more than 70 million tons. In Ukraine, the

production volume of mineral products amounts to about 19 million tons. All 21 countries

presented in Figure 5 produce clinker which is the product with the highest share of

production in all countries except from the Netherlands. Shares of clinker production reach

from 30 percent in the Netherlands to nearly 90 percent in Denmark and Ireland.

31 Due to the lack of production data in several countries (e.g. confidentiality issues) the sample is reduced to 22 countries.


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Figure 5: Structural characteristics of the minerals industry across countries (2007)

a) Output composition in absolute terms

Source: DIW ECON

b) Output composition in relative terms

Source: DIW ECON


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In Ukraine, the share of clinker production is about 60 percent. With the exception of the

Netherlands all countries produce lime. Soda ash is only produced in 12 countries (i.e. the

Netherlands, Portugal, Romania, United Kingdom, Ukraine, Poland, France, Germany, Italy,

Russia, and Japan) and is the product with the lowest share of production in all countries. In

Ukraine, the production of clinker is followed by the production of lime (26%), glass (6%) and

soda ash (5%).

In order to assess whether the production structure in the minerals sector has a measurable

influence on the level of efficiency, several variables potentially influencing efficiency are

considered in the estimation. These variables include the volumes of production (in absolute

and relative terms) of different non-metallic mineral products as well as GDP per capita and

energy intensity (as presented in section 1.3.4). The time period considered is from 1997 to

2007.

Our estimation results do not show a significant relationship between the production structure

of the minerals industry and efficiency. This is the case both if volumes of production in

absolute as well as in relative terms are considered. We only find some weak relationships

between single products (e.g. soda ash) and technical efficiency, but not of the entire

production structure of the sector.32 This leads to the conclusion that in case of the minerals

industry, differences in the technical efficiency levels cannot be explained by differences in

the production structure across countries. The estimated efficiency scores do therefore not

need to be adjusted for country specific structural characteristics.

1.4.5 Summary and implications for the minerals industry in Ukraine

The international benchmark analysis of the minerals industry has placed Ukraine among the

countries with poor performance in terms of technical efficiency. A closer look at the

production structure of the minerals industries across countries has not given evidence that

structural characteristics need to be considered when comparing efficiency levels across

countries.

32 Alternative approaches such as the standardization of the volumes of production by the number of employees or total revenues in the minerals sector do not show a measurable influence on technical efficiency either.


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Given Ukraine‟s current level of technical efficiency in the minerals industry of 0.53 (as

estimated based on the benchmarking approach in section 1.4.3), Ukraine has an efficiency

improvement potential of about 47 percent. In terms of GHG emissions, this corresponds to a

savings potential of up to 11 Mt of CO2 equivalents.33

1.5 Benchmarking the chemical industry


the chemical and chemical products industry. The focus of interest is again on the

relationship between the inputs used in the production processes in different countries (i.e.

labour, capital and energy) and the respective outputs in terms of gross output and

greenhouse gas (GHG) emissions. For ease of notation the chemicals and chemical

products industry is henceforth referred to as chemicals industry.

1.5.1 Database

The two major sources providing data on the chemicals industry in different countries are:

The World Input Output Database (WIOD)34, and

The United Nations Framework Convention on Climate Change (UNFCCC)35.

The chosen country sample includes 17 European Union (EU) countries and 10 non-EU

countries (as listed in Table 3) for which the following information is available:

GHG emissions (in thousand tonnes of CO2 equivalent, source: UNFCCC36),

Fuel combustion (in TJ, source: UNFCCC37),

Gross output (in millions of US dollars, source: WIOD 2012),





35the National Inventory Submissions 2013, http://unfccc.int/national_reports/annex_i_ghg_inventories/national_inventories_submissions/items/7383.php

36 For countries not included in UNFCCC database and for the USA, data from WIOD was taken




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WEO 201338)


201339)

Since the most recent information for all countries is available for 2007, this year is chosen

as base year for the benchmarking analysis. Ukraine is included in all sources except from

WIOD. The missing data on gross output, persons employed and capital stock is therefore

taken from national statistics.

1.5.2 The chemicals industry in selected countries

Table 3 gives a first impression of the performance of different countries in the chemicals

industry. Due to the lack of production data there is only one column for sustainable

performance (column I) and one for economic viability (column II). The third column (III)

contains a ratio on emissions per energy use. For ease of comparison, the three top

performers in each column are shaded in grey. With respect to the sustainability indicator

Austria, Italy and Sweden show top performance while France, Korea and Turkey are the

best countries with regards to economic viability. The lowest levels of emissions per energy

used are in Germany, Korea and the USA.




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Table 3: Comparison of capital and emission intensities across countries, chemicals industry (2007)

2007



Emissions per energy use

(tons of CO2-eq per thousand US-$) (US-$ per US-$)

Tons of CO2-eq per TJ Energy

(I) (II) (III)

Australia 0.85 0.90 0.13

Austria 0.17 1.76 0.09

Belgium 0.30 1.67 0.09

Brazil 0.41 0.79 0.07

Canada 0.41 2.11 0.10

Czech Republic 1.65 1.23 0.10

Finland 0.40 1.79 0.18

France 0.19 3.96 0.08

Germany 0.21 1.80 0.06

Greece 0.44 1.76 0.10

Hungary 1.06 0.48 0.18

India 0.80 0.92 0.10

Italy 0.16 1.33 0.08

Japan 0.22 0.81 0.07

Korea 0.18 2.53 0.05

Netherlands 0.43 2.09 0.11

Poland 0.80 2.21 0.20

Portugal 0.52 1.58 0.10

Romania 2.96 1.82 0.13

Russia 1.45 1.38 0.18

Slovakia 1.32 2.21 0.12

Spain 0.23 1.60 0.07

Sweden 0.09 1.85 0.07

Turkey 0.18 3.09 0.12

Ukraine 1.83 1.06 0.11

United Kingdom 0.25 1.31 0.09

United States of America 0.38 1.84 0.05

Source: DIW ECON based on wiod.org, Worldsteel Association, UNFCCC,

State Statistics Service of Ukraine

The comparison of the different indicators allows identifying the leaders in each respective

category, but not for deriving conclusions about the overall performance of a country with

respect to efficiency, i.e. about the best combination of sustainability and economic viability.

This is the objective of the benchmarking approach to be carried out in section 1.5.3.


The efficiency benchmarking of the chemicals industry is based on output-oriented efficiency

measures of technical efficiency (see Box 1). All efficiency estimates are given as indices

ranging from zero to one, with one indicating best performance.


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Figure 6 shows the estimated technical efficiency levels of the chemicals industry in selected

countries for the year 2007. Separate results for scale efficiency and overall efficiency

(technical & scale efficiency) are shown in the Appendix A.

Figure 6: Technical efficiency levels of chemicals industries in selected countries

(2007)

Source: DIW ECON

The results with respect to technical efficiency can be summarized as follows:

In 11 out of the 27 countries in the sample (Austria, Finland, France, Greece, Italy,

Japan, Romania, Slovakia, Sweden, Turkey and the United States) the chemicals

industry operates technically efficient. These countries determine the technology frontier

of the chemicals industry in an international comparison.

In the remaining countries (i.e. Australia, Belgium, Brazil, Canada, Czech Republic,

Germany, Hungary, India, Korea, the Netherlands, Poland, Portugal, Russia, Spain,

Ukraine and the United Kingdom) the chemicals industry is technically inefficient. There

are several countries that seem to reach the maximum score of 1 in the figure (e.g.

Hungary, Korea, Portugal), but in real terms only reach scores around 0.98 and 0.99.

Since nearly all countries reach a high level of efficiency even these small differences

matter for differentiating between technically efficient and inefficient countries.


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Due the small variation in the level of technical efficiency across countries (i.e. with the

exception of India all countries have a score above 0.9), Ukraine belongs to the lower

third of the countries despite its high (in absolute terms) efficiency score of 0.95.


In order to assess the change of productivity over time a special productivity index is used. It

measures the technical and productivity changes over time and can be explicitly

decomposed into a measure of efficiency change and the rate of technological progress.

Applying this index to our model, an improvement of total productivity of on average 1.7

percent per year is estimated for the period 1995 to 2007. This change is driven by a

reduction in efficiency of on average 0.9 percent per year and by a technological progress of

on average 2.6 percent per year.


This section takes a closer look at structural characteristics in the chemicals industries

across countries. We want to assess whether differences in efficiency levels may be

attributable to differences in the production structure of the chemicals industries. If that is the

case, the efficiency scores estimated in section 1.5.3 would need to be adjusted for country-

specific structural characteristics.

The classification by UNFCCC for chemical products includes the following products:

Ammonia, Nitric Acid, Adipic Acid, Carbide, Carbon Black, Ethylene, Dichloroethylene,

Styrene and Methanol.40 Since many of these products have similar production processes

(i.e. the products are highly correlated in statistically terms), we cannot include all of them in

the estimation. This would lead to an incorrect (i.e. biased) quantification of the impacts on

technical efficiency. We therefore choose the following two products as representative

products for the chemicals sector:

Ammonia

Carbide

These two products are considered best representatives for the chemicals industry since

they are i) correlated with the majority of other chemicals listed above (i.e. the production of

40United Nations Framework Convention on Climate Change (UNFCCC) (2013): Annex I Party GHG Inventory Submissions. Sectoral report for industrial processes.


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ammonia is highly related to the production of other chemical products) and ii) not correlated

with each other. In addition to that, ammonia is produced in all of the countries in the sample

and therefore represents a central element of chemical production.

Ammonia is a basic chemical and one of the most commonly produced industrial chemicals.

About 80 percent of the ammonia produced by industry is used as fertilizer in agriculture. 41

The rest is used as a refrigerant gas, for purification of water supplies, and in the

manufacture of plastics, explosives, textiles, pesticides, dyes and other chemicals. The main

greenhouse gas emitted from ammonia production is CO2.42

Carbide is a chemical compound composed of carbon and a less electronegative element.

The production of carbide generates emissions of CO2, methane and sulfur oxide. Silicon

carbide is a significant artificial abrasive. It is produced from silica sand or quartz and

petroleum coke. Calcium carbide is used in the production of acetylene and as a reductant in

electric arc furnaces (see section 1.3.4). It is made from calcium carbonate (limestone) and

carbon-containing reductant (petroleum coke).43

Figure 7 gives an overview of the production volumes of ammonia and carbide in selected

countries.44 In absolute terms, Russia and the United States are the biggest producers of

ammonia and carbide with production volumes of more than 10 million tons (see Figure 6 a)).

Greece and Hungary are the countries with the lowest volumes of production of ammonia

and carbide amounting to less than 0.3 million tons. All countries in the sample produce

ammonia which also accounts for the biggest share of production (compared to carbide) in all

countries. Carbide is only produced in six of the countries in our sample (i.e. Austria, Poland,

Russia, Slovakia, Ukraine and the United States). With a production volume of about 0.1

million tons, Slovakia is the biggest producer of carbide in the country comparison. In

Ukraine total production of ammonia and carbide amounts to about 5.2 million tons with

ammonia accounting for more than 5.1 million tons of production and carbide for less than

0.05 million tons.

41 http://www.health.ny.gov/.

42 Intergovernmental Panel on Climate Change (IPCC) (2006): Guidelines for National Greenhouse Gas Inventories. Chapter 8: Reporting Guidance and Tables.

43 IPCC (2006), see footnote 39.

44 Due to the lack of production data in several countries (e.g. confidentiality issues) the sample is reduced to 15 countries (Greece, Hungary, Czech Republic, Slovakia, Austria, Italy, Romania, Belgium, UK, France, Poland, Canada, Ukraine, USA, Russia).


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Figure 7: Structural characteristics of the chemicals industry in selected countries (2007)

a) Production of ammonia and carbide in absolute terms

Source: DIW ECON


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b) Per capita production of ammonia and carbide

Source: DIW ECON

In order to account for size effects (i.e. on average higher volumes of production in bigger

countries), we divide the production of ammonia and carbide by persons employed in the

chemical sector and use these per capita production variables for the estimation.45 As can be

seen in Figure 7 b) Slovakia, Canada and Ukraine are the leader countries in terms of per

capita ammonia production, with more than 25 tons of production per person employed in the

chemicals industry. Slovakia also has the highest per capita production of carbide reaching

about 8 tons per person employed in the chemicals industry. These per capita production

volumes are used as an approximation for the relative importance of ammonia (and carbide)

production across countries. That is, high volumes of per capita production of ammonia can

be interpreted as an indication for a focus of production on ammonia in that country. This is

the case for example in Canada and in Ukraine. In the United States in contrast, per capita

volumes of ammonia production are relatively low, implying that the focus of production in the

chemicals sector is not on ammonia.

The time period considered for our analysis is 1995 to 2007. The estimation yields the

following results:

45 Since we only have two products, using shares of production (as done for the metal and minerals industry) is not feasible in this case.


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A negative influence of ammonia production (per capita) on technical efficiency

A positive influence of carbide production (per capita) on technical efficiency

These results imply that a focus of production on ammonia – a highly energy and emission

intensive product – goes to the disadvantage of technical efficiency while the production of

less energy demanding products such as carbide is positively related to efficiency. Due to

this statistically measurable influence of the production structure on efficiency, structural

characteristics need to be considered when comparing efficiency levels across countries.

Figure 8 shows the technical efficiency scores adjusted for country-specific structural

characteristics. The green bars represent the efficiency scores as estimated by the

international benchmark approach (see also Figure 6). The red marks represent the adjusted

efficiency scores for each country. In case of Ukraine, the adjustment for structural

characteristics in the chemicals industry (i.e. taking into account the focus on ammonia

production) leads to an increase in the efficiency score from 0.94 to 0.95 (see Figure 8). In

terms of efficiency improvement these results imply that given the specific production

structure of its chemicals industry, Ukraine has an efficiency improvement potential of 5

percent46.



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Figure 8: Technical efficiency levels adjusted for structural characteristics

Source: DIW ECON

1.5.5 Summary and implications for the chemicals industry in Ukraine

The international benchmarking analysis of the chemicals industry has placed Ukraine at the

lower third in terms of technical efficiency performance. A closer look at the production

structure of the chemicals industry across countries has given evidence that structural

characteristics need to be considered for an international comparison of efficiency levels

Given Ukraine‟s specific production structure in the chemicals industry, i.e. its focus on

production of ammonia, the estimation results imply an emission reduction potential of 5

percent through technological improvement. In absolute terms, this corresponds to a GHG

emission reduction potential of up to 1 Mt of CO2 equivalents.47

1.6 Conclusion

The international benchmarking approach used in our sectoral economic analysis takes into

account two main aspects of industrial production processes: i) economic viability and ii)



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environmental sustainability. It allows not only to identify the countries with a good

performance in single aspects of efficiency such as emission intensity or profitability, but also

to determine the countries with the best combination of economic viability and sustainability.

Both aspects are combined in the economic concept of efficiency, which can be measured

for a specific industry in different countries and then used for comparison.

The efficiency-based international benchmarking approach is applied to the metal, non-

metallic minerals and chemicals industry. It is used to determine a technological yardstick for

each sector which then is applied to the Ukrainian context to quantify the GHG emission

reduction potential in each sector in Ukraine. The specific production structure of the sectors

plays an important role in that context. Our estimation results show large emission reduction

potentials in the three sectors in Ukraine, ranging from 5 percent in the chemicals industry,

over 25-30 percent in the metals industry up to 47 percent in the minerals industry.


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2. Short analytical papers on economic analysis

of policy options to support low carbon policies

2.1 Towards a low carbon growth strategy for Ukraine

This section includes the executive summary of the Policy Paper No. 2 “Towards a low

carbon growth strategy for Ukraine”. The paper is included as Appendix C-2 to this

Final Report.

Ukraine is one of the most energy-intensive economies in Europe. New impulses are needed

to overcome traditional production structures that are no longer efficient and unsustainable in

social and environmental terms. This paper identifies the key areas in terms of potential to

reduce greenhouse gas (GHG) emissions and derives the corresponding policy actions

needed to foster low carbon growth.

We argue that growth can only be sustained by fundamentally shifting the Ukrainian

economy away from its current carbon-intensive path to a form of growth that is less

dependent on the heavy use of natural resources, especially coal.

For a successful transition to low carbon growth, government intervention is indispensable.

Firstly, private investments into clean technologies can only be induced by increasing the

cost of emitting GHG, for example through carbon pricing or the introduction of an Emission

Trading System (ETS). Secondly, the Ukrainian government needs to promote research and

development into innovative clean technologies. Thirdly, in order to profit from possible

financial assistance and technology transfers from abroad, the Ukrainian government may

need to enter into further international commitments and guarantee a more ambitious

reduction target in the level of emissions.

The main obstacles for a transition to low carbon growth in Ukraine are the lack of

diversification of the economy, heavy reliance on expensive fossil-fuel imports, outdated and

inefficient production capacities and unsustainably high subsidies in energy pricing. This

implies a dire need for the government to increase competition, introduce market-based

prices and to improve energy efficiency across all sectors.


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The sectors with the greatest potential in terms of emission reductions are the industrial

sector, the energy sector including energy resources as well as electricity and heat

production, the transport sector and the residential sector. Promising sectoral policies include

the modernization of the capital stock in the industrial sectors, the liberalization of the energy

market, deregulations in the heating and electricity sectors as well as improved heat

containment in residential buildings and the introduction of fuel taxes for private transport.

2.2 Assessing the innovation potential in Ukraine

This section includes the executive summary of the Technical paper No. 1 “Assessing

the innovation potential in Ukraine”. The paper is included as Appendix C-3 to this

Final Report.

Innovations are crucial for shifting from a conventional to a sustainable low-carbon economic

growth trajectory. This technical paper assesses the current innovation potential in Ukraine

and infers to what extent innovations contribute to economic growth.

We analyse input and output factors of innovation in Ukraine over the recent past and across

different economic sectors:

We find that expenditures in R&D have fallen at a rate of 7% between 2005 and

2011. Thus spending in R&D measured as a share of GDP decreases from 0.14% in

2005 to 0.08% in 2011.

Sectoral R&D funding fluctuates heavily over time and has declined across all

industrial sectors except for food processing between 2009 and 2011.

Despite decreasing expenditure in R&D, patent applications and registrations have

increased from 2009 onwards. This is due to the fact that the share of foreign patent

holders increased over the last years.

Innovative outputs show high volatility and sensitivity to business cycle downturns.

The share of innovative industrial production has contracted sharply by 40%

between 2007 and 2009 and has still not reached the pre-crisis levels by 2011.

The innovation intensity of output varies widely between industrial sectors, with some

small sectors showing substantial innovative capacity.


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When comparing Ukraine with other benchmark countries we find that Ukraine is placed in

the middle field regarding the expenditure in R&D, spending a larger share of GDP on R&D

than Poland, Belarus or Kazakhstan. Compared to Russia, however, Ukraine would need to

increase R&D expenditure by a factor of 1.5. Measuring innovation by the number of

patents per capita Ukraine currently takes a place in the lower half among the

benchmark group, having 3 times less patented inventions per year, than Belarus or

Russia. The difference to the advanced economies such as the EU and the United States is

even larger.

Ukraine spends little R&D per patent. Most advanced economies spend more resources

per patent. In this regard, a low level of spending per patent may not be so much a signal of

efficiency, but rather an indication that the registered patent is not the result of prolonged

domestic innovative research.

We evaluate the capacity of patented technology to induce economic growth and conclude

that growth of Ukrainian GDP was driven much less by R&D than in other nations,

implying that Ukraine‟s domestic capacity for a growth path driven by technological

innovation is still limited at the moment.

We conclude that the switch of the Ukrainian economy towards a low carbon economic

growth trajectory will require initially large transfers of technology from abroad. This should

be accompanied by efforts to increase domestic research capacity.

2.3 Policy options for LCD in industry

2.3.1 Introduction

In 2008, direct GHG emissions made by industrial enterprises comprised more than 30% of

total emissions in Ukraine, not including indirect emissions through industrial electricity use.

Therefore, an analysis of potentials for emission reductions in industry should be an

important part of a low-carbon development plan for Ukraine.


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In the following we aim to review the existing policy proposals for future development in

Ukraine‟s industry.

We proceed as follows. First, we present the official GHG emission forecast and list the

policy goals announced by the government. Then, we compare these options with the other

recent proposals. In particular, we take the NERA report (NERA Economic Consulting, 2012)

as the most comprehensive reference for our analysis.

The analysis shows that the current policies of Ukraine are not well coordinated and do not

rely strongly enough on exploring the existing high potentials for energy saving in industry.

The conclusions offered in this chapter are preliminary though; the issue has to be analysed

in more detail based on sound empirical modelling, which is envisaged for the course of the

current project.

2.3.2 Status quo and the planned policies in industry

At present, the expectations and plans about the development of the Ukrainian industry, its

future energy demand and corresponding GHG emissions are very contradictory between

different governmental bodies.

The latest official forecast of GHG emissions, which was published in 2009, envisaged that

the emissions from industrial enterprises would rise – over the period 2010-2017 they would

grow with the average rate of 5.7-6.0% per year, depending on the scenario (“3rd, 4th and

5th National Communication of Ukraine to the UNFCCC”, 2009). According to the National

Communications, if cost-effective emission reduction measures are undertaken by industrial

enterprises, the potential emission reduction would reach 18.6 million tons of CO2-

equivalents. If advanced measures, which would specifically target emission reduction, are

undertaken, the potential for emission reduction would add another 4.9 million tons of CO2-

equivalents (see Figure 9).


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Figure 9: GHG Emissions by the Ukrainian industry, million tons of CO2-equivalents

Source: “3rd, 4th and 5th National Communication of Ukraine to the UNFCCC.” (2009). p. 181.

In early 2009, the Ministry of Industrial Policy of Ukraine adopted “The Programme for

Energy Efficiency and Energy Saving in Industry until 2017”48. The Programme aims to bring

the energy intensity of industrial processes to the standards of developed countries,

particularly the EU.49 The Ministry recognises that the successful achievement of this goal

would considerably help to secure energy independence of the country and to decrease

imports of fuels50. It is expected that substantial investments into energy efficiency will be

made by industrial enterprises from their own funds or will be facilitated by bank credits;

resources of the state budget would only cover the relevant research and development

activities. The energy demand by industrial sectors and the corresponding energy saving

goals are presented in Table 4 .

According to the Programme for Energy Efficiency, upon implementation of the envisaged

measures, the demand for primary energy by the three key emitting sectors – metallurgy,

machine building and chemistry – would grow with an annual rate of 0.93%. Evidently, the

development of the Programme has not been coordinated with the team of experts, who

were responsible for the preparation of the National Communications to the UNFCCC, where

even the most optimistic scenario of future industrial emissions does not rely on an

assumption of such high energy efficiency improvement in industry.

48 The Programme entered into force with the Order of the Minister of Industrial Policy of Ukraine No.152 from February 25, 2009.

49 At present, energy intensity of Ukraine‟s industry is 0.5 kg of oil equivalent per USD. This is 2.6 times more than the international standards (0.21 kg per USD) Source: “The Programme for Energy Efficiency and Energy Saving in Industry until 2017” (p.4) High energy intensity is often claimed to be one of the reasons for the economic crisis in the 1990s.

50 In 2010, energy import dependency ration was almost 40%. Source: OECD/IEA (2012).

60

80

100

120

140

160

1990 2000 2005 2010 2015 2020

No emission reduction measures undertaken

Cost-ef fective emission reduction measures undertaken

Advanced measures aimed on emission reduction undertaken


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Table 4: Programme for Energy Efficiency and Energy Saving in Industry (2009-2017), selected numbers

Share in

output

Energy demand,

million tons of oil

equiv.

Energy intensity, kg of oil equiv. / UAH

CAGR of

energy demand

over 2010- 2017

Planned investments,

billion UAH

2007 (status quo)

2010 (goal)

2015 (goal)

2017 (goal)

Total R&D

Non-fuel mining & metallurgy

52% 48.6 0.39 0.27 0.90% 61.3 0.5

Machine building

23% 4.6 0.08 0.069 0.06 0.06 5.26% 56.2 5.8

Chemistry 16% 12.5 0.33 0.29 0.25 0.24 -1.50% 5.7 0.5

Light industry & wood processing

9% n.a. 0.1 0.01

Total 100% 0.93%1 123.4 6.9

1 Not including light and wood processing industries.

Source: Programme for Energy Efficiency and Energy Saving in Industry until 2017. Output shares

and CAGR – own calculations.

A later official document – “The Revised Energy Strategy of Ukraine for the Period until

2030”, which was made public in 2012, – stipulates that over the next ten years the demand

for energy by industry over 2010-2017 will change as follows: the demand for natural gas will

decrease by 1.60% per year while industry demand for coal will grow by 1.4% per year. Total

energy demand will decrease by 1.2% per year in the same period. Some detailed

information is presented in Table 5.

In the framework of the Energy Strategy, the Ministry of Energy and Coal Industry plans

extensive investments, 694 billion UAH over 2010-2020, into new electricity generating

capacities (most of new power plants will be based on coal combustion) and new coal

extraction capacities in order to meet the increasing energy demand for electricity and coal

by the industry. The forecast about the future energy demand is based on about 30% to 35%

energy efficiency improvement. Although the Energy Strategy recognises an important role of

energy efficiency and emphasises the need for a comprehensive Programme of measures to


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achieve energy-efficiency goals, it does not go much further than that. While trying to secure

energy independency of Ukraine, the Ministry of Energy and Coal Industry urges the

industrial enterprises to use domestic coal and to withdraw from usage of gas, which is

imported from Russia. The coal mining sector is expected to develop very quickly: according

to the Energy Strategy, the yearly volumes of coal extraction should grow by 40-50% till

2030, whereas its consumption by industry will grow by nearly 50%.

Table 5: Demand for energy in industry: Official forecast

2010 (real data)

Forecast – basic scenario51

CAGR of energy

demand over 2010-

2017

Energy saving

potential used for the

forecast

2015 2020 2025 2030

Electricity demand, billion KWt/h

97.6 111.0 120.4 131.0 139.0 +2.1% -7%

Demand for natural gas, billion m

3

21.3 19.6 18.2 18.1 18.3 -1.6% -53%

Demand for industrial coal, million tons

3.1 3.3 3.6 4.1 4.6 1.4% n.a.

Total energy demand, million tons of oil equivalent

18390 17247 -1.2% not including electricity

-0.01% including electicity

30-35%

Source: “The Revised Energy Strategy of Ukraine for the Period until 2030.” Oil equivalent and CAGR – own calculations.

Based on official regulatory documents, developed by different Ministries, we have different

expectations with respect to future dynamics of direct GHG emissions and the demand for

energy by industrial enterprises; Figure 10 depicts the results. Whereas the Ministry of

Environmental Protection foresees extensive fuel combustion in industry and the

corresponding growth of GHG emissions by 5.77% per year, the Ministry of Energy and Coal

Policy relies on low growth of energy demand by the industry. After some recalculations for

51 Under the basis scenario, the Energy Strategy of Ukraine assumes average GDP growth at 5% up till 2030 of economic development; in pessimistic scenario, about 3.8% average yearly GDP growth is envisaged. At the same time, according to IMF, the most realistic rate for average yearly GDP growth in 2014-2018 is 3.5%. The economic growth of the last few years also does not allow for better than pessimistic view on the economy, if classified according the assumptions in the Energy Strategy.


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the Ministry‟s original set of data, we obtain that the corresponding emissions, expressed in

CO2 equivalents, would decrease yearly by almost 1%; the demand for energy would remain

stable, although the demand for fuels would decrease as well. At the same time, the Ministry

of Industrial Policy expects 1% increase yearly in demand for energy, if expressed in oil

equivalents.

Figure 10: Direct GHG emissions and the demand for energy by industrial enterprises, as foreseen by different ministries. Yearly expected percentage changes over 2010-2017.

Source: Own calculations.

First of all, the evident inconsistencies, described above, may indicate an absence of well

organised policy coordination between the governmental bodies. As we see, the

development of the industrial policy in Ukraine is currently coordinated neither with the

energy policy nor with the environmental policy52. This calls for development of a

comprehensive inter-sectoral strategy for low carbon growth in Ukraine, which must become

a foundation and an instrument for any sub-programme, which would be later on elaborated

by sectoral Ministries or lower-ranking sub-sectoral agencies.

52 The industrial policy is under responsibility of the Ministry of Industrial Policy of Ukraine; the energy policy is conducted by the Ministry of Energy and Coal Industry of Ukraine; the environmental policy the area of the Ministry of Ecology and Natural Resources of Ukraine.


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2.3.3 Potential for emission reduction in industry: Assessments from the literature

According to the recently published NERA report, there is a high potential for cost-effective

emission reduction in the Ukrainian industry (NERA Economic Consulting, 2012). Under the

assumption of static energy-intensity (status quo), there is a potential for “a reduction of over

30% of the industrial emissions that would be implied by the static intensity projection for

2030” (NERA Economic Consulting, 2012, p.65). This comprises about 65 Mt CO2

abatement, out of which 51 Mt CO2 is cost-effective. If the government undertakes enhanced

policy measures, the abatements could reach 77 Mt CO2, out of which 72 Mt CO2 is cost-

effective. If recalculated into percentage changes of emissions, NERA‟s result implies that

industrial emissions can grow by +2.53% to +4.14%. The growth rate of emissions depends

on the policy measure that is undertaken. The detailed estimations are presented in Table 3.

Table 6: NERA estimations of GHG emissions from industry until 2030. Yearly % change.

Cost-effective measures

undertaken

All potential measures

undertaken

Planned policies scenario +4.14% +2.96%

Enhance policies scenario +3.44% +2.53%

Source: NERA Economic Consulting (2012) and “3rd, 4th and 5th National Communication of Ukraine

to UNFCCC” (2009). Own calculations.

Relying on projections from the table, we may view the planned policies of the Ministry of

Industrial Policy and expectations about the future energy demand of the Ministry of Energy

and Coal Industry as relatively optimistic. A comprehensive empirical analysis, based on

realistic expectation about economic development of Ukraine and industrial growth in

particular, is urgently needed in order to develop a broad policy package.

2.3.4 What can the government do for the low carbon development?

Except many obstacles on the way to implementation of governmental strategies (financial,

lack of effective energy management systems and techniques skills, etc.), the absence of

policy coordination, wrong estimation of the status-quo platform, and little apprehension of

potential growth impulses, which may arise from cost-effective investments into green

technologies, are some of the reasons for the breakdown of the industrial strategies of the


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government even before their implementation starts. With better policy coordination and with

some additional political efforts towards energy saving, the allocation of funds between

different energy-related projects would become more effective and the Ukrainian industry

would converge to the low carbon development path. The economy would benefit from saved

energy costs, higher and sustainable growth and higher employment.

A green growth strategy for Ukraine should include a comprehensive set of energy efficiency

measures, which would benefit Ukraine while inducing growth and employment. A thorough

analysis of measures for such a programme will be done on the basis of sound empirical

modelling, which is envisaged for the course of the current project.

Within the set of energy efficiency policies consisting of fiscal, financial, market and

informational policies, and measures to be implemented by the government some of the

most relevant are:

Gradual abolishment of energy subsidies , especially for natural gas and heat to move

retail gas and heating tariffs to full cost recovery, complemented by targeted programs to

support low-income households.

Introduction of obligatory minimum energy efficiency requirements for new and

refurbished buildings as well as other energy intensive goods (i.e. household appliances,

cross sector production equipment like electrical engines, pumps, compressed air

systems etc.)

Introduction of efficient carbon taxes (raising the level of the current non-sufficient low

rates of the existing CO2-tax) or of a GHG emission trading system covering major GHG

emitters.

Tax relieves implementation of most energy efficient technologies (above minimum

energy efficiency standards)

Implementing economic incentives for use of renewable heat etc.


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3. Impact assessment of identified policies and

measures and development of BAU scenarios

until 2020 and 2050

3.1 How to assess the potential of identified policies for low-carbon

economic growth in Ukraine

Assessing the long-term impact of policies and investment proposals aiming at stimulating

carbon-neutral economic growth requires the use of complex economic models. In particular,

two issues are relevant. First, the model needs to reproduce the behaviour of all relevant

players in the economy (i.e. different firms, private households, the government etc.).

Second, the model must be based on a sound database which captures the structure and

flow of all income and expenditures in the economy, all relevant interdependencies between

different activities that arise from the use of intermediate inputs in the production processes

of other activities, as well as relevant data on Greenhouse Gas (GHG) emissions by relevant

types such as emissions from fuel combustion or process-based emissions.

A tool capable to meet these requirements is a multi-sector Computable General Equilibrium

(CGE) model. It is based on a microeconomic representation of the behaviour of different

economic activities (production sectors), private and public households as well as the

external sector. CGE models cover all product and factor markets in an economy and are

hence able to trace changes in supply, demand as well as prices of different commodities

and production factors. Because this also includes all relevant types of primary and

secondary energy, a CGE model is also capable to simulate Greenhouse Gas (GHG)

emissions from fuel combustion and other industrial processes.

In the following section, we describe the key features of a CGE model that we develop to

assess the potential for carbon-neutral economic growth in Ukraine. Apart from the key

features of the model we will describe how it will be used for simulating different growth

scenarios.


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3.2 Model description

3.2.1 Building blocks

The CGE model for Ukraine includes private households, different production activities, the

government as well as the external sector (the rest of the world). These institutions exchange

commodities and primary input factors (labour and capital) on separate markets. The model

is dynamic and the simulations cover the time period 2011-2050. The overall setup of the

model is as follows:

Private households earn income (remuneration) for labour and capital that they provide

to the production sectors and receive transfers from the government. They spend this

income for consumption of domestic and imported goods and services as well as for

savings.

Production activity in the economy is represented by 23 different sectors (covering

agriculture, mining, manufacturing, utilities, transport and services). They employ labour

and capital and use intermediate inputs to produce their specific output. Production

sectors export (a part of) their output and/or sell it on domestic markets, where the total

demand is represented by the intermediate demand (by production sectors) and final

demand (by private households, gross capital formation or the government).

The government receives income from its capital endowment as well as tax revenue

(e.g. from import duties). It uses this income to finance subsidies and transfer payments

to private households and public investments as well as for providing public goods and

services.

The rest of the world represents an aggregate of all countries, which export to or import

from Ukraine or which interact with Ukraine in financial transactions. It hence absorbs

exports from Ukraine and provides imports in return. It also provides investment

opportunities abroad to private households and owns some Ukrainian assets.

This setup requires considering the following markets:

Factor markets for labour and for capital (the so-called primary input factors):

Supply is determined by the factor endowments (changing over time) of households

and the government;

Demand is derived from production activities.


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Commodity markets for each of the goods and services that are produced and/or

consumed in the country:

Supply is given by the output of the respective industries + imports;

Demand is derived from intermediate and final consumption (including export).

Market for investment goods:

Supply of domestic investment goods is provided by two sources: a separate activity

that uses various commodities as inputs for new capital formation as well as by

government issuing bonds in order to finance the budget deficit.

Investment demand is matched by the corresponding amount of public and private

savings which include savings by Ukrainian residents and foreigners (where the

latter is consistent with Ukraine‟s current account deficit).

Foreign exchange market:

Supply is given by export earnings and well as by purchases of Ukrainian assets by

foreigners;

Demand is derived from the demand for imported intermediate and final goods and

services as well as from the demand for overseas investments.

3.2.2 Production technology

Production of goods and services is modelled by specific production functions. For each

activity, they determine the amounts of different inputs necessary for producing a given

amount of output. Technically, all production functions are of the Constant Elasticity of

Substitution (CES) type.53 Since the substitutability of specific input factors can be rather

different, they are clustered into different nests (inside so-called nested production functions).

Essentially, the structure is as follows:

Non-energy intermediate inputs (as well as feed stocks) cannot be substituted by

other input factors (Leontief-type technology, elasticity of substitution is zero)

Aggregate energy (coal, gas, petroleum products, electricity and heat) and value

added inputs (labour and capital) cannot be substituted by one another or by non-

53 CES is a standard form of production and demand functions in microeconomic theory. It includes all types of functions where the degree of substitution of different inputs remains constant. Common types of CES functions are Cobb-Douglas (elasticity of substitution equals one) and Leontief (elasticity of substitution equals zero). The general form for a CES production function with two

factors (L and K) is Q=F(∝ 𝐾𝑟 + 1−∝ 𝐿𝑟)1

𝑟 , where Q denotes output, F factor productivity and ∝ and

r are exogenous parameters. The constant elasticity of substitution is given by 𝑠 =1

1−𝑟.


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energy intermediate inputs (Leontief-type technology, elasticity of substitution is

zero)

Energy inputs (coal, gas, oil products, electricity and heat) can – to some degree –

be substituted with one another (elasticity of substitution above zero). However,

possibilities for substitution differ by activity.

Production in agriculture and mining (coal, gas and oil) also requires the use of

natural resources (i.e. arable land and energy resources, respectively). These are

modelled as non-tradable input factors with exogenous supply.

The typical structure of production is manufacturing is shown in the figure below.

Figure 11: Schematic representation of a multi-level CES production function

Source: DIW ECON

Sector X output

Products of Sector 1 Products of Sector NValue added (primary factors)

. . .

Domestic DomesticImported ImportedLabour Capital

Domestically sold Exported

Non-energy goods Energy & value-added mix

Energy inputs

Energy

good1

Energy

good K

. . .


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3.2.3 Power sector

In order to allow formulation of different scenarios for the development of the power sector

until 2050, the supply of electricity is simulated by a separate model – the electricity supply

model. The model builds on a detailed representation of different generation technologies

(i.e. coal- and gas-fired thermal power plants, hydropower plants, nuclear power plants as

well as renewables), which include information on the currently installed capacity, availability

factors, the corresponding capital and running costs for the existing capacities as well as

investment costs for capacity extension. The key source of the technology-specific

assumption is the MACCTool report by Thomson Reuters (see Appendix B-1). The projected

costs change over time, reflecting changes in fuel prices as well as in technologies per se.

The objective of the electricity supply model is to compute the dispatch of generation

capacity that satisfies the projected demand for electricity in Ukraine (represented by a load

curve for every future year), subject to available generation capacities. The model however

does not consider the regional distribution and the issue of availability of transmission

capacity.

The dispatch is not based on the minimum-cost approach, but is rather based on a set of

rules that depict the actual situation in the electricity sectors of Ukraine. The generation

technologies are separated into “must-run” and “flexible”. Must-run generation technologies

run during the whole year with average available capacity. Must-run technologies include gas

and coal CHPs, nuclear power plants as well as solar and wind power plants. Flexible

technologies include coal TPPs, hydro power plants, as well as pumped storage and

biomass capacities. These technologies are used to cover the peak demand.

Eventually, the electricity-sector model yields estimates of costs of electricity generation for

the given future level of electricity demand. This includes the costs of investing into new

generating capacities (conventional and renewable) if that is required to match the demand.

These results are embedded into the CGE model by passing the cost structure to the CGE

model and reading electricity demand from the CGE model (the iteration between models is

not automatic).

In order to allow for the perfect match between the electricity cost structure in the CGE model

and in the electricity supply model, the production technology for electricity in the CGE model

is different in every year. This is achieved by setting all substitution elasticities in the


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production function to 0 and scaling the share parameters according to the results of the

electricity supply model. Right angles in the substitution nests in the Figure 12 below

symbolize that the substitution elasticities are set to zero. Heat is treated as a by-product of

coal- and gas-fired CHPs. All costs of this joint production are assumed to be covered by the

electricity costs.

Figure 12: Schematic representation of the CES production function electricity sector

Source: DIW ECON

3.2.4 Heat supply sector

The activity of the heat supply sector describes all heat provision that is not covered by the

CHPs. Heat supply in Ukraine is currently almost entirely gas-based. The installed capacity

of boiler houses exceeds 120 thousand GCal / hour. The biggest part of this capacity is

provided by large boiler houses which can produce more than 100 GCal per hour, but there

are also many smaller installations.

One key problem related to the heat supply sector is a high share of worn-out equipment and

holey transmission lines. It means that there is a need to make massive investments in the

sector in the nearest future. Another problem is posed by the high gas prices, and the need

(stimulated by the conditions of the IMF financial support program) to reduce the gas and

heat subsidies to the households. The latter factor makes a shift in the heat sector from the

Output

Products of Sector 1 Products of Sector N

Value added (primary factors)

. . . Labour Capital

Domestically sold Exported

Energy products

Non-energy products Energy and factors

Products of Sector 1 Products of Sector N. . .

1

Electricity Heat


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gas-fired capacity to the coal-fired capacity a very probable future scenario (foreseen e.g. in

the 2014-2015 State modernization program for the heat sector).

These two problems mean that the current composition of inputs used in the heat supply

sector (in other words, the production technology) is likely to change dramatically in the

nearest future. For this reason, our modelling approach for this sector is similar to the

approach we take for the power sector. We set up a simple model of the heat sector. We

assume that the currently used gas-fired capacity will be refurbished over the next years,

while any new capacity that has to be built to cover the increased heat demand will be coal-

fired.

Given the initial heat demand forecast for the period until 2050, the heat model provides the

required input composition, including capital, labour, fuel and other costs. Similar to the

approach in the power sector, we let the production technology for heat in the CGE model be

different across years and make it correspond to the results of the heat model. This is

achieved by setting all substitution elasticities in the production function to 0 and scaling the

share parameters according to the results of the heat supply model.

3.2.5 Taxes and subsidies

The coverage of taxes and subsidies on products and production factors in the model is not

very detailed. For the direct factor taxes, sector-specific tax rates are calibrated from the

input-output data and the same rates are applied to both, labour and capital income. For the

indirect taxes, product-specific rates are applied to the total domestic supply. These rates are

also calibrated based on the input-output table.

Because of their huge importance for the public budget, special attention is paid in the model

to the gas and heat subsidies. The size of these subsidies in the benchmark year 2011 is

roughly 7% of GDP. The public budget subsidises the use of gas by households and by the

electricity and heat sectors. The result of these subsidies is that the households pay a price

for gas that is way below (6-7 times lower) the price paid by the industry. The price that the

public heat providers pay for gas is also twice lower than the market price. The IMF financial

support program requires that these subsidies are gradually abolished.

In the model, we allow the simulation of scenarios with higher gas and heat prices for the

users that now pay the subsidized price. To this end, we make the subsidy rates depend on


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the exogenously set tariff rates that the households and the public heat providers pay. These

tariff rates can be adjusted (e.g. gradually increased, as foreseen by the IMF program) and

the required subsidy rates will adjust accordingly. Also the public budget in the model will

react to the reduction of subsidies – the public deficit will be reduced.

3.2.6 GHG emissions

In addition to production of physical output, the CGE model also covers the three relevant

types of GHG emissions: fuel combustion, fugitive emissions (e.g. in mining activities), as

well as emissions from industrial processes (e.g. in the chemical industry or in waste

management):

GHG emissions from fuel combustion are directly related to the amount of energy

inputs used by different production activities as well as by households (in TJ). The

fuel types are coal, gas, and refined oil products.

As depicted in Figure 11, substitution between different types of fuel is possible.

Significant movements in relative prices of energy inputs may thus induce producers

to choose a different type of fuel for their production capacities. In the same manner,

the households may also change their demand pattern (for example, the choice of

fuel used for decentralized heating, or car use). Such decisions can have a

significant impact on the GHG emissions (consider, e.g., substitution of coal through

gas).

Fugitive GHG emissions and GHG emissions from the industrial processes are

directly related to the production levels (real output) of the respective activities. The

emissions, the source of which is not fully specified in the UNFCCC data, are

assigned to the public sector and are kept constant over time in the model.

3.2.7 Rest of the world

Ukraine is modelled as a small open economy, which does not have an impact on the world

prices, but can export or import any required amount of any commodity. The world prices (in

particular, the prices for the main export goods, such as raw oil, metals, etc) are thus taken

as given.

Imports of every type of goods are modelled as imperfect substitutes to the domestically

produced variants of the same type of goods (this is the so-called Armington assumption). It


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means that the market price on the domestic market for any product is a composite of the

price of domestic producers and the import price (combined using a CES function). Similarly,

the exports are modelled as being slightly different from the variants of the product sold on

the domestic market. The gross output of any production sector is transformed into

domestically sold varieties and exported varieties using a CET transformation function.

The model also reports payments and receipts of residents in Ukraine in their transactions

with the rest of the world (for example, due to investments abroad).

3.2.8 Behavioural setup and equilibrium

The bottom-line of the behavioural setup is that all institutions adjust their behaviour in

response to prices. On all markets, prices are determined by market clearing. This means

that prices on each market adjust until the quantity of supplied factors, goods or services

equals the corresponding level of demand. The different institutions in the model take these

prices as given and behave as follows:

Activities demand different goods and services (so-called intermediate demand) as well

as labour and capital for producing their output (as determined by their respective

production function). Profits are determined by revenues from selling final output less

costs of all necessary inputs. Activities are assumed to choose their demand for different

inputs in order to maximise their profits.

Private households derive their wellbeing (so-called “utility”) from final consumption

(i.e., the more they consume, the better off they are). They spend a given fraction of their

income for savings as well as to maximise their utility subject to the available income

(which is mainly given by earnings from labour and capital endowments);

The government keeps the real value of public service provision constant. Therefore,

government income has to adjust depending on changes in commodity and factor prices.

The equilibrium of the model is a set of prices and quantities (i.e. levels of demand) such

that:

All factor and commodity markets clear;

Private households realise maximum utility given their specific household income;

Activities realise maximum profits given their specific technologies; and


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Expenditures of all institutions do not exceed the income of the respective institution

(so-called hard budget constraint).

3.2.9 Dynamic elements

As mentioned above, the model is dynamic, that is, it produces equilibrium solutions (i.e.

values of input and output variables) for each year in the simulation period 2011-2050. The

equilibria for different years are linked by the changes of labour force and capital stock as

well as by changes of specific exogenous parameters that determine world prices, factor

productivity or energy efficiency. In line with standard theory of economic growth, this setting

implies that economic growth is driven by the following factors:

Population growth/decline: The available labour force in each year changes in line with

the overall level of population growth (which is negative in Ukraine). This is appropriate

as long as labour market rigidities such as unemployment or demographic changes are

not explicitly modelled.

Capital accumulation: By assumption, a constant share of existing capital – the Gross

Fixed Capital Stock – depreciates every year while new capital is created from private

and public investment. The sources of investment are foreign and domestic savings.

Productivity growth. Due to exogenous technological progress, the productivity of

labour and capital can grow over time as well as at different levels for specific activities.

While the rates of population growth and depreciation are simply exogenous parameters, the

modelling of investment decisions is more complex. We model investments – or gross fixed

capital formation – as being responsive to changes in incentives. In particular, investment

demand in a given sector increases if the return from a given amount of capital exceeds the

costs of building up that amount of capital through investments (capital formation).54 In the

opposite case, once the ratio decreases, demand for investments declines as well. In

addition, the model also allows for incremental increases of investments under specific

policies such as green technology rollout.

54 This ratio of return to capital over costs of capital formation – or more generally, market value over replacement value of capital – is known as Tobin's q.


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3.2.10 Model closure

The reaction of households and firms to changes of economic conditions in the CGE model

is determined by specific behavioural assumptions. In particular, households maximize utility

subject to their available income and firms maximize profits under given technologies

constraints. In addition, the complete model specification also requires formulating

behavioural rules for the government and the exchange of goods, services and financial

assets between Ukraine and the rest of the world. These rules are typically referred to as

model closure. In terms of modelling, this requires specifying which macroeconomic

indicators will be fixed at target levels and which are allowed to freely adjust.

Generally, the economy-wide (general equilibrium) nature of the model requires that all

monetary flows in the economy are taken into account, all markets clear, and all

expenditures match with corresponding income sources. This implies that certain

macroeconomic identities in the model must hold at all times. On the aggregate level, it

requires that the sum of domestic investment and investments abroad must equal the sum of

public and private savings. In turn, this implies that at least one of these components (public

and private savings, domestic investment, and the current account balance) must be free to

adjust to changing economic developments.

In the CGE model for Ukraine, we need to reflect the current macroeconomic situation, in

which the public budget is characterized by a large deficit, and the external trade balance is

negative. As far as the state budget is concerned, the major source of the deficit is given by

the huge energy (gas and heat) subsidies. In the future, these subsidies need to be reduced,

because this situation is unsustainable. The tariffs for gas and heat will have to gradually

approach the corresponding market prices and the subsidies will be reduced.

A suitable model closure in this situation encompasses an endogenous budget balance that

reacts to the changes in the subsidy rates. Accordingly, the real value of government

expenditure will also be determined by the model. The private savings depend directly on

household income and thus, also adjust. Hence, public and private savings are

endogenously given by the model solution.

As far as the links with the global economy are concerned, the model is based on the small

open economy assumption. This implies that all goods and services as well as financial

assets can be bought from and sold to world markets in unlimited number at given (fixed)


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prices. However, the market clearing condition for foreign currency requires that the balance

of payments holds. Trade deficit must be matched by the inflow of foreign capital (purchase

of domestic assets by foreigners). This latter amount (the current account deficit) is fixed in

the model.

3.2.11 Database

The model builds on an extensive database. Main data sources are:

National Accounts of Ukraine for 2011. (Source: State Statistic Service of Ukraine,

2013, Kyiv.)

Ukrainian Input-Output Table at Consumer Prices for 2011. (Source: State Statistic

Service of Ukraine, 2013, Kyiv.)

Energy Balance of Ukraine for 2011. (Source: State Statistic Service of Ukraine,

2013, Kyiv)

GHG emissions inventory of Ukraine for 2011. (Source: National GHG Inventory

report of Ukraine for 1990-2012. Submitted to the Secretariat of the UNFCCC on

April 12, 2014. Retrieved from http://unfccc.int)

Relevant publications by the IMF, the State Statistic Service of Ukraine (the official

statistical institute), and others, including:

for GDP outlook till 2019 – IMF. (2014). World Economic Outlook Database. May

2014.

for producers„ price index – State Statistic Service of Ukraine. (Different years.)

Producer Price Indices. Retrieved from http://www.ukrstat.gov.ua/

The sources listed above are not always entirely consistent. Therefore, we had to make a

choice of the source at the instances when a conflict was identified. In particular, we used the

following rules:

The total macroeconomic indicators, such as GDP, value added, tax revenue, exports,

imports, total output, final consumption, etc., are taken directly from the national

accounts (NA).

The input-output table (IOT) is used to split the totals in the NA into different activities. In

this way the split by activity/product is carried out for the following data pieces:

Intermediate product use


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Value added

Total output

Taxes on products and activities

Final consumption (households, government, investment)

Imports and exports

The model database is thus linked to the official statistics of Ukraine and the key economic

indicators coincide. The sectoral figures for value-added in 2011 are reproduced by the

model with the same high precision (Figure 13).

Figure 13: Gross value added by key sectors in Ukraine (2011)

Source: UkrStat.

An important output of the model is the amount of GHG emissions by activity. We included

the information on the emissions from fuel combustion and from industrial processes

(including agriculture and waste management) as reported in the GHG emissions inventory

of Ukraine for 2011. For the economic activities, for which no information from UNFCCC is

available, estimations were made based on the additional information from the Energy

0

100,000

200,000

300,000

400,000

500,000

600,000

Agriculture Mining Manufacturing Utilities Transport Services

mln

UA

H


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Balance of Ukraine. The resulting database which lists all 23 production activities is reported

in Table 7.

The model described in this section will be used to assess the impact of specific policy

measures and technologies aimed at stimulating low carbon growth in Ukraine. It will also

form the basis for the development of BAU scenarios until 2020 and 2050 as presented

below.


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Table 7: Energy use and GHG emissions by activity

Agriculture

Coal extraction

Extraction of crude oil

Extraction of natural

gas

Other mining

Food and beverages

Textiles and

furniture

Wood, paper,

pulp, and print

Coke oven products

Oil refining

Energy consumption (2011, in TJ)

Liquid Fuels 57190 110 31 27 902 1412 9 56 529 12791

Solid Fuels 1175 84385

1183 2380 26 585 10908 3

Gaseous Fuels 22963 2530 4372 8583 25890 55693 405 7390

7248

Biomass 1907 884 542 1065 13 6064 13 2495 234 Other Fuels 38 92 24 46 2 1949 0 1 16 2312

GHG Emissions (CO2e in Gg) A. Fuel Combustion 5594 4823 247 483 1614 3570 26 472 643 1444

Liquid Fuels 4186 8 2 2 67 106 1 4 39 875

Solid Fuels 117 4667

110 222 2 54 603 0

Gaseous Fuels 1274 140 242 475 1436 3090 22 410

402

Biomass * 14 2 1 2 0 11 0 5 0 Other Fuels 3 7 2 3 0 141 0 0 1 167

B. Fugitive Emissions from Fuels

19596 4 3

460 397

C. Emissions from Industrial Processes 36299

TOTAL Emissions (CO2e in Gg) 41893 24419 251 486 1614 3570 26 472 1104 1841

* CO2 emissions from combustion of biomass fuels are not included in the total CO2 emissions from fuel combustion (UNFCCC Website).


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Table 7 (continued): Energy use and GHG emissions by activity

Chemical

s Minerals

Metal produc-

tion

Machinery and equip-

ment

Other manufactu-

ring

Construc-tion

Public electricity

Natural gas

production and

distribu-tion

Heat and hot water

supply

Water and waste

manage-ment


Liquid Fuels 177 190 3515 182 518 797 1768 74 1130 40

Solid Fuels 940 30693 330042 233 13422 258 822536 823 207

Gaseous Fuels 135364 47018 209440 16315 2381 184151 7684 281916 281

Biomass 439 3606 5 150 155 3528 3

Other Fuels 1661 0 4 3 0 2 1509 19 32 0

GHG Emissions (CO2e in

Gg) A. Fuel Combustion 7716 5494 44071 941 1291 216 88194 432 15785 38

Liquid Fuels 12 14 269 13 38 59 136 5 87 3

Solid Fuels 73 2864 32181 22 1252 24 77696 78 19

Gaseous Fuels 7510 2609 11620 905 132 10201 426 15617 16

Biomass * 1 7 0 0 0 7 0

Other Fuels 120 0 0 0 0 0 154 1 3 0


28608

C. Emissions from Industrial Processes

10726 10983 26527 11234

TOTAL Emissions (CO2e in Gg)

18442 16476 70598 941 1291 216 88194 29041 15785 11272



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Table 7 (continued): Energy use and GHG emissions by activity

Transport Gas

pipeline transport

Other services

Total industries

Private Households

Non-specified

by sectors Total


Liquid Fuels 421498

2209 505155 14765 2648 522568

Solid Fuels

16690 1316490 27573 3167 1347229

Gaseous Fuels

100804 56044 1176472 598886 12150 1787507

Biomass

4088 25190 12947 329 38466

Other Fuels

544 8254

8254

GHG Emissions (CO2e in Gg) A. Fuel Combustion 30997 5675 4999 224765 36940 1176 262881

Liquid Fuels 30997

161 37084 910 199 38193

Solid Fuels

1658 121644 2705 299 124648

Gaseous Fuels

5675 3109 65312 33227 674 99213

Biomass *

31 81 98 2 181

Other Fuels

39 644

1 645


3

49072

49072

C. Emissions from Industrial Processes

726 96495

96495

TOTAL Emissions (CO2e in Gg) 30997 5678 5725 370332 36940 1176 408448


Source: UNFCCC, Energy Balance of Ukraine, DIW ECON calculations.


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3.3 Scenario analyses

The model described in Section 3.2 will be used to simulate the impact of specific policy

measures and/or technology changes aiming at stimulating low-carbon growth in Ukraine. To

this end, the impact of policies and technology change has to be assessed against a robust

benchmark which captures the hypothetical development of the economy in the absence of

such changes (henceforth referred to as Business as Usual, BAU). In this section, we

discuss the key assumptions underlying the development path for Ukraine‟s economy under

the BAU scenario (section 3.3.1), present the results of the BAU scenario (section 3.3.2) and

elaborate on the different channels through which technological change and low-carbon

growth policies can be implemented (section 0).

3.3.1 The Business-as-Usual (BAU) Scenario

The business-as-usual (BAU) scenario describes a hypothetical development path of the

economy which the model reproduces under the assumption that there will be no substantial

policy interventions aiming at green growth facilitation. It is not to be understood as a

forecast (i.e. most realistic development) of the economy but rather as a benchmark for

comparing the results of different policy scenarios and a motivation for policy action.

In the CGE model, all key economic variables, such as GDP, output and value added by

activity etc, are endogenous. That is, they are determined inside the model and cannot be

fixed at exogenously given values. Instead, replicating a given development path – e.g. the

forecasts of the IMF until 2019 – requires modifying the parameters of the model that

influence economic development, such as productivity growth (by activity), tax and subsidy

rates, or world prices.

3.3.1.1 Growth assumptions

As mentioned above, there are three main sources of growth: population growth

(exogenous), capital accumulation (partly exogenous) and productivity growth (exogenous).

A particular challenge is the trend in population, which has been decreasing since the mid-

1990s. The National Institute of Demography forecasts a continuous population decline at an


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average rate of 0.4% per year. In fact, this implies that changes in population will have a

negative impact of economic growth. In other words, economic growth needs to be

generated from other sources, in particular capital accumulation (investments) and

productivity growth. Hence, the development of the overall economy as well as of individual

activities will be mainly reflected in activity-specific changes of labour and capital productivity.

For the BAU scenario, these parameter values will have to be adjusted so as to meet

historical developments.

For the first years of the simulation period (2011 - 2019), some target values for Ukraine are

determined by the current forecast of the IMF (IMF Country Report No. 14/106, May 2014).

This forecast assumes that Ukraine will manage to implement a package of reforms that will

stabilize its macroeconomic situation. The model parameters for the first years are adjusted

so as to replicate the IMF forecast.

Table 8: GDP growth 2012-2019

Year GDP growth, %

2012 0.3

2013 0.0

2014 -5.0

2015 2.0

2016 4.0

2017 4.0

2018 4.5

2019 4.5

Source: IMF Country Report No. 14/106, May 2014

For later years, there are no reliable projections on annual GDP growth available.

Consequently, productivity levels cannot be adjusted to meet a given development path.

Instead, we use conservative assumptions on further productivity growth, based on the

historical data in the growth period 2000-2008.

Altogether, we assume the following developments of labour and capital productivity under

the BAU scenario:

Agriculture:

Average productivity growth rate 2.2% in 2012-2019


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Manufacturing industries:



Mining:



Transport



Service sector



3.3.1.2 GHG emission intensity and energy efficiency

This section contains the calculations representing the deliverable agreed upon in the

contract extension: differentiated development paths of energy efficiency for several selected

energy intensive industries of the agricultural, energy and manufacturing sectors of the

Ukrainian economy.

Despite a very steep decline of the emissions intensity over the last 15 years, Ukraine

remains one of the most emissions and energy intensive countries of the world; its emissions

intensity of GDP is still more than three times higher than average over OECD Europe (see

Figure 14). Most of these emissions stem from fuel combustion. This indicates a significant

potential for further reduction of emissions and energy intensity of GDP.


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Figure 14: GHG emission intensity in Ukraine and OECD Europe (1990-2010)

Source: OECD55

and PWT 7.156

; own calculations

The intentions to decrease energy intensity of GDP have been repeatedly declared by

different development programs in Ukraine. The issue is recognised as a strategically

important and of the highest priority.57

Energy intensity is measured by relating the amount of energy inputs in a given activity to the

respective production volume. In the CGE model of Ukraine, this ratio can be controlled by

specific parameters.58 To reflect assumed increases in energy efficiency, these parameter

values must be adjusted over time. In the BAU scenario, we base our assumption about the

development of the energy efficiency of different production sectors on the historical trends

extracted from the statistics provided by the national Agency for Statistics as well as by the

IEA.

55 Emission data were retrieved from http://www.oecd.org/statistics/; OECD refers to the UNFCCC

as the primary source of the data. 56

Heston, A., Summers, R., and Aten, B. (July 2012). Penn World Table Version 7.1. Center for International Comparisons of Production, Income and Prices at the University of Pennsylvania.

57 According to the recently revised “Energy Strategy of Ukraine”, Ukraine should reduce energy intensity of GDP by almost 60% by 2030. According to “The State Programme for Stirring-up the Economy” (Decree of the Cabinet of Ministers, No.187 from February 27, 2013), the energy intensity of GDP in Ukraine has to decrease by 1.5-3% per year by 2014. The Government announced its intention “to enhance the economic incentives for energy saving”. The same Programme envisages revision of subsidies to coal mining enterprises and optimization of coal mining sector.

58 More specifically, these parameters define the required volumes of energy input per unit of output for each activity.

0.0

0.5

1.0

1.5

2.0

2.5

3.01990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010tCO

2e

/GD

P in

20

05

co

nsta

nt

pri

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s a

nd

P

PP

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OECD Europe Ukraine


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Figure 15 shows the development of energy intensity (defined as primary energy input

relative to real output) in the aggregated sectors between 2002 and 2012. We interpret these

data as showing a downward trend in primary energy intensity in the recent years and we

use an average rate of change to extrapolate this trend into the future. Thus, we assume for

the BAU scenario that energy efficiency of sectoral output increases:

by 4.0% p.a. in agriculture,

by 4.0% p.a. in mining,

by 3.0% p.a. in manufacturing,

by 6.0% p.a. in services.

Figure 15: Primary energy intensity of sectoral output in BAU (TJ per mln UAH in constant prices of 2001)

(a) mining, manufacturing, transport

Source: DIW ECON calculations using data from IEA and UkrStat.

0

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(b) agriculture and services


In addition to primary energy efficiency, an important issue is also the efficient use of

electricity and heat. For producing an estimate of the corresponding future trend we used the

historical electricity demand data provided by UkrStat. Figure 16 illustrates these data for the

years characterized by economic growth in Ukraine. Again, these downward trends in

electricity intensity are extrapolated into the future. In the BAU scenario, we thus assume

electricity efficiency in manufacturing to improve at an average rate of 2% p.a, in services at

1% p.a. and in agriculture at 4% p.a. We assume also that these rates are not preserved

forever, but that there is smooth reduction of the rate of change over time (at 3% p.a.).

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2002 2007 2012 2017 2022 2027 2032 2037 2042 2047

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Figure 16: Electricity intensity of sectoral output in BAU (GWh per mln UAH in constant prices of 2001)

(a) manufacturing and mining

(b) agriculture


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(c) services


3.3.1.3 Power sector development

For the electricity sector, the assumptions that determine future developments in the CGE

model are adjusted such that they are consistent with the findings of the sector-specific

model of the power sector. In particular, the production function in the CGE model is

calibrated such that the costs of producing electricity coincide with the findings of the power

sector model.

The BAU scenario of the power model reflects an increase in the electricity demand as well

as an increase in the renewables capacity. In particular, the total electricity demand

increases from 199 TWh in 2013 to 314 TWh in 2030 and 468 TWh in 2050. This increase in

demand (together with the need to refurbish existing capacities) requires investments in

additional generation capacity (Figure 17), estimated at a total of 2400 bln UAH (at constant

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2002 2007 2012 2017 2022 2027 2032 2037 2042 2047

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prices of 2011). This investment amount is huge, two times higher than the GDP level of

2011. However, it is required to match the electricity need of a growing Ukrainian economy.

Figure 17: Installed generation capacity in the BAU scenario

Source: DIW ECON

According to the BAU scenario, in 2030, 48% of the electricity will be produced by nuclear

power plants, while the remaining parts will be coal (30%), gas (8%), hydropower (9%), and

other sources, such as solar, wind and biomass (5%). In 2050, the share of solar and wind

power plants will increase to 13%, and the shares of conventional sources will slightly

decrease (Figure 18).

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Figure 18: Fuel mix of produced electricity (in percent of total generation, BAU scenario)

Source: DIW ECON

3.3.1.4 Heat sector development

As mentioned in the model description, the evolution of the heat sector is also modelled

using results from an external model. The purpose of the heat sector model is to simulate

different scenarios of capacity development and calculate corresponding investment costs

and the resulting structure of the production inputs (fuel, capital, labour, other inputs).

In the BAU scenario, we assume that new capacity is 50% coal-fired and 50% gas-fired. We

further assume that the existing gas-fired capacity that is actively used can be refurbished.

Given the low utilization rates of the worn-out gas-fired capacity, the currently installed

capacity of 120000 GCal/hour will not be sufficient to satisfy heat demand in 2050. Our

estimation is that the capacity of 30000 GCal/hour that is used 40% of the total time in the

year is enough to satisfy the current demand (105000 TCal per year). Using the IEA data on

energy use, we can infer that the major part of this available capacity (27500 GCal/hour) is

gas-fired. This is the capacity that will be refurbished in the BAU scenario.

The assumed amount of additional coal-fired capacity that is required in the BAU scenario

stems from the estimate of demand increase that is roughly the same as the increase in

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electricity use: 200% increase between 2011 and 2050. This additional demand can be

satisfied by installing a coal-fired capacity of 65 TCal per hour.

The corresponding investment costs for refurbishment and new capital amounts to 4000 mln

UAH per year between 2015 and 2050, or a total of about 150 bln UAH.

Figure 19: Fuel mix of produced heat (in percent of total generation, BAU scenario)

Source: DIW ECON

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3.3.1.5 Gas import price

The price of imported gas is an important driver of economic development in Ukraine, as

suggested by the recent history. For the BAU scenario, we follow the assumptions of the IMF

country report for Ukraine for the period until 2019. For later years, we take the IEA long-term

trend for the imported gas in Europe as a basis.

Figure 20: Assumed development of the import price (in real terms) for natural gas (USD per thousand cubic meters)

Source: DIW ECON based on IEA (2013) and IMF Country Report for Ukraine (2014)

3.3.1.6 IMF support program

The conditions of the IMF support program for Ukraine that was agreed upon in May 2014

are very detailed and are likely to be implemented in the full extent. They relate the provision

of funds to the obligation of the Ukrainian government to conduct a painful but necessary

reform in the energy sector. The majority of existing subsidies on energy must be abolished.

As a result, the deficit of public budget must be brought back to a sustainable level.

We assume that the IMF program is implemented as agreed. According to the published

degrees of the Ukrainian government, the regulated gas tariffs for the households will rise by

56% in 2014, by 40% in 2015, and by further 20% in the years 2016 and 2017. For the heat

generating companies, the tariffs for gas will rise by 40% in 2015, and by further 20% in the

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2011 2016 2021 2026 2031 2036 2041 2046

Ukraine imports (IEA and IMF), $ per tcm

Europe imports (IEA), $ per tcm


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years 2016 and 2017. After that, the tariffs will follow the pace of the import price described

above.

3.3.2 Results of the Business-as-Usual scenario

The BAU scenario corresponds to a rather restrained picture of the economic development in

Ukraine until 2050. Given the poor economic performance of Ukraine in the recent years, the

resulting long-term rate of growth of 4.5% in the period 2015-2050 is not over-optimistic. The

model‟s staring year is 2011, that is why we have to reproduce the major economic slump in

2014, which is currently estimated to cost 5% of GDP. Figure 21 illustrates this dynamics in

the GDP growth.

Figure 21: Real GDP growth rates in BAU scenario

Source: DIW ECON (model results)

On the sectoral level, the developments are mainly following our assumptions about the rates

of total factor productivity growth (subsection 3.3.1.1). Figure 22 and Figure 23 show that the

service sector and the agricultural sector will be the main contributors to economic growth

over the next 40 years and will further grow in importance.

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Figure 22: Growth of sectoral gross value added in the BAU scenario


Figure 23: Structure of gross value added in the BAU scenario


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Structural changes in the economy, as well as our assumptions with respect to the energy

efficiency improvements and the developments in the power and heat sector lead to

substantial changes in GHG emission intensity of the economy, which falls at an average rate

of 1.5% p.a. in the period 2011-2050.

Figure 24: GHG emissions intensity of GDP in the BAU scenario (kt CO2eq per bln UAH in prices of 2011)


0

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The total amount of GHG emissions in the BAU scenario is however rising due to the growth

of the economy (Figure 25).

Figure 25: GHG emissions in the BAU scenario (kt CO2eq)


0

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3.3.3 The Energy-Efficient-Investments (EEI) scenario

The objective of the EEI scenario is to simulate the impact of energy-efficient technologies as

well as of the corresponding investment expenditures. In this section, we elaborate on how

these were modelled in the CGE model for Ukraine and present the corresponding results.

3.3.3.1 Impact of energy-efficient technologies

As explained in section 3.2.2, production technologies are modelled as specific production

functions that determine the amount of different inputs – such as labour, capital, energy etc.

– needed to produce a given volume of output. Changes in technology imply changes in the

underlying parameter values of these production functions. For example, a shift to energy

efficient technologies in a certain activity can be modelled by reducing the parameter values

for required energy input per unit of output in this activity. Obviously, the critical issue is to

determine by how much these parameters are to be reduced. This is discussed below in

section 3.3.3.3.

3.3.3.2 Investments in energy-efficient technologies

In addition to the impact on production, a shift to energy-efficient technologies can require

additional capital expenditures (i.e. additional investments). In the CGE model, production

technologies are part of the national capital stock – the so-called Gross Fixed Capital. As

explained in section 3.2.9, investments in gross fixed capital are modelled as being

responsive to changes in incentives, which are determined by the return to capital relative to

the costs of capital formation. In this way, the model yields optimal investment levels at given

levels of product and factor prices. To the extent that energy-efficient technologies are the

most-profitable investment option – mainly, due to cost savings – the shift to such

technologies is part of the regular gross fixed capital formation.59 However, the focus of the

different components of the energy-efficient scenario is on assessing the impact of additional

investments in energy-efficient technologies that accrue on top of what is economically

optimal. Shifting to such technologies implies additional, so-called incremental investments.

This is modelled by exogenously adding the respective volumes of incremental investments

to the volume of gross fixed capital formation as determined by the model. To the extent that

these additional investment volumes have an impact on prices (i.e. the return to installed

59 In fact, this is what happens in the BAU scenario where energy efficiency increases as described in section 3.3.1.2.


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capital and the costs of new capital formation), this also captures crowding out effects since

the level of gross fixed capital formation is responsive to changes in relative prices.

3.3.3.3 Efficient energy use and the costs of incremental investments

Technically, modelling the impact of energy-efficient technologies and the corresponding,

incremental investments as described before is straightforward. Of crucial importance,

however, is the specification of parameter changes which should be based on empirical

assessments of corresponding energy efficiency potentials and incremental investment

volumes.

In the CGE model for Ukraine, energy efficiency potentials and incremental investments are

mainly based on the results provided by Thomson Reuters (2013) (in the framework of this

project) on CO2 mitigation potentials and abatement costs in Ukraine under alternative

scenario assumptions (a baseline scenario and a low-carbon scenario). For some missing

sectors, we made use of similar calculations provided earlier by NERA (2012). The potential

abatement and the corresponding marginal abatement costs for each model sector are

presented in Table 9. The detailed list of all measures for each sector is included in Appendix

B-2.

In addition to this information, we also use the results of our own efficiency analyses for the

metal industry, the non-metallic mineral products industry (i.e. production of clinker, lime,

glass and soda ash) and the chemical industry in Ukraine as presented in Chapter 1.

These data are used to assess energy use reduction potential for each production activity in

the economy. Furthermore, the reported abatement costs can be used to estimate the

volume of incremental investments (i.e. the additional capital expenditures). In the following

we explain the corresponding parametric assumptions for different sectors.

The energy efficiency improvements in the EEI scenario are calibrated for each sector such

as to match the abatement potential for combustion activities reported in Table 9. These

improvements come on top of the baseline energy intensity trends of the BAU scenario

(described above in Section 3.3.1.2).


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Table 9: GHG abatement volume and incremental investments in Ukraine by activity

Abatement measures by sector and type:

Emissions reduction in 2050 (compared to BAU,

in million tons CO2e)

Marginal abatement cost (€

per ton CO2e)

Source of cost data

Agriculture (process) 39.3 63 TR

Coal extraction (process) 5.7 36 TR

Oil refining (combustion) 0.1 61 NERA

Chemistry (combustion) 4.6 45 TR

Minerals production (combustion) 2.4 94 TR

Metallurgy (combustion) 33.7 31 TR

Heat use in buildings (combustion) 8.9 100 DIW econ

Heat and hot water supply (combustion) 12.6 325 TR

Waste management (process) 15.6 53 TR

Transport (combustion) 16.3 179 NERA

Source: DIW ECON based on Thomson Reuters (2013) and NERA (2012)

For manufacturing, the energy efficiency assumptions for two key energy-intensive industries

of metals and minerals production are specified individually. The rates of change there are

assumed to be slower than in the rest of manufacturing. Important efficiency improvements

are assumed for the supply side (local boilers and networks) as well as demand side

(insulation of residential and office buildings) of heating. Finally, fuel efficiency measures in

freight and public transport are included in the EEI scenario.

Specifically, we assume that the incremental investments in energy efficiency lead to a

decrease of primary energy intensity:

by 1.0% p.a. in metals production,

by 1.5% p.a. in minerals production,

by 3.0% p.a. in food industry, textiles industry, machinery and equipment, and other

manufacturing.

by 2% p.a. in heat supply

by 2% p.a. in heat demand by residential sector (households) and service sector

by 1.0% p.a. in public and freight transport

These developments are illustrated by the following figures.


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Figure 26: Primary energy intensity of sectoral output in manufacturing in the EEI scenario (TJ per mln UAH in constant prices of 2001)

Source: DIW ECON

Figure 27: Primary energy intensity of sectoral output in transport in the EEI scenario (TJ per mln UAH in constant prices of 2001)

Source: DIW ECON

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Figure 28: Primary energy intensity of sectoral output in heat supply in the EEI scenario (TJ per mln UAH in constant prices of 2001)

Source: DIW ECON

The corresponding investment volumes are calculated based on the achieved abatement

and the abatement costs as specified in Table 9. As the abatement volume increases with

time, we aggregate the required total investment by a net present value, which is specified in

Figure 29.

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Figure 29: Composition of the required energy efficiency investments (total net present value, in bln UAH of 2011)

Source: DIW ECON

3.3.4 Results of the Energy-Efficient-Investments (EEI) scenario

The EEI scenario has a clear positive impact on the macroeconomic indicators such as GDP

and household consumption (Figure 30). The predicted GDP in the year 2050 in the GREEN

scenario is 7.4% higher than in BAU. The impact on households‟ consumption is slightly

larger; it is 8.4% higher than in BAU. These improvements do not come at the cost of higher

environmental burden. CO2 emissions are projected to be 7.8% lower than under BAU.

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Figure 30: Dynamics of key indicators (EEI relative to BAU scenario in each year)

Source: DIW ECON

It is worthwhile to study these key impacts in more detail. Figure 31 and Figure 32

decompose the total GDP and emission effects into the effects of different packages of green

investments:

Energy-saving measures in industry;

Modernization of heating networks;

Increasing energy efficiency of buildings;

Increasing energy efficiency of transport.

To put the effect into the current perspective, the indicators are compared to the levels of

2011. On the one hand, the direction of predicted effects is rather intuitive. On the other

hand, the relative magnitude of the effects of different packages could only be quantified

using a comprehensive computational model, like our CGE model.

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Figure 31: Decomposition of the total GDP impact of the EEI scenario in 2050 (in % relative to the baseline level of 2011)

Source: DIW ECON

Figure 32: Decomposition of the total emissions impact of the EEI scenario in 2050 (in % relative to the baseline level of 2011)

Source: DIW ECON

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Looking at the effects of individual investment packages, we see that improvement of energy

efficiency in manufacturing has the most important effect on both, the economy and the GHG

emission level. Substantial effect is also produced by the measures in the heat supply sector,

where the investments are directed to reducing currently huge heat losses. However, due to

limited feedback effects from these investments, the macroeconomic impact is not as large

as for the measures in the manufacturing sector.

Figure 33 shows the total impact of the GREEN scenario on the gross value added in

different sectors.

Figure 33: Sectoral GVA impacts of the EEI scenario (difference in GVA between EEI and BAU in 2050 relative to the level of 2011, %)

Source: DIW ECON

The negative effect on mining is due to the reduce energy (mainly, coal) use by industry and

heat supply. The positive effects on manufacturing and construction are the largest and

correspond to the results in Figure 31.

Note that the improvement of energy efficiency is costly. It requires investments by firms in

the corresponding sectors that go beyond “normal” investment levels. Thus, these can only

be expected to be implemented if they lead to cost savings and additional profits in the

future. To assess the chances for such additional contributions to realize, the impact of the

proposed measures on different manufacturing industries must be further assessed.

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Figure 34: Profitability of economic sectors in the EEI scenario (net present value of incremental profits, as compared to BAU)

Source: DIW ECON

Figure 34 reports the value of discounted profit flows for aggregate sectors. The measures in

heating and transport are relatively most expensive and they lead to negative profits. It

means that the implementation of these measures will need additional incentives provided

the government. The increase of heating tariffs for the households (in accordance to the IMF

program requirement) is already included in our calculations. The additional incentives may

include on the one hand, public subsidies, but on the other hand also the use of market

mechanisms like CO2 taxes.

The measures in manufacturing seem to generate enough cost saving for the firms in the

sector. It is still worthwhile to look at this in a bit more detail.

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Figure 35: Profitability of key manufacturing sectors in the partial EEI scenario with only manufacturing measures (net present value of incremental profits, as compared to BAU)

Source: DIW ECON

Figure 35 reports the value of discounted profit flows for individual manufacturing sectors in a

partial scenario, where only the measures in manufacturing are simulated. In fact, the values

are positive for all sectors. Key investments are carried out in the metallurgy, chemicals and

minerals sectors. These are also the manufacturing sectors with the largest GHG emissions

in the benchmark year 2011.

Positive returns in the manufacturing sectors mean that these sectors can be expected to

invest in the energy-efficiency measures without that additional motivation will be necessary.

However, positive profits also suggest that these sectors could potentially contribute more to

energy efficiency through additional investments. Moreover, if parts of these profits in

manufacturing can be re-distributed towards utilities – the sector that accounts for the

strongest losses under the EEI scenario – this could yield a more balanced and thus,

preferable overall policy impact.

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4. Short-term, ad hoc expertise and consulting to

decision makers and key stakeholders for

current topics on the political agenda

4.1 Introduction

The ad hoc expertise was provided on the topic of the impact of Doha Amendment for

Ukraine. This analysis was carried out in October 2013 and therefore does not take

into account the recent developments, including IMF growth forecast as shown in

Table 8.

The international climate negotiations in Doha at the end of 2012 adopted an amendment to

the Kyoto Protocol regulating the second commitment period (CP2) from 2013 to 2020. In

particular, emission allowances at the national level will be capped based on average

emissions from 2008 to 2010. For Ukraine, this corresponds to emission allowances of about

3.1 billion tons of CO2 equivalents or 0.39 billion tons per year (on average). The actual

GHG emissions in Ukraine and available assigned amount units (AAUs) for CP2 based on

the Doha Amendment are depicted in Figure 36.


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Figure 36: GHG Emissions in Ukraine and available AAUs for CP2 based on Doha Amendment

Source: UNFCCC (2013), own calculations.

Policy makers in Ukraine worry that this cap on emissions will effectively limit the possibilities

for future growth of GDP. Thus, they currently consider not to ratify the Doha Amendment.

In July 2013, DIW ECON put forward arguments in favour of ratification of the Doha

Amendment emphasising that it would be beneficial for Ukraine not to opt out (DIW ECON,

2013). This section provides additional evidence that with some political efforts, the CP2

emission target for Ukraine is feasible and economically reasonable. Thus, we recommend to

Ukrainian policy makers to ratify the CP2 Doha amendment.

4.2 The challenge

The analysis of recent economic developments in Ukraine and of the latest GHG inventory

data shows that the emission cap as determined in the Doha Amendment does not impose a

barrier for future economic growth to Ukraine. On the contrary, it can be expected that even

under Status Quo developments – that is, in the absence of any further policy interventions –


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national GHG emissions will exceed only the allowed amount of emissions induced by the

CP2-cap. More precisely, given the Status Quo, we estimate that the Ukrainian GHG

emissions on average will exceed the CP2-cap by just 1.3% per year during the commitment

period 2013-2020. However, if Ukraine manages to fully utilise its estimated abatement

potential at the cost level of up to 40 Euros per ton as estimated by NERA, Ukrainian GHG

emissions will clearly remain on average by 6.3% per year below the CP2-cap. The

corresponding estimations are illustrated in Figure 37 below.

Figure 37: Available AAUs for CP2 (Doha Amendment) and estimated GHG Emissions in Ukraine

Source: UNFCCC (2013), own calculations

4.3 Analysis

The analysis of future GHG emissions rests on two key assumptions:

The expected yearly levels of GDP growth until 2020; and

The intensity of GHG emissions per unit of GDP until 2020.

4.3.1 Expected yearly levels of GDP growth until 2020

Expectations on future economic growth in Ukraine until 2020 have been strongly revised

during the past two years. For example, as of April 2011, the IMF expected average growth

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rates of at least 4% for Ukraine (IMF, 2011). Recently, however, this optimistic projection has

been substantially revised. In its most recent outlook as of October 2013, the IMF expects

growth rates of only 0.4% for 2013 and less than two percent until 2018 (IMF, 2013).

Assuming a rather high level of GDP growth of 3% for 2019 and 2020, the revised GDP

forecast implies that GDP grows from 2011 to 2020 by an annual average of only 1.7% (as

compared to 4.2% based on the previous forecast). The initial and revised outlooks are

presented in Figure 38.

Consequently, the significant drop in expected growth translates into lower expected

amounts of GHG emissions relative to the forecasts of previous years.

Figure 38: Expected yearly levels of GDP until 2020: Outlook of 2011 vs. outlook 2013.

(in constant 2007 national currency units)

Source: IMF, World Economic Outlook (WEO).

4.3.2 The intensity of GHG emissions per GPD until 2020

At present, Ukraine remains one of the most emission intensive countries of the world with

emissions per unit of GDP more than three times higher than average level in OECD Europe.

Hence, there is still a significant potential for further reductions of Ukraine‟s emission

intensity. Following the report by NERA (2012), the assumed development of GHG

emissions per unit of GDP would be as follows:

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Under Status Quo (SQ) developments, NERA expects the ratio of GHG emissions

per unit of GDP (the carbon intensity of GDP) to decrease by an average of -1.5%

per year between 2011 and 2020.

In its Enhanced Policies (EP) scenario, which considers utilisation of all abatement

potential at costs of less than 40 Euros per ton, NERA expects the ratio of GHG

emissions per GDP to decrease by an average of -2.9% per year over 2011-2020.

4.3.3 Expected national GHG emissions: new adjusted estimations

Applying the expected development of emission intensity to the revised GDP forecast of

October 2013, the expected total Ukrainian emissions are adjusted downwards, as already


As a result, under Status Quo developments (when no additional policy efforts are made and

current institutions continue as they are now) national GHG emissions will be only slightly

higher than AAUs imposed by the CP2: on average, national emissions exceed the CP2-cap

by 1.3% per year during 2013-2020. Nonetheless, with some political efforts (i.e.

implementation of current plans to reform the wholesale electricity market) it would be easy

to get below the CP2-cap. Moreover, if Ukraine manages to fully utilise its estimated

abatement potential at costs of up to 40 Euros per ton, national emissions will clearly remain

below the CP2-cap between 2013 and 2020 (by 6.3% on average per year).

4.3.4 Costs of reaching the 2012 Doha Amendment

According to the adjusted emissions expectations under Status Quo scenario, the cumulated

GHG emissions (when summed up over 2014-2020), will exceed the 2012 Doha Amendment

allowances by total amount of 38 MtCO2e. These emissions are represented by the shaded

area in Figure 4 (which actually depicts an enlarged view of the Figure 2).

In order to reduce the national emissions by this amount, some additional political efforts and

investments, which depart from the Status Quo toward the Enhanced Policies scenario,

would be needed.

Multiplying the obtained emissions amount by the maximal price at 40 Euro per ton CO2e

(NERA, 2012), results in 1.53 billion Euro of total investments, which will be needed over the

next seven years in order to keep to the newly imposed emission cap. This implies that with

additional investments into technological modernisation of on average 219 million Euro (or


Final Report

102

0.2% of GDP) per year until 2020 the requirements of the 2012 Doha Amendment could be

achieved by Ukraine.

Figure 39: Abatements needed to keep with requirements of the Doha Amendment

Source: DIW ECON

4.4 Conclusions

The presented analysis shows that the emission target imposed by 2012 Doha Amendment

for the second commitment period from 2013 to 2020 is achievable with some additional

political efforts and economically reasonable for Ukraine. Requiring yearly investments of

0.2% of GDP, the new target is achievable even under the current limitations in financial

markets or difficult situation in Ukraine‟s state budget. The target will not even trigger serious

structural changes within the economy. On the other side, the resulting improving overall

energy efficiency of the economy and reducing emission intensity of GDP would promote

growth in targeted sectors and increase competitiveness of domestic products and services.

Additional benefits, listed by DIW ECON (2013), emphasise the obtained conclusions and

strongly favour the ratification of the 2012 Doha Amendment by the Ukrainian side.

350

400

450

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

19

20

20

MtC

O2

e

Status Quo: DIW econ Availalbe AAUs under CP2


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103

5. Revised concept of a low carbon development

plan of Ukraine: From Stabilisation to

Sustainable Economic Growth

This section includes the executive summary of the Policy Paper No. 6 “From

Stabilisation to Sustainable Economic Growth”. The paper is included as Appendix C-

8 to this Final Report.

The IMF rescue programme to Ukraine‟s interim government has reinforced economic

stability in Ukraine. However, the fundamental structure of the Ukrainian economy remains

flawed. A strong reliance on industry exports coupled with a pronounced dependence on

energy imports jeopardizes Ukrainian long-term growth prospects and makes it vulnerable to

external shocks. Thus, structural policies ought to prioritise economic diversification to

achieve sustainable economic growth.

Abolishing energy subsidies and liberalising energy markets are the key conditions adherent

to the IMF loans. However, they are also expected to incur a wave of energy price shocks

and thus, economic losses. Hence, the economy risks being locked in a viscous cycle where

stabilization requires price shocks which in turn undermine economic growth and –

eventually – stabilisation. The focus of this paper is to demonstrate how this cycle can be

broken. In the medium-term, energy prices shocks can initiate technological adjustment,

yielding productivity gains and energy efficiency. Under favourable circumstances, incipient

losses are not only set off but also allow for economic growth. In Ukraine, however,

conditions for such a technological adjustment process towards lower energy intensity have

not been established yet. Rather, a technological frontier gap and pronounced capital

depreciation prevail. Protectionist measures by the government invalidated the market

pressure to invest in energy efficiency and capital stock modernization like of the

manufacturing industry. Accordingly, reversing the trends of capital depreciation and high

energy intensity in manufacturing, improving market structures in the energy sector and

ameliorating the economy-wide business environment can provide Ukraine with vast

potential for economic growth. This is the focus of this paper.

Above all, initiating capital stock modernisation as well as diversification requires

investments. In turn, kick-starting the investments requires the government to act along two

lines of action:


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104

The first task is to improve the country‟s investment climate. The corresponding need for

reforms in areas such as strengthening of property rights and fighting corruption and red-tape

is well understood, and the key measures have been widely discussed already. However, we

acknowledge that even when the government succeeds in improving the country‟s

investment climate, quick acceleration of investment activities is highly unlikely since trust

and confidence of investors can only be build up over a considerable period of time.

However, neither the economic nor the political situation in Ukraine allow to wait.

Accordingly, the second task is initiating public support to private investment in all relevant

areas including modernisation of capital stock in manufacturing, infrastructure or buildings.

As public budgets will not be able to provide the necessary funds, the government needs to

secure funding through international donors willing to support economic reconstruction in

Ukraine. In fact, by establishing improvements in energy efficiency as key condition for such

loans, the government can achieve a win-win situation:

As argued before, reducing energy intensity is key to re-vitalize the national

economy during times of rising energy prices. Hence, a benefit to Ukraine.

Reducing primary energy consumption as well as carbon emissions is a common

objective of international donors such as World Bank, EBRD, European Investment

Bank etc. Hence, using donors‟ funds to reduce energy intensity is a clear benefit to

those organisations as well.


Final Report

105

6. Findings from the economic assessment of a

domestic ETS and possibilities for linking the

ETS in Ukraine with other FSU countries

This section includes the executive summary of the Policy Paper No. 5 “MRV and

linking a potential ETS in Ukraine with other systems”. The paper is included as

Appendix C-7 to this Final Report.

Although the question of a future linking of a potential emission trading system (ETS) in

Ukraine with other ETS is currently more of hypothetical matter, some of the fundamentals

of an ETS, like for example Monitoring Reporting and Verification (MRV), are relevant

today for Ukraine anyway. That is because Ukraine takes part in international climate

change regulations and negotiations in upcoming new rules and instruments.O n the other

hand, Ukraine has adopted a revised Energy Strategy until 2030 which aims at increasing

energy efficiency in all sectors of the economy as well as supporting the use of renewable

energies.

Some of the fundamentals of linking an ETS outlined in this paper are therefore essential

for cooperation in international climate change framework as well as for the

implementation of national climate change and energy policies and strategies.

There are at least two main fundamentals for both linking and international cooperation to

ensure achieving the goals and targets of national strategies and policies:

Credibility, and

Stringency of targets.

The creation of a reliable system of monitoring, reporting and verification by the

government is essential for these fundamentals. MRV is key for:


Final Report

106

Ensuring greater transparency, accuracy and compatibility of information with regard

to climate change, energy efficiency etc. in order to identify good practice, foster a

learning process, and allow for international benchmarking

Recognition and visibility of mitigation achievements

Attribution of quantified impacts to policies

Accounting national and international progress

Identification of gaps and international support needs

Creation of access to international public and private finance.

The government should create frame conditions and rules which would allow the business

sector to benefit from international climate change cooperation and from the advantages of

linking an ETS with other similar systems, as well as from implementing national policies. A

reliable MRV system is a crucial element for that.

The current MRV system in place in Ukraine needs to be substantially improved not only

for a potential ETS but also for monitoring implementation of other GHG reduction

policies and measures like the carbon tax or the Energy Strategy 2030.

The MRV system should always be as robust and ambitious as feasible in order to be

most useful for domestic purposes of MRV, but also to address international

requirements at the same time. To establish two parallel systems for domestic and

international purposes would be highly inefficient.

Respective MRV guidelines and rules should be in accordance with guidelines and rules

of major potential emission trading partner countries.

As an MRV system is quite complex it needs strong coordination capacity between

national and subnational entities. Co-ordination and communication between regulators,

industry and verifiers through workshops or permanent working group proved to be very

helpful.

Due to the fact that a future ETS linking may generate advantages as well of

disadvantages both should be analysed in advance before making a decision on linking.


Final Report

107

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114

Appendix A

Figure A1: Overall efficiency levels (technical efficiency & scale efficiency) of metal industries in selected countries (in 2007)

Source: DIW ECON

Figure A2: Scale efficiency levels of metal industries in selected countries (in 2007)

Source: DIW ECON

0.0

0.2

0.4

0.6

0.8

1.0

0.0

0.2

0.4

0.6

0.8

1.0


Final Report

Appendix A

115

Figure A3: Overall efficiency levels of minerals industries in selected countries (in 2007)

Source: DIW ECON

Figure A4: Scale efficiency levels of minerals industries in selected countries (in 2007)

Source: DIW ECON


Final Report

Appendix A

116

Figure A5: Overall efficiency levels of chemicals industries in selected countries (in 2007)

Source: DIW ECON

Figure A6: Scale efficiency levels of chemicals industries in selected countries (in 2007)

Source: DIW ECON


Final Report

Appendix B

117

Appendix B-1

This Appendix contains detailed assumption used in the construction of the power model.

Macroeconomic assumptions

Variable Value Source

Discount factor 8% across all years Thomson Reuters MACTool

Report

Gas price 411.22 $/1000 m³ in 2013,

growing with 1% across all

years

Thomson Reuters MACTool

Report, own assumptions for

development

Gas energy content 36.24 MBTU/1000 m³ across

all years

Key World Energy Statistics

(IEA) (heat content of

Russian gas)

Coal price 101.18 $/t SKE in 2013,

growing with 0.5% across all

years

Coal Study (Opitz DIW

ECON), Thomson Reuters

MACTool Report, own

assumptions for

development

Coal energy content 27.77 MBTU/t SKE across all

years

A.G. Energiebilanzen

Nuclear fuel price 0.66 $c/kWh, growing with

0.5% across all years

Royal Academy of

Engineering

Load data 2010 detailed load data has

been fitted by 12% growth

and 2.5% peak shaving to fit

the official Ukrainian data.

Ukrstat


Final Report

Appendix B

118

Technology specific assumptions

Gas CHP old


Installed capacity 4300 MW in 2013, gradual

shutdown until 2020

(replacement through

gasCHP_new)

UNCS (email), Energy

Strategy, Thomson Reuters

MACTool Report,

Assumption by DIW ECON

Availability factor 70% flat across all years

(due to calibration, could be

up to 92% from TR); further

adjustment for seasonal

influence (during summer

20% of available capacity,

during winter 100% of

available capacity, hours of

the year are split even

between summer and winter)


Capital cost 0 $/kW across all years Due to shut down and

replacement with

gasCHP_new

O&M Cost 72.5 $/kW and 0 $/kWh

across all years


Report

Lifetime Shut down Assumption by DIW ECON

(based on Thomson Reuters

MACTool Report and Energy

Strategy)

Retrofit capital cost - No retrofit due to shut down

and replacement

Retrofit lifetime - No retrofit due to shut down

and replacement

Efficiency 30% across all years UNCS, Mitsubishi Heavy

Industries (data on efficiency

of old gas turbines)


Final Report

Appendix B

119

Gas CHP new (Natural Gas Combined Cycle CHP)



construction of 6300 MW

from 2014 to 2030, flat

afterwards


(based on Thomson Reuters

MACTool Report and Energy

Strategy)

Availability factor 70% flat across all years

(due to calibration, could be

up to 92% from TR); further

adjustment for seasonal

influence (during summer

20% of available capacity,

during winter 100% of

available capacity, hours of

the year are split even

between summer and winter


Capital cost 1100 $/kW across all years Thomson Reuters MACTool

Report

O&M Cost 72.5 $/kW and 0 $/kWh

across all years


Report

Lifetime 25 Thomson Reuters MACTool

Report

Retrofit capital cost 770 $/kW across all years Assumption by DIW ECON

(70% of capital cost)

Retrofit lifetime 20 Assumption by DIW ECON

Efficiency 60% across all years Siemens (maximum

efficiency for NGCC)

Nuclear old


Installed capacity 14000 MW in 2013, 10000

MW retrofitted in the first 10

years (2014 – 2023) and

Energy Strategy,

Assumptions by DIW ECON


Final Report

Appendix B

120

remaining 4000 MW

decommissioned until 2030.

Then 10000 MW flat until

2050

Availability factor 74% in 2013, gradual

increase to 77% in 2030, flat

afterwards

UNCS, Thomson Reuters

MACTool Report

Capital cost 0 $/kW across all years No new capacity installed

O&M Cost 1.67 $c/kWh across all years IEA (Projected Cost of

Generating Electricity), no

cost for waste disposal and

decommissioning accurately

included


Report


(70% of capital cost for

nuclear_new)

Retrofit lifetime 20 Energy Strategy

Nuclear new


Installed capacity 0 in 2013, then gradual

construction of new capacity,

depended on exogenous

demand growth

Scenario depended variable

Availability factor 89% flat across all years National Renewable Energy

Laboratory


Report

O&M Cost 1.67 $c/kWh across all years IEA (Projected Cost of

Generating Electricity), no

cost for waste disposal and


Final Report

Appendix B

121

decommissioning accurately

included


Report




Coal old



shutdown of 12000 MW and

continuous retrofit of the

remaining 5200 MW until

2030, flat afterwards

Energy Strategy,

Assumptions by DIW ECON



afterwards


(due to bad condition of

Ukrainian coal TPPs, see

Energy Strategy)


O&M Cost 37.8 $/kW and 0.00447

$/kWh across all years

Energy Information

Administration


Report

Retrofit capital cost 1500 $/kW across all years Energy Strategy


Efficiency 24% across all years Assumption by DIW ECON

(due to age and bad

condition of Ukrainian coal

TPPs, see Energy Strategy

and UNCS)


Final Report

Appendix B

122

Coal new (Ultra Super Critical Coal TPP)


Installed capacity 0 in 2013, then gradual



demand growth


Availability factor 85% across all years Natio b nal Renewable

Energy Laboratory


Report

O&M Cost 37.8 $/kW and 0.00447


Energy Information

Administration


Report



Efficiency 50% across all years World Coal Association

Coal CHP


Installed capacity 4800 MW across all years,

continuous retrofit

UNCS, Assumption by DIW

ECON



afterwards


(due to bad condition of

Ukrainian coal TPPs, see

Energy Strategy)


O&M Cost 37.8 $/kW and 0.00447


Energy Information

Administration


Report



Final Report

Appendix B

123


Efficiency 24% across all years Assumption by DIW ECON

(due to age and bad

condition of Ukrainian coal

TPPs, see Energy Strategy

and UNCS)

Large hydro old


Installed capacity 4754 MW all retrofitted in the

first 10 years (2014-2023)

Energy Strategy

Availability factor 31% in 2013, then gradual

increase to 60% in 2030


Report, Assumption by DIW

ECON (TR only gives

capacity factors)


O&M Cost 85 $/kW in 2013, then

gradual decline to 60 $/kW in



Report

Lifetime 50 Assumption by DIW ECON

(based on past information

about hydro plants)

Retrofit capital cost 128 $/kW across all years Energy Strategy (5 bln. UAH

of investments until 2023 to

ensure retrofit)


Large hydro new


Installed capacity 0 MW in 2013, then gradual

construction of 1046 MW

until 2030, flat afterwards

Energy Strategy

Availability factor 55% in 2013, then gradual Assumption by DIW ECON


Final Report

Appendix B

124


afterwards

(Thomson Reuters MACTool

Report only gives capacity

factors)

Capital cost 6250 $/kW in 2013, then

gradual decrease to 4000

$/kW until 2030, flat

afterwards


Report





Report


Report

Retrofit capital cost 4375 $/kW in 2013, then



afterwards




Small hydro



extension to 600 MW until



Report

Availability factor 55% across all years Thomson Reuters MACTool

Report




afterwards. CAPEX for 2013

assumed to be the same as

2014



ECON




Report


Final Report

Appendix B

125



Report




afterwards




Pumped storage


Installed capacity 900 MW in 2013, then

gradual extension to 4700

MW until 2030, flat

afterwards

Energy Strategy

Availability factor 80% across all years Assumption by DIW ECON

(TR only gives capacity

factor)

Capital cost 1550 $/kW across all years,

CAPEX for 2013 assumed to

be the same as 2014



ECON

O&M Cost 5 $/kW across all years, Thomson Reuters MACTool

Report


Report




Large solar PV



gradual extension to 1500


Report, UNCS


Final Report

Appendix B

126

MW until 2030, flat

afterwards


Report




afterwards, 2013 CAPEX

based on UNCS

(subcontractor) data


Report, UNCS, Assumption

by DIW ECON

O&M Cost 0.01 $/kWh across all years Thomson Reuters MACTool

Report


Report




afterwards




(whole new panels)

Residential solar PV



construction of 459 MW until

2030, then gradual extension

to 1000 MW until 2050


Report


Report




afterwards


Report


Final Report

Appendix B

127


Report


Report




afterwards




(whole new panels)

Wind



gradual construction of new

capacity, depended on

exogenous demand growth

UNCS, Scenario depended

variable


Report




afterwards, 2013 CAPEX

based on UNCS

(subcontractor) data


Report, UNCS, Assumption

by DIW ECON

O&M Cost 71 $/kW across all years Thomson Reuters MACTool

Report


Report




afterwards




Final Report

Appendix B

128


Biomass





demand growth


Availability factor 76% in 2013, then gradual


afterwards


Report




afterwards


Report


Report


Report




afterwards





Final Report

Appendix B

129

Appendix B-2

This Appendix contains the list of measures used by Thomson Reuters Point Carbon (2013) to

calculate the abatement potential in different sectors of the Ukrainian economy.

Measures in coal mining (2014-2054)

Action MAC Value in $/ton Emissions Reduction (2014-

2054) in millions tons CO2e

Coal Mine Methane – Ventilation Air

Machine (VAM)

2 52

Coal Mine Methane – Combined

Heat and Power (CHP)

2 61

Coal Mining Energy Efficiency 740 32

Measures in manufacturing (2014-2054)



Aluminum Scrap Recycling 40 37

Ammonia Energy Efficiency 3 17

Ammonia Electrolysis 58 76

Dry Cement Process 5 24

Wet Cement Process (Slag) 153 93

Shale Gas in Cement 65 19

Direct Reduction Iron 24 309

Iron Ore Production Energy

Efficiency

1 46

Steel Rolling/Casting Energy

Efficiency

26 10

Steel Continuous Rolling 2 158

Steel Electric Arc Furnace (EAF) 4 114

Lime Production Energy Efficiency 122 5

Paper Production Energy Efficiency

(Boiler Replacement)

8 1


Final Report

Appendix B

130

Measures in waste management (2014-2054)



Landfill Gas Power (LFG) 3 38

Clean Municipal Solid Waste Power

(MSW)

45 6

Waste Water Utilization for Power 29 18

Segregate Colloids Utilization for

Power (Food Waste Biogas)

11 57

Replace Obsolete Municipal Waste

Facilities (Pumping Systems)

12 4

Composting 1 3

Biodegradable Plastics 2 160

Increased Recycling 68 24

Modern Materials Recycling 12 2

Waste Production Limits 215 215

Measures in buildings and heat supply (2014-2054)



Draught Proofing 6 91

Wall Insulation 16 57

Windows Energy Efficiency 33 31

Boiler Upgrades 11 84

Heat Pumps 294 24

Heat Network Optimization 35 66

Heat Network Boiler Upgrade 420 14

Water Energy Efficiency 18 64


Final Report

Appendix B

131

Measures in agriculture and other land use (2014-2054)



Biogas Plants - Cattle 5 100

Biogas Plants - Swine 13 24

Concentrated Fodder - Cattle 143 2

Reduction of Cows – Increased Milk

Production

19 8

Ionophores in Cattle Ration 0 13

Zeolites in Cattle Ration 19 18

Sunflower Seeds in Cattle Ration 304 31

Crop Rotation 271 16

Extensive to Intensive Agriculture

Processes

9 27

Nitrification Inhibitors in Corn

Production

25 12

Erosion Prevention Measures 156 9

Preservation of Degraded Lands 36 3

Wetlands Renewal 0 13

Straw Combustion 304 31

Organic Farming 81 14

LULUCF – Organic Fertilizer Use 15 301

LULUCF – No Till Techniques 1 239

LULUCF - Afforestation 35 15

Measures in transport (2014-2054)



Gas Pipeline Modernization 1078 25

Gas Transport Modernization 687 43

NG Pressure Reduction -366 6

Vehicle Energy Efficiency 921 188

Biofuels 199 133

City Transport Electrification 8230 0


Final Report

Appendix B

132

Railway Electrification 34 6

Source: Thomson Reuters Point Carbon (2013)


Final Report

Appendix C-1: Green Growth Policy Paper No. 1

Appendix C-1

Benchmarking for sustainable and

economically viable technology

options

Low Carbon Ukraine - Policy Paper No. 1 (December 2012)


Final Report



The case of the metal industry in Ukraine

Green Growth Policy Paper No. 1

ii



options


Low Carbon Ukraine - Policy Paper No. 1 (December 2012)

Project





iii

Contact:

DIW econ GmbH

Dr. Lars Handrich

Mohrenstraße 58

10117 Berlin

Germany

Phone +49.30.20 60 972 - 0

Fax +49.30.20 60 972 - 99

[email protected]

www.diw-econ.de





iv

Table of contents

Executive Summary .............................................................................................................. iv

1. Introduction ..................................................................................................................... 1

2. The benchmarking approach .......................................................................................... 1

3. Benchmarking for the Ukrainian metal industry ............................................................... 3

3.1 Database .................................................................................................................. 3

3.2 Benchmarking methodology ..................................................................................... 4

3.3 Benchmarking results ............................................................................................... 6

3.4 Implications for the metal industry of the Ukraine ...................................................... 8

4. Conclusions and outlook ................................................................................................14

Appendix ..............................................................................................................................15




v

Executive Summary

Detailed sectoral analysis is an important component of the search for green growth

potentials in the economy of the Ukraine. The focus of the present paper is on developing a

general approach for sectoral analysis that takes into account economic viability as well as

environmental sustainability.

We present an international benchmarking approach that is based on the economic concept

of efficiency. The yardstick for comparing the performance of the economic sectors in

different countries is given by:

High levels of desired outputs such as production volumes (in physical unites) or

revenues (values),



As a first example, we apply our efficiency-based international benchmarking approach to the

metal industry. The procedure is used to identify the relevant technological yardsticks that

could be applied in the case of the Ukraine. The results show large potential for reducing

greenhouse gas emissions in the Ukrainian metal industry. The full realisation of this

potential would allow abating 52 Mt per year in terms of CO2 equivalent. The assessment of

the corresponding investment need will be the subject of our consecutive analysis.




1

1. Introduction

Developing a low-carbon growth strategy requires an understanding of the mitigation

potential in the most relevant sectors of an economy. The focus of the present paper is on

developing a general approach for sector-specific analysis of mitigation potentials that takes

into account economic viability as well as environmental sustainability. In this paper we apply

the suggested methodology to the analysis of the metal industry in Ukraine.

In the following we present a benchmarking approach that is based on the economic concept

of efficiency. In particular, it explicitly takes into account that production processes have

undesired outputs, the amount of which should be minimized. In this first application we take

greenhouse gas emissions as an example of such undesired outputs. The approach,

however, can be applied for different industrial sectors and different kinds of adverse

environmental impacts.

2. The benchmarking approach

The key objective of our benchmarking approach is to identify technology options for a given

industrial sector to best combine sustainability and economic viability. The yardstick for this

comparison is balanced combinations of:


revenues (values),



The focus of the benchmarking approach is on technologies that are actually used in

practice, while theoretical solutions and technologies that are not yet implemented are not



In economic terms, the best combinations of desired outputs, undesired outputs and inputs

are considered to be efficient. Theoretically, efficiency levels of different technologies can be

measured as well as decomposed into different subcomponents related to technology, scale




2

and price levels (see Box 1). For practical applications, however, such a comparison is

strongly limited by the availability of data and relevant information. In particular, micro-level

benchmarking of different installations or companies is rather difficult and requires access to

private and often confidential information. Alternatively, one can benchmark the same

industry across different countries. In this way, detailed company- or even installation-

specific information is compensated by aggregate information from a range of countries,

which is more easily available. Such an international benchmarking allows for identifying

those countries where the most efficient technologies are used.


Efficiency is an economic concept which describes the optimal use of production factors in



inputs) and the specific goods such as steel, chemicals or food (henceforth outputs) which

are produced from these inputs. It is typically defined as either:



The highest-possible level of outputs that can be produced from at given set of inputs




Technical efficiency describes the ability of a firm to obtain optimal combinations of

input and output quantities;

Scale efficiency describes the ability of a firm to produce at optimal combinations of

input and output quantities while optimising all scale economies; and



In this analysis, efficiency will be measured in terms of technical efficiency and scale

efficiency.




3

3. Benchmarking the metal industry in Ukraine

In this section we illustrate our benchmarking approach for the case of the metal industry in

Ukraine. To do so, we compare the relationship between the inputs used in the production

processes in different countries (i.e. labour, capital and energy) and the respective outputs in

terms of metal products and greenhouse gas (GHG) emissions.

3.1 Database

The available data on the metal industry in different countries stems from four key sources:

the World Input Output Database (WIOD) which has been compiled by a consortium

of scientific organizations with financial support of the European Union60,

the Steel Statistical Yearbook of the World Steel Association61,

the United States Geological Survey Mineral Resources Program62, and

the United Nations Framework Convention on Climate Change (UNFCCC)63.

In those datasets, different industries are defined in accordance with the ISIC standard of the

United Nations Statistics Division. The metal industry is described as “Manufacturing of basic

metals” and “Manufacturing of fabricated metals”.64 This includes the production of pig iron,

crude steel (primary or secondary fusion), precious and non-ferrous metals as well as metal

casting and the production of fabricated metal products.65

With respect to the countries that are included in the international benchmarking exercise,

our intention was to primarily cover technological leaders in the relevant sector. Our

database covers 27 EU countries and 13 other major countries in the world for which the

following information is available:

GHG emissions (in thousand tonnes of CO2 equivalent, source: wiod.org)66,

Energy Use, Emission Relevant (in TJ, source: wiod.org),


61 http://www.worldsteel.org/

62 http://minerals.usgs.gov/


64 ISIC Rev 3.1 sectors 27 and 28.

65 Note that the analysis does not include the mining of metal ore and the production of coke.

66 UNFCCC for Luxembourg and Ukraine


http://www.worldsteel.org/





4

Gross Output (in millions of US dollars, source: wiod.org),

Number of persons employed (in thousand persons, source: wiod.org),

Real fixed capital stock (in millions of US dollars, source: wiod.org),

Total production of pig iron (in thousand metric tonnes, source: World Steel

Association),

Production of crude steel (in total and by production process, all in thousand metric

tonnes, source: World Steel Association),

Production of non-ferrous metals (aluminium and ferroalloys, in thousand metric

tonnes, source: United States Geological Survey Mineral Resources Program)

For the present analysis 22 OECD countries and 3 non OECD countries are included in the

data base (as listed in Table 1 below). The most recent information for all countries is

available for the year 2007 which is the base year for the benchmarking exercise.67

Ukraine is included in all sources except of WIOD. While the levels of gross output and

employment are available from national statistics, there is no reliable information on capital

stocks in the metal industry. Hence, the country can only partially be considered in the

following benchmarking analysis.

3.2 Benchmarking methodology

Table 1 gives a first impression on the performance of the metal industry in the different

countries. The first two columns refer to the sustainability (emissions per output), the third

and fourth column to economic viability (output per capital input) of the production processes

in the different countries. For ease of comparison, the three top performers in each column

are shaded in grey. With respect to sustainability indicators (columns i and ii), Italy, Slovenia,

Luxembourg and Brazil show top performance, while Finland, Hungary, Korea, Brazil, Poland

and Slovakia are the top countries with respect to economic viability (columns iii and iv).

Finally, the table highlights the performance of the metal industry in Ukraine with respect to

sustainability (columns i and ii).68

67 In fact, 2007 is a good choice for a base year since it is the last year before the start of the global economic crises.

68 Note that values for columns iii and iv are not available for Ukraine since there is no reliable estimate on capital stocks.




5

Table 10: Comparison of capital and emissions intensities across counties, year 2007

2007





(tons of CO2-e per thousand

US-$)

(tons of CO2-e per ton of metal

product) (US-$ per US-$)

(tons of metal product per

thousand US $)

(i) (ii) (iii) (iv)

Australia 0.43 2.01 2.19 0.47

Austria 0.34 0.96 2.79 1.00

Belgium 0.22 0.69 2.65 0.86

Brazil 0.37 0.48 1.92 1.47

Canada 0.36 1.16 3.43 1.06

Czech Republic 0.47 1.06 2.45 1.09

Finland 0.23 0.87 4.03 1.08

France 0.15 0.70 2.61 0.56

Germany 0.21 0.81 3.08 0.79

Greece 0.13 0.64 2.89 0.60

Hungary 0.32 0.90 3.91 1.41

India 0.77 1.22 1.70 1.07

Italy 0.10 0.54 1.75 0.32

Japan 0.27 0.69 1.34 0.52

Korea 0.34 0.87 3.71 1.45

Luxembourg 0.13 0.25 2.06 1.04

Netherlands 0.20 0.56 2.90 1.05

Poland 0.58 1.18 3.31 1.62

Slovakia 0.71 0.93 3.04 2.31

Slovenia 0.09 0.85 3.12 0.34

Spain 0.13 0.65 2.16 0.43

Sweden 0.15 0.66 2.82 0.63

Taiwan 0.38 0.87 1.83 0.80

United Kingdom 0.32 1.14 2.77 0.79

United States 0.25 1.07 3.09 0.72

Ukraine 2.90 1.12

Source: DIW econ based on wiod.org, World Steel Association, UNFCCC,

and the State Statistics Service of Ukraine




6

However, the comparison of different indicators does not yet allow for deriving overall

conclusions. In fact, it must be emphasized that:

First, output can be measured as value or in physical quantities (i.e. in millions of Dollars

or in tons of output). However, metal industries produce a range of different products

such as pig iron, crude steel, non-ferrous metals (aluminium and ferroalloys) based on

different production processes. Hence, a meaningful output measure must consider the

relevant structural characteristics.

Second, the costs of production (inputs) not only include capital but also other key inputs

such as labour and energy.

Third, the isolated comparison of different indicators does allow for identifying the leaders

in each respective category, but not necessarily for identifying those countries that

perform relatively well in all categories. However, the objective of our benchmarking

analysis is to identify the best combinations of both, sustainability as well as economic

viability.

To identify the countries that realize the most-efficient combinations of inputs and outputs

(that is, the most efficient technologies) we employ a specific, empirical estimation technique,

the Data Envelopment Analysis (DEA). This is a well-established methodology for estimating

different efficiency measures as described in Box 1 above based on a large variety of

different input and output measures. For benchmarking metal industries, we consider the use

of capital, labour and energy as key inputs and differentiate outputs into pig iron, crude

steel69and non-ferrous metals. We also differentiate between primary and secondary

production of crude steel as they represent different production chains and differ strongly by

energy consumption and GHG emissions.

3.3 Benchmarking results

Our benchmarking analysis of the metal industry is based on output-oriented efficiency

measures of technical efficiency und scale efficiency (see Box 1). In other words, we identify

the countries that operate at an efficient scale and are able to produce the highest volumes

of outputs with the lowest levels of emissions from a given set of inputs (output-oriented

69 Due to data limitations, the production of other steel products like rolled product, pipes, tracks etc. cannot be considered in this analysis. However, since these production processes cause relatively low levels of emissions as compared to those from pig iron and crude steel production, this does not significantly distort the results of the present analysis.




7

efficiency). All efficiency estimates are given as indices ranging from zero to one, which

indicates the best performance. For example, a technical efficiency score of one for a given

country indicates that in no other country within our sample the metal industry produces more

outputs from the same combination of inputs. Likewise, a technical efficiency score below

one suggests that at least in one other country the metal industry is capable to produce

higher outputs from the same inputs. Similarly, a scale efficiency score equal to one indicates

that the country‟s metal industry is producing at efficient scale while a score of less than one

indicates that other countries are better in utilizing scale economies.

Figure 40: Overall efficiency levels (technical efficiency & scale efficiency) of metal industries in selected countries (in 2007)

Source: DIW econ

Overall efficiency levels (technical efficiency & scale efficiency) of metal industries in the

selected countries are summarised in Figure 1. Separate results for technical and scale

efficiency are shown in the appendix. The overall result is as follows:

In 12 out of the 25 countries in the sample (Australia, Belgium, Canada, Finland, Greece,

Hungary, Korea, Luxembourg, the Netherlands, Slovakia, Slovenia and Spain) the metal

industry operates fully efficient. These countries determine the technology frontier of the

international metal industry in 2007.

0,0

0,2

0,4

0,6

0,8

1,0




8

Among the inefficient countries, two different subgroups can be identified based on the

additional results for technical efficiency and scale efficiency as shown in the Appendix:

in Austria, Brazil, Germany, India, Italy, Japan, Poland and the United States, metal

industries are technically efficient but operate at too large scale (that is,

underutilization of available production capacities), while

in the Czech Republic, France, Sweden, Taiwan and in the United Kingdom, the

metal industry suffers also from technical inefficiency.

For all countries where the metal industry is found to be inefficient, the analysis provides

insights for possible improvements. For example:

The overall efficiency level for the Germany metal industry is estimated at 67% due to

operations at an inefficient scale. Likewise, overall efficiency of the Brazilian metal

industry equals 82% due to inefficient scale of operations. In fact, this suggests that the

German and the Brazilian metal industry could produce the same output at only 67% and

82%, respectively, of its current scale (i.e., its current input levels).

The overall efficiency level for the metal industry in the Czech Republic is estimated at

85%, caused by technical inefficiency (technical efficiency score of 0.98, see Appendix)

and inefficient scale of operations (scale efficiency score of 0.87 , see Appendix). This

suggests that:

the industry could produce the same output at only 87% of its current scale (input

levels), and

given operations at an efficient scale (input levels), output could be increased by 2%

(=1-0.98).

3.4 Implications for the metal industry of the Ukraine

Due to missing information on the capital stock of the Ukrainian metal industry, it is not

possible to directly include Ukraine in the benchmarking analysis presented above. However,

results and implications for Ukraine‟s metal industry can be derived by identifying countries

with comparable structural characteristics and then focussing on the results and implications

for these countries.

The most relevant structural characteristics of metal industries across the different countries

are shown in Figure 41. With the exemption of Slovenia, Greece and Luxembourg, all




9

countries under consideration produce pig iron as well as crude steel (Figure 41 a). The

share of pig iron in total production of iron and steel in the Ukraine (45%) is close to the

average share over all countries (34%). A second characteristic of the metal industry in

Ukraine is a relatively large share of aluminium and ferroalloys (3%). In fact, of the remaining

25 countries, only Australia, Brazil, Canada, India and the United States produce higher

volumes of non-ferrous metals than Ukraine, while Luxembourg, Hungary, the Czech

Republic, Austria, Belgium and Taiwan have no or almost no production. Hence, based on

output composition the metal industry of Ukraine is not comparable to Slovenia, Greece,

Luxembourg, Hungary, the Czech Republic, Austria, Belgium and Taiwan and most similar to

Australia, Canada, Brazil, India and the United States.




10

Figure 41: Structural characteristics of the metal industry in different countries

c) Output composition

Source: DIW econ

* Complete data for Japan omitted for better representation. Full data: 87 million tons of pig iron, 120 million tons of crude steel, 0.9 million tons of non-ferrous metals.

b) Structure of crude steel production processes

Source: DIW econ

0

20

40

60

80

100

120

140

mill

ion tons

Pig Iron Crude Steel Aluminium & Ferroalloys

0%

20%

40%

60%

80%

100%

Oxygen Blown Converter and Open Hearth Furnace Electric Furnace




11

The second relevant structural characteristic of metal industries is the structure of crude steel

production (Figure 41 b). Overall, two main processes can be distinguished. Oxygen blown

converters (OBCs) and open hearth furnaces (OHFs) are methods of primary steelmaking in

which pig iron is made into crude steel70 while electric arc furnaces (EFs) are mostly used for

secondary steelmaking based on metal scrap71. Obviously, all countries where pig iron is

produced also use OBCs as primary steelmaker, however at different levels72. Here, Ukraine

stands out with 96% primary steel production based on OBCs and OHFs. With respect to

GHG emissions, this is of particular relevance since primary steelmaking based on OBCs

and in particular OHFs is more energy- and thus, emission-intensive than secondary

steelmaking based on EFs. Hence, a metal industry that is structurally similar to that of the

Ukraine should also be focussed on primary steel making. As can be seen in Figure 41 b, the

countries with similarly high share of OBCs are the Netherlands, Slovakia, Austria, the Czech

Republic and to a lesser extent Australia, Belgium, Brazil, Finland, Germany, Hungary,

Japan, Sweden and the United Kingdom.

The results of this comparison are summarised in the following Table 2. Obviously, for four

countries in the sample the metal industries are similar to that of the Ukraine by output

composition as well as by crude steel production processes:

Australia,

Brazil,

the Netherlands, and

Slovakia.

The industries in Australia, the Netherlands and Slovakia operate at the highest efficiency

levels (see Figure ), whereas Brazil is technically efficient but operates at too large scale.

These countries can be taken as peer countries for identifying sustainable and economically

viable technology options for the Ukrainian metal industry. To a lesser extent, this is also the

case for Austria, Canada, Finland, India and the United States. However, the industries in

these countries are all not fully comparable. In Canada, India and the United States, the

share of EFs in the production of crude steel is much higher than in the mentioned peer

countries. In Austria and Finland, the share of energy-intensive productions of non-ferrous

metals is too low.

70 http://en.wikipedia.org/wiki/Basic_oxygen_steelmaking

71 http://en.wikipedia.org/wiki/Electric_arc_furnace

72 Nevertheless, pig iron is also traded internationally.

http://en.wikipedia.org/wiki/Basic_oxygen_steelmaking

http://en.wikipedia.org/wiki/Electric_arc_furnace




12

Table 11: Comparing the metal industry of the Ukraine with other countries

Countries with a structurally similar metal

industry by… Efficiency score

… output composition

… crude steel production process

(technical efficiency)

Australia X x 1.00

Austria X 1.00

Belgium x 1.00

Brazil X x 1.00

Canada X 1.00

Czech Republic X 0.98

Finland x x 1.00

France x 0.98

Germany x 1.00

Greece 1.00

Hungary x 1.00

India X 1.00

Italy 1.00

Japan x 1.00

Korea 1.00

Luxembourg 1.00

Netherlands x X 1.00

Poland 1.00

Slovakia x X 1.00

Slovenia 1.00

Spain 1.00

Sweden x x 0.99

Taiwan 0.98

United Kingdom x x 0.95

United States X 1.00

Key: Strong similarity

Slight similarity Source: DIW econ

Having identified the relevant peers for the metal industry in Ukraine, we will next take a

closer look at the performance indicators of these countries. For convenience, Figure 3




13

presents the indicators of emissions intensity and economic viability. The reversed direction

of bars for emissions intensity illustrates that emissions are an undesired output.

Figure 42: Comparison of Ukraine with peer countries

Source: DIW econ

What can be inferred from these values for the GHG emissions reduction potential of the

Ukrainian metal industry? Although the respective emission values for the Netherlands and

Slovakia are higher than the Brazilian, the two countries operate at a fully efficient level

whereas Brazil operates at too large scale. Nevertheless Brazil is technically efficient and

possesses of the comparable share of non-ferrous metals production, mainly aluminium

production. As for the year 2007, the difference in technological level between the metal

sectors in the two countries corresponds to roughly 60% higher emissions per unit of output

in Ukraine. Related to the emissions level of 2007, the full realisation of this potential (which

obviously requires very substantial investment expenditures) would allow abating 52 Mt per

year in terms of CO2 equivalent.

2

1

0

1

2

3

Ukraine Brazil Netherlands Slovakia

tons C

O2-e

per

ton

US

$ p

er

US

$

Emissions per volume of production Revenue per capital stock

maximum reduction

potential (60%)




14

4. Conclusions and outlook

The benchmarking approach presented in this paper takes into account two main aspects of

the industrial production processes: economic viability and environmental sustainability. Both

aspects are combined in the economic concept of efficiency, which can be measured for a

given industry in different countries and used for comparison. The general approach is

applicable to different industries.

As a first example, we apply our efficiency-based international benchmarking approach to the

metal industry. The procedure is used to identify the relevant technological yardsticks to

apply for the case of Ukraine. The results show large potential for reducing GHG emissions

in the Ukrainian metal industry.

The presented analysis should be extended at a later stage to include several important

aspects. First, an assessment of the investment need corresponding to the adoption of the

identified benchmark technologies should be carried out. Second, the analysis should be

extended to include the dynamic perspective, the development of the technology frontier over

time.




15

Appendix

Figure A1: Technical efficiency levels of metal industries in selected countries (in 2007)

Source: DIW econ

Figure A2: Scale efficiency levels of metal industries in selected countries (in 2007)

Source: DIW econ

0,0

0,2

0,4

0,6

0,8

1,0

0,0

0,2

0,4

0,6

0,8

1,0




16


Final Report


Appendix C-2

Towards a low carbon growth strategy

for Ukraine

Low Carbon Ukraine - Policy Paper No. 2 (April 2013)


Final Report



Final Report


Towards a low carbon growth

strategy for Ukraine

Key policy steps

Low Carbon Ukraine - Policy Paper No. 2 (April 2013)

Project


Towards a low carbon growth strategy for Ukraine:

Key policy steps


ii

Contact:

DIW econ GmbH

Dr. Lars Handrich

Mohrenstraße 58

10117 Berlin

Germany

Phone +49.30.20 60 972 - 0

Fax +49.30.20 60 972 - 99

[email protected]

www.diw-econ.de



Key policy steps


iii

Table of Contents


1. Introduction ..................................................................................................................... 1

2. The structure of the Ukrainian economy ......................................................................... 1

2.1 Ukraine‟s economic structure and pattern of trade .................................................... 1

2.2 Ukraine‟s carbon record ............................................................................................ 4

3. Towards low carbon growth in Ukraine ........................................................................... 7

3.1 Framework conditions for low carbon growth ............................................................ 7

3.1.1 The role of the Ukrainian government ............................................................... 7

3.1.2 The role of International Cooperation ................................................................ 9

3.2 A sectoral policy mix ............................................................................................... 10

3.2.1 Industrial Sector ...............................................................................................10

3.2.2 Energy Sector ..................................................................................................11

3.2.3 Transport Sector ..............................................................................................14

3.2.4 Residential Sector ............................................................................................15

4. Policy Recommendations ..............................................................................................15

Literature ..............................................................................................................................17


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Executive Summary

Ukraine is one of the most energy-intensive economies in Europe. New impulses are needed

to overcome traditional production structures that are no longer efficient and unsustainable in

social and environmental terms. This paper identifies the key areas in terms of potential to

reduce greenhouse gas (GHG) emissions and derives the corresponding policy actions

needed to foster low carbon growth.

We argue that growth can only be sustained by fundamentally shifting the Ukrainian

economy away from its current carbon-intensive path to a form of growth that is less

dependent on the heavy use of natural resources, especially coal.


Firstly, private investments into clean technologies can only be induced by increasing the

cost of emitting GHG, for example through carbon pricing or the introduction of an Emission

Trading System (ETS). Secondly, the Ukrainian government needs to promote research and

development into innovative clean technologies. Thirdly, in order to profit from possible

financial assistance and technology transfers from abroad, the Ukrainian government may

need to enter into further international commitments and guarantee a more ambitious

reduction target in the level of emissions.

The main obstacles for a transition to low carbon growth in Ukraine are the lack of

diversification of the economy, heavy reliance on expensive fossil-fuel imports, outdated and

inefficient production capacities and unsustainably high subsidies in energy pricing. This

implies a dire need for the government to increase competition, introduce market-based

prices and to improve energy efficiency across all sectors.

The sectors with the greatest potential in terms of emission reductions are the industrial

sector, the energy sector including energy resources as well as electricity and heat

production, the transport sector and the residential sector. Promising sectoral policies include

the modernization of the capital stock in the industrial sectors, the liberalization of the energy

market, deregulations in the heating and electricity sectors as well as improved heat

containment in residential buildings and the introduction of fuel taxes for private transport.


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1. Introduction

From 2000 until the beginning of the economic crisis in 2008, the Ukrainian economy had

been growing significantly, however at the expense of excessive depletion of natural

resources and degradation of the ecosystem. Due to the heavy reliance on cheap energy,

especially coal, and the production of steel, the economic structure of Ukraine is highly

carbon intensive. Today, Ukrainian policy makers are facing the challenge to decrease GHG

emissions without restricting economic activity. But how can the Ukrainian government tackle

emission reductions and climate change while at the same time maintaining further growth,

even in the short run?

This paper discusses the policy framework needed to enable sustainable investments in

clean technologies. We outline concrete steps and recommendations for the Ukrainian

government in the uptake of a low carbon growth strategy.

The paper is structured as follows. Section 2 provides a brief overview of the general

economic structure, pattern of trade and carbon intensity in Ukraine and identifies the

economic sectors with the greatest potential for emission reductions. Section 3 discusses the

framework conditions needed for the successful implementation of a low carbon strategy and

outlines a specific policy mix aimed at the different economic sectors identified in section 2.

Section 4 concludes with a summary of the main policy recommendations established

throughout this paper.

2. The structure of the Ukrainian economy

2.1 Ukraine’s economic structure and pattern of trade

Although Ukraine‟s economy had been growing significantly until the crisis in 2008/2009, this

is not a blueprint for future development. The significant growth in the years before the crisis

relied to a considerable extent on the abundant availability of rather cheap energy resources.

The pre-crisis economic model relied heavily on cheap energy imports mainly from Russia

and high export volumes of ferrous and non-ferrous metals (see Tables 1 and 2).


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Ferrous and nonferrous metals account for a third of total exports while the import share of

mineral products (including mineral fuels such as oil and gas) is even more than one third of

total imports. With a negative trade balance the current economic model triggers high trade

and current account deficits and will not be sustainable anymore.

Table 1: Ukraine’s export structure (2010-2012)

2010 2011 2012

In million USD Agricultural products 9,935 12,804 17,881

Mineral products (incl. mineral fuels) 6,237 9,608 6,945

Chemicals 4,658 6,980 6,763

Timber and wood products 1,768 2,184 2,193

Industrial goods 1,309 1,621 1,543

Ferrous and nonferrous metals 17,333 22,114 18,890

Machinery and equipment 9,183 11,895 13,284

Other (incl. informal trade) 1,768 2,212 2,313

Total (million USD)

52,191 69,418 69,812

% of total

Agricultural products 19.0 18.4 25.6

Mineral products (incl. mineral fuels) 11.9 13.8 9.9

Chemicals 8.9 10.1 9.7

Timber and wood products 3.4 3.1 3.1

Industrial goods 2.5 2.3 2.2

Ferrous and nonferrous metals 33.4 31.9 27.1

Machinery and equipment 17.5 17.1 19.0

Other (incl. informal trade) 3.3 3.2 3.3

Total (%) 100 100 100

Source: National Bank of Ukraine (2013), own calculations


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Table 2: Ukraine’s import structure (2010- 2012)

2010 2011 2012

In million USD

Agricultural products 5,762 6,346 7,520

Mineral products (incl. mineral fuels) 20,707 29,396 27,077

Chemicals 10,524 12,961 13,519

Timber and wood products 2,000 2,230 2,182

Industrial goods 3,355 3,508 4,465

Ferrous and nonferrous metals 4,128 5,695 5,238

Machinery and equipment 12,689 20,018 22,433

Other (incl. informal trade) 1,414 5,516 7,870

Total (million USD) 60,579 85,670 90,304

% of total

Agricultural products 9.7 7.4 8.3

Mineral products (incl. mineral fuels) 34.3 34.3 30.0

Chemicals 17.4 15.1 15.0

Timber and wood products 3.3 2.6 2.4

Industrial goods 5.5 4.1 4.9

Ferrous and nonferrous metals 6.8 6.6 5.8

Machinery and equipment 20.7 23.4 24.8

Other (incl. informal trade) 2.3 6.4 8.7

Total (%) 100 100 100

Source: National Bank of Ukraine (2013), own calculations

Relying on energy intensive production technologies, Ukraine‟s heavy industry also causes

high emission rates of GHG. For instance, steelmaking in Ukraine requires four times more

energy in Ukraine than in China (OECD 2012). In a separate paper, we estimate the annual

potential of reducing GHG emissions for the Ukrainian metal industry to reach a level of 52

Mt per year in terms of CO2 equivalent if switching to efficiency based technologies available

today (see DIW econ 2012c).

The Ukrainian economy is lacking competition and transparency in the energy sector,

especially in the gas market, causing rent seeking behaviour and economic inefficiencies.

The funds spent on subsidies in the energy sectors place a heavy strain on the government

budget, decrease the funds available for other policy measures and increase the tax burden.

A serious drawback is the focus of economic investments on the recommissioning of already

existing but outdated production capacities, thereby impeding the real increment in more

efficient production capacities and technologies. Furthermore, innovations – essential for


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sustainable growth – do not play an important role as a growth determinant in Ukraine. The

growth of Ukrainian GDP is driven much less by Research and Development than in other

nations (see Technical Paper, DIW econ 201373).

In the past five years, economic growth in Ukraine slowed down significantly. This is mainly

due to the following reasons:

A declining demand for Ukrainian exports. In particular China has switched in recent

years from a net-importer to a net-exporter of ferrous and non-ferrous metals by building

up its own production capacities.

The gas crisis: Since 2005 import prices for Russian gas have been increasing

significantly. Today Ukraine is paying one of the highest gas prices in Europe.

The economic and financial crisis in 2008/2009 and the political turmoil in the

Mediterranean and North Africa (MENA) region have led to a further drop in demand for

Ukrainian exports.

Ukraine is lacking behind with regards to foreign direct investments; the investment

environment is rather poor and has significantly deteriorated in the recent past. The

combination of widespread corruption and weak investor protection with a flawed

judiciary has left Ukraine 152nd out of 183 countries in the World Bank‟s most recent

Ease of Doing Business ranking.

Furthermore, the Ukrainian economy suffered repeated financial bottlenecks.

In conclusion, the present Ukrainian economic model is exhausted and will not generate any

further economic growth. Instead, new reform impulses are needed to overcome traditional

production structures that are no longer efficient, internationally not competitive, and

unsustainable in environmental and social terms. Ukraine needs a structural change in order

to achieve a realigned, sustainable growth path.

2.2 Ukraine’s carbon record

Along with increasing international efforts to reduce GHG emissions, the average carbon

intensity of GDP has been falling in the EU-15 countries, the United States as well as in

China (EBRD 2011). Even previous transition economies in Europe and Asia, for example

Poland (World Bank 2011) and Kazakhstan (DIW econ 2012a), have drafted and

73 DIW econ (2013): “Assessing the innovation potential in Ukraine – Recent track record and implications for low-carbon development”. Low Carbon Ukraine – Technical Paper No.1.


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implemented ambitious programmes to decrease the carbon content of their GDP. Ukraine

on the contrary lags far behind these international developments.

With an aggregate GHG emission of 383 million metric tons of CO2 equivalent (UNFCC

2012a)74, Ukraine is placed among the twenty countries with the highest emissions worldwide

(European Commission 2011). Table 3 shows a comparison between CO2 emissions from

energy use (per unit of GDP) in Ukraine and other previous transition economies.

Table 3: Carbon intensity in selected Eurasian economies75, 2010

Ukraine Kazakhstan Russia Poland

Carbon intensity

(kg CO2 / $ of

GDP)

3.03 2.44 1.82 0.79

Source: own calculations

As illustrated in Table 3, Ukraine needs more CO2 emissions to produce one unit of GDP

than other countries in the region. This is all the more remarkable given the fact that

Kazakhstan and Russia are sizeable producers of oil and natural gas, which usually is

connected with high emissions from extraction operations. The carbon intensity of Ukrainian

exports is far above that of all other countries in Europe, East Asia and the Commonwealth

of Independent States (CIS) and is more than six times higher than world average (EBRD

2011).

The sectoral distribution of emissions in Ukraine is shown in Table 4. This is a preliminary

account, splitting total GHG emissions in Ukraine according to the major emitting sectors of

its economy. While a more detailed investigation of these sectors will be provided during the

course of the current project “Capacity Building for Low Carbon Growth”, this overview offers

a useful starting point.

More than half of total Ukrainian emissions are accounted for by fuel combustion in industries

and industrial processes as well as by the generation of electricity and heat production.

74 Value for 2010, excluding emissions from land use and land use change (LULUCF) (UNFCCC 2012a).

75 Carbon Intensity for 2010 in metric tons of Carbon Dioxide from energy use per thousand U.S. Dollars of GDP, 2005 prices and market exchange rates (EIA 2011).


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Among the industrial sectors, the majority of emissions (17.8 percent) stems from the metal

industry, followed by the chemical industry with 3.9 percent.

The extraction, transport and processing of oil, natural gas and coal constitute another major

source of emissions (13.3 percent). The transport and residential sector account for 10.4

percent of total emissions each. Out of the emissions in the transport sector, 75 percent are

attributable to the use of road vehicles, corresponding to 7.7 percent of total emissions.

Table 4: Green house gas emissions76 in Ukraine by sector, 2010

Sector CO2 equivalent (in

1000 metric

tonnes)

Percent of

total

emissions

Industrial processes and fuel combustion in industry 105 510 27.5

Industry: metals 68 278 17.8

Industry: chemical products 14 896 3.9

Industry: mineral products 9 323 2.4

Industry: other 5 743 3.4

Electricity and heat production 94 370 24.6

Production, transport and processing of energy

resources (oil, gas & coal) 50 842 13.3

Energy: natural gas fugitive emissions 19 814 5.2

Energy: coal mining 19 675 5.1

Energy: other 11 353 3.0

Transport sector 40 025 10.4

Transport: road vehicles 29 431 7.7

Residential sector 39 921 10.4

Other (incl. agriculture, waste) 52 513 13.7

Total 383 182 100.0

Source: UNFCCC 2012a, own calculations

76 All Greenhouse Gases included, emissions from LULUCF excluded.


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3. Towards low carbon growth in Ukraine

The alternative to the current carbon intensive growth in Ukraine is the adoption of an

innovative low carbon growth77 strategy. Low carbon growth strategies comprise two broad

sets of policies: (i) framework policies and (ii) sectoral policies. The implementation of such

policies necessarily implies the decoupling of energy consumption and GHG emissions from

economic development (Low Carbon Growth). Climate policies should be not regarded as a

burden to economic development but rather as a chance for further sustainable growth

opportunities. In fact, greening policies can induce many positive development outcomes

such as enhanced productivity and innovation, the creation of new jobs and markets as well

as fiscal revenue generation.

There are first signs that this awareness is starting to be reflected in Ukrainian policies.

Ukraine has already undertaken some first measures to green its economy (MEP 2006). One

example is the discussion of the introduction of an Emission Trading System (ETS), possibly

preceded by a carbon tax.

3.1 Framework conditions for low carbon growth

3.1.1 The role of the Ukrainian government


The main task for the government consists in redirecting market forces towards cleaner

production and investment. This is achieved by narrowing the cost gap between brown and

green technologies, by pricing in the costs of GHG emissions. Such measures include the

phasing out of unsustainable brown subsidies, reforming policies, redirecting public

investments and enforcing market-based mechanisms. As soon as the cost of brown

technologies exceeds the cost of clean technologies, investments in specific abatement

technologies will be more attractive yielding positive returns for investors.

The two major instruments for the government to price in GHG emissions in order to redirect

market forces towards low carbon investments are a carbon tax or the introduction of an

Emission Trading System (ETS).78

77 In general, low carbon growth refers to conventional economic growth at increased efficiency with respect to GHG emissions and the use of natural resources (DIW econ 2012).

78 A more detailed analysis of these instruments and their implementation possibilities is to follow in a

further policy paper in the course of the current DIW econ project “Capacity Building for Low Carbon Growth in Ukraine”.


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A tax on carbon emissions increases the cost of carbon intensive production and thereby

provides a financial incentive for firms and private investors to reduce GHG emissions. A

tax may institutionally be easy to administer in Ukraine, but determining the optimal tax

rate is not a trivial matter. Too low tax rates may not trigger any significant cuts in GHG-

emissions, while prohibitive tax rates endanger industrial competitiveness (NECU 2011).

In general, it is hard to reach a specific reduction target by using a tax on carbon.

At present, the Ukrainian government plans to introduce a cap-and-trade system for CO2

emission certificates. Trading systems, such as the European Union ETS, are based on

setting a maximum ceiling on emissions. Enterprises that emit less GHG than their cap

can sell unused emission allowances to firms that are likely to emit more carbon. Such a

carbon market does not require any further environmental standards to be enforced

since firms will seek to emit less GHG to avoid having to purchase more allowances. It

does, however, require sound economic judgment in setting the level of the cap (DIW

econ 2012b) and needs additional efforts to set up a market place for CO2.

Apart from increasing the relative price of dirty to clean technologies, innovation is crucial for

the realisation of low carbon growth. As Aghion et al. (2009) point out, “governments (...)

need to influence not only the allocation of production between clean and dirty activities, but

also the allocation of research and development between clean and dirty innovation.” In the

absence of government intervention to redirect technological development towards clean

innovations, innovations tend to be biased towards already existing dirty technologies

(Aghion et al. 2009). Hence an optimal policy combines carbon pricing (or carbon permits)

with strong support in clean-innovation R&D. In practice, these subsidies in R&D can be

financed through the receipts form carbon pricing.

In Ukraine, research and development is not sufficiently developed. From 2005 to 2011,

spending in R&D measured as a share of GDP decreased from 0.14 per cent to 0.08 per

cent (DIW econ 2012).79 However, Ukraine has a comprehensive network of higher

education institutes80 and possesses a rather well developed industrial base capable of

manufacturing complex machinery. These factors, in theory, form a sufficient basis for the

79

For a more detailed discussion on the innovation potential of the Ukrainian economy see DIW econ (2013): “Assessing the innovation potential in Ukraine – Recent track record and implications for low-carbon development”. Low Carbon Ukraine – Technical Paper No.1.

80 For example, Ukraine outscores other countries in the region, as well as France and the United Kingdom, on the 2011 education index compiled by the United Nations Development Programme (UNDP), which takes literacy and schooling years into account (UNDP 2011).


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development of domestic research in clean technologies. Hence there is a strong need for

the government to engage in the promotion of domestic research and development.

Possible measures are the promotion of cutting-edge scientific research in natural and

economic sciences and specific training aimed at developing new skill sets needed for green

jobs. This may be supported by administering specific research subsidies81. Policies should

also encourage the cooperation between enterprises, think tanks and universities in the

framework of a National System of Innovation (OECD 1997).

» To encourage private investment in clean technologies, public intervention is

indispensable. Public policies should combine measures that increase the

relative cost of dirty to clean technologies, e.g. through carbon pricing or the

introduction of an ETS, with direct subsidies in clean-innovation R&D.

3.1.2 The role of International Cooperation

In many sectors, private investment may be limited to financial constraints and may depend

on technology82 transfers from abroad. Fortunately there exist several possibilities of external

assistance (OECD 2012), for example within the framework of the UNFCCC or international

organisations. Since European, North-American and Asian companies currently operate at

the technology frontier with respect to GHG emission reductions, the Ukrainian economy

may profit significantly from technological spill over effects from abroad.

Some of the publically supported channels include:

The Global Environmental Facility (GEF), mandated by the Conference of the Parties to

the UNFCCC to support technology diffusion in developing and transition economies.

Projects include renewable energy, energy efficiency, sustainable transport, and

innovative financing initiatives (GEF 2010);

The Framework for Implementing Agreements, administered by the OECD and the

International Energy Agency (IEA), to share research on breakthrough energy-related

technologies and to assist with deployment programmes in member and non-member

states (IEA 2003);

81 Domestic research subsidies for green technology may, apart from accumulating domestic knowledge, also lower the final price of green products, or decrease their time to market. This in itself may have positive effects on the uptake of these technologies and thus on climate change mitigation (Acemoglu et al. 2012).

82 The term technology does not only refer to equipment, but also includes know-how and organisational methods suited to cutting emissions associated with particular economic activities (IPCC 2000).


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Technical assistance provided by foreign governments or the European Union, i.e. the

EU project PROMITHEAS aimed at fostering cooperation among research institutes and

universities of the Black Sea littoral states with a focus on renewable energies;

Multilateral financial institutions such as the European Bank for Reconstruction and

Development (EBRD) or the World Bank may give access to large scale loans. The

World Bank has been active in financing energy efficiency investments in the building

sector of Eastern European countries through targeted loans to its governments (World

Bank 2008). Similarly, the EBRD has been financing projects within its Ukrainian Energy

Efficiency Programmes (UKEEP).

To fully gain access to financial and technological transfers from abroad, a number of steps

are necessary. Firstly, the potentials of specific technologies to reduce GHG emissions as

well as their economic cost need to be assessed for all economic sectors within the

framework of Technology Needs Assessments (TNAs). Secondly, Ukraine may need to enter

into further commitments with multilateral financial institutions or foreign governments. Such

commitments may involve a firm assurance by the Ukrainian government to promote low

carbon growth policies and to set an ambitious reduction target in the level of GHG

emissions.

» In order to gain access to financial assistance and technology transfers from

abroad, Ukraine may need to enter into further international commitments and

to guarantee a more ambitious target in the level of emission reductions.

3.2 A sectoral policy mix

In the following section we discuss sector specific policy measures to be applied in the

emission-intensive sectors identified in Section 2.1. Following the structure of Table 4, these

sectors include the industry, energy, transport and residential sector and are listed in

decreasing order in terms of their share of total GHG emissions.

3.2.1 Industrial Sector

As illustrated in Table 4, industrial processes and fuel combustion in industry constitute the

highest share of emissions in Ukraine (27.5%). This is due to the fact that manufacturing

activity in Ukraine is dominated by energy-intensive steel production. The key reason for the

energy intensity is an ageing capital stock with outdated and inefficient production

technologies that remain in use across the entire region. Smelting one tonne of steel in


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obsolete open-heart furnaces in Ukraine consumes almost four times more energy than

smelting one tonne of steel in the European Union countries or China (OECD 2012).

Hence the industrial sector and in particular the metal industry present much potential for the

reduction of GHG emissions.83 This however can only be achieved if the capital stock,

especially outdated infrastructure and production capacities, is modernized. Promising

energy efficiency measures include the improvement of energy management systems, heat

recovery, the replacement of electric apparatus, improved cooling systems as well as the

replacement of furnaces and kilns in the metals and cement industries (UKEEP 2012).

In order to provide incentives to implement such technologies, regulatory standards for

production technologies should be tightened and coupled with reinforced penalties for their

violation.

» The main requirement for emission reductions in the industrial sector is the

improvement of energy efficiency. This implies the modernization of the capital

stock, especially of deteriorate infrastructure and outdated production

capacities.

3.2.2 Energy Sector

In order to put Ukraine on a low carbon growth path, much effort has to be directed into the

energy sector. The Ukrainian energy sector, especially the gas market, is characterized by

“dirty” technologies, high levels of inefficiencies and corruption, rent-seeking behaviour, and

misleading incentives by distorted prices.

3.2.2.1 Energy Resources: Oil, Natural Gas and Coal

Emissions in the energy sector mainly arise from the production, processing and transport of

oil, natural gas and coal. The bulk of emissions (78 percent) originate in equal parts from the

transport of natural gas and the mining of solid fuels, primarily coal. Both of these activities

offer substantial scope for the reduction of GHG emissions, for example trough the

modernisation and optimization of the gas transport system. Particularly promising measures

83 For a detailed discussion of low carbon growth potentials in the metal industry, see DIW econ (2012c): “Benchmarking for sustainable and economically viable technology options – The case of the metal industry in Ukraine”. Green Growth Policy Paper No. 2.


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include the reduction in greenhouse gas methane emitted from leakages in natural gas

pipelines (NECU 2010).

Apart from investments in infrastructure, the key of reducing GHG emissions in the energy

sector rests on encouraging market based competition. Specifically, we propose such efforts

to include:

Phasing out direct subsidies to coal mining (Handrich, Pavel and Naumenko 2009) and

phasing out economically unfeasibly low tariffs for natural gas consumers. Currently,

Ukraine‟s direct and indirect energy subsidies are the world‟s 8th largest in terms of

economic value (UNEP 2008). This has become a significant strain on the national

budget, a liability in relations with Russia as far as gas is concerned, and a major

deterrent to energy efficiency (Opitz 2010);

Restructuring of the gas sector through transparent regulation by independent

authorities, unbundling and demonopolisation in the gas transport and distribution as well

as in the oil and gas extraction sectors (Pavel and Poltavets 2005; Aslund and

Paskhaver 2010).

These policy measures will lead to an increase in the price of fossil energy, as advocated in

Section 3.1.1. Industries that rely on the input of fossil fuels will become less competitive,

while non-energy intensive industries, such as the agricultural sector, could profit. This brings

about the need for structural change and diversification of the Ukrainian economy. In an

international perspective, this will lead to changes in the comparative advantage of Ukraine.

Steel and other heavy industries will display decreasing volumes of production, leading to a

change in the pattern of foreign trade.

Apart from the structural change, Ukraine needs a stable and reliable macroeconomic policy

permitting firms to predict the change of energy prices. Only if policy makers ensure in a

credible way that the induced changes of relative energy prices are permanent, firms will

make long term investments into energy efficiency and clean technologies.

» The key to reduce GHG emissions in the energy sector lies in promoting market

based competition. This involves phasing out direct subsidies to coal mining,

phasing out unfeasible low tariffs for natural gas as well as the

demonopolisation of the gas transport sector.


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3.2.2.2 Electricity and Heat Production

The overwhelming majority of heat in Ukraine (97 percent) is produced by burning natural

gas. Natural gas also plays an important role in electricity generation with 8 percent of power

stemming from this source. The most important fuel for electricity production is domestic coal

(36 percent). Renewable energy sources, mainly large hydro stations, only generate 7

percent of electricity (IEA 2009).

The electricity and heat production sector is the largest fuel consumer in Ukraine after the

industrial sector. Emissions from the production of electricity and communal heat account for

about 25 percent of all GHG emissions in Ukraine (see Table 4). These emissions can

broadly be divided into two categories: (i) Emissions deriving from the combustion of fossil

fuels used for heat generation, (ii) emissions deriving from technical losses in heat and

electricity generation and distribution.

Emissions from losses in heat and electricity generation and transmission hinge to a large

degree on the state of current infrastructure and equipment (Pavel 2007). Both the natural

gas transmission and distribution infrastructure as well as the storage and gas-fired units for

district heating systems are in dire need for upgrade and renovation (IEA 2012).

The principal way to compel electricity companies and district heating providers to invest in

infrastructure improvements lies in liberalising utility tariff rates and improving regulation

(Pavel and Chukhai 2005). There is a strong need for removing subsidies for private gas

consumption and district heating systems and to adjust residential electricity tariffs to cost-

reflective levels (IEA 2012). These must include the capital and replacement costs.84

With respect to renewable energies, investments in wind power, biomass and photovoltaic

installations have experienced an increase recently (Trypolska 2012). Generous feed-in-

tariffs for solar and wind energy generation and an obligation for state companies to connect

new units to the grid, have given a boost to Ukraine‟s renewable energy development (IEA

2012). However, quantities are yet too small to account for an aggregate impact.

In order to further reduce Ukraine‟s dependence on fossil fuels, we propose to:

84 To minimise the social impact of these reforms, the tariff increases may be carried out in a

stepwise procedure (Opitz, Dodonov and Pfaffenberger 2004).


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Maintain the current system of feed-in tariffs guarantying access for electricity generated

from renewable sources to the national grid;

Clarify land rights, permit renewable energy installations for private households and

increase the capacity of the grid to include green electricity;

Support the construction of small biomass cogeneration plants in agricultural areas

through preferential loans in order to decrease emissions from heat production and

agricultural waste.

» Emission reductions in the heat and electricity sector are subject to the

modernization of the gas transmission system and the renovation of depreciated

heating equipment. These investments in infrastructure can only be induced if

subsidies for gas consumption are eliminated and electricity tariffs are increased

to full cost-recovery levels.

3.2.3 Transport Sector

Sectors with comparatively low carbon intensity, such as the transport sector, provide great

opportunities for emission reductions. With emissions accounting for 11 percent of total

emissions in Ukraine, the energy intensity of transport in Ukraine is lower than that of the EU-

27 average (UNECE 2010). However, this may change in future since incomes are growing

and car ownership is increasing (Ernst & Young 2012). The challenge for policy makers

consists in reducing present emissions and detaining future emissions from a potentially

growing sector.

Measures such as the successive implementation of fuel efficiency standards and fuel taxes

in the private transport sector may provide a starting point. These could be complemented by

investments in public transport modes and the modernisation of the railway, urban tram and

bus systems. With respect to road transport, improvements can be achieved by investments

in better road infrastructure and by supporting the implementation of electric, hybrid and fuel

cell electric vehicles (DIW econ 2011). However, more research on transport capacities in

Ukraine is needed to determine the ecological and efficiency gains of these policy options.

» Promising measures in the transport sector include the adoption of fuel

efficiency standards and taxes, the improvement of road infrastructure and the

modernization and expansion of the public transport system.


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3.2.4 Residential Sector

The residential sector offers great scope for improvement in energy efficiency, especially in

the private household sector. The increase of electricity and utility tariffs to cost covering

levels advocated in section 3.2.2.2 will give residents the incentives to save energy

(Meissner, Naumenko and Radeke 2012). They may start to engage in energy efficiency

investments such as heat containment in buildings through insulation of walls, windows and

roofs. This does not only improve energy efficiency, but also reduces Ukraine‟s dependence

on Russian oil and gas imports and creates jobs in the construction and handicraft sector.

A mix of measures that have been discussed in neighbouring countries with similar

residential structures may prove fruitful (Opitz 2003):

Enforce the deployment of metering and heat controls to supply residents with the tools

to control and reduce their energy consumption;

Improve the framework for the operation of Energy Service and Performance

Companies;

Sharpen the definition of residential property rights and support the formation of resident

associations as methods to share investment outlays and risks;

Advance the provision of financial support to households for energy efficiency

improvements, possibly through co-financing or support from multilateral financial

institutions (see section 3.1.2)

» With respect to the residential sector, we advocate giving private residents the

incentives and the tools to invest in heat containment and other energy

efficiency measures.

4. Policy Recommendations

This paper discussed the policy framework needed to enable investments in clean

technologies and outlined concrete steps to assist the Ukrainian government with the

implementation of a low carbon growth strategy. Low carbon growth strategies comprise two

broad sets of policies: (i) framework policies and (ii) sectoral policies. Both of them call for a

central role of the Ukrainian government.


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There is a dire need for the Ukrainian government to implement an effective regulatory

framework that increases competition and strengthens the efficiency of markets. Ideally,

public policy should combine measures that increase the relative cost of dirty to clean

technologies, for example through carbon pricing or the introduction of an ETS, with direct

subsidies into clean-innovation R&D.

With respect to sectoral policies, we recommend a specific policy mix aimed at the economic

sectors with the greatest potential for emission reductions. The most promising sectors

identified in this paper are the industrial sector, the energy sector including energy resources

and electricity and heat production, as well as the transport and residential sector.

1. The main requirement for emission reductions in the industrial sector is the improvement of

energy efficiency. This implies the modernization of the capital stock, especially of

deteriorate infrastructure and outdated production capacities.

2. The key to reduce GHG emissions in the energy sector lies in promoting market based

competition. This involves phasing out direct subsidies to coal mining, phasing out unfeasible

low tariffs for natural gas as well as the demonopolisation of the gas transport sector.

3. Emission reductions in the heat and electricity sector are subject to the modernization of the

gas transmission system and the renovation of depreciated heating equipment. These

investments in infrastructure can only be induced if subsidies for gas consumption are

eliminated and electricity tariffs are increased to full cost-recovery levels.

4. Promising measures in the transport sector include the adoption of fuel efficiency standards

and taxes, the improvement of road infrastructure and the modernization and expansion of

the public transport system.

5. With respect to the residential sector, we advocate giving private residents the incentives

and the tools to invest in heat containment and other energy efficiency measures.


Key policy steps


17

Literature

Acemoglu, D. et al. (2012): The Environment and Directed Technical Change. American Economic Review, 102(1): 131-66. Aghion, Philippe; Boulanger, Julian; Cohen, Elie (2011): Rethinking industrial policy. Bruegelpolicybrief, 2011/4. Aghion, Philippe; Hemous, David; Veugelers, Renhilde (2009): No green growth without innovation. Bruegelpolicybrief, 2009/7. Aghion, Philippe; Veugelers, Reinhilde; Serre, Clément (2009): Cold start fort the green innovation machine. Bruegel policy contribution, 2009/12. Aslund, A. and Paskhaver, O. (eds.) (2010): Proposals for Ukraine- 2010 Time for Reform, Independent International Experts Commission in Ukraine. CCAP (2005): Technology Transfer and Investment Risk in International Emissions Trading (TETRIS)- Joint Implementation and Emissions Trading in Eastern Europe, Report by the Center for Clean Air Policy. DIW econ (2013): Assessing the innovations potential in Ukraine – Recent track record and implications for low-carbon development. Low Carbon Ukraine, Technical Paper No.1. DIW econ (2012a): Sketching a Green Growth Strategy for the Republic of Kazakhstan, Green Growth Policy Paper No. 1. DIW econ (2012b): The Introduction of Emissions Trading in Kazakhstan, Green Growth Policy Paper No. 2. DIW econ (2012c): Benchmarking for sustainable and economically viable technology options – The case of the metal industry in Ukraine. Low Carbon Ukraine, Policy Paper No. 1. DIW econ (2011): Fuel Cells in Automotive Transport- Current Situation and Prospective Developments in Germany, Report for State Oil Company of Azerbaijan Republic (SOCAR). EBRD (2011): The Low Carbon Transition, Special Report on Climate Change by the European Bank for Reconstruction and Development. EIA (2011): Energy related carbon intensity, accessed at the US Energy Information Administration, www.eia.gov/cfapps/ipdbproject/IEDIndex3.cfm?tid=91&pid=46&aid=31. Ernst & Young (2012): The Central and Eastern European Automotive Market- Ukraine, www.ey.com/GL/en/Industries/Automotive/The-Central-and-Eastern-European-automotive-market---Country-profile--Ukraine. European Commission (2011): Joint Research Centre (JRC)/PBL Netherlands Environmental Assessment Agency. Emission Database for Global Atmospheric Research (EDGAR), release version 4.2. http://edgar.jrc.ec.europe.eu, 2011.


Key policy steps


18

GEF (2010): Transfer of Environmentally Sound Technologies - Case Studies from the Climate Change Portfolio of the Global Environment Facility.

Handrich, L.; Pavel, F. and Naumenko, D. (2009): Prospects for Ukraine‟s steam coal industry – high time for reform, IER policy papers, 09/ 2009. IEA (2012): Ukraine 2012 – Energy Policies Beyond IEA Countries.

IEA (2009): Electricity and Heat Statistics by Country, accessed at International Energy Agency www.iea.org/stats/electricitydata.asp?COUNTRY_CODE=UA. IEA (2003): International energy technology co-operation- International Energy Agency Implementing Agreements. IPCC (2000): Methodological and Technological Issues in Technology Transfer- A Summary for Policy Makers, Intergovernmental Panel on Climate Change Special Report. Meissner, F.; Naumenko, D. and Radeke, J. (2012): Towards higher energy efficiency in Ukraine- Reducing regulation and promoting energy efficiency improvements, German Advisory Group / IER Policy Paper, 01/ 2012. MEP Ukraine (2006): Ukraine’s report on demonstrable progress under the Kyoto Protocol, Ministry of Environmental Protection of Ukraine. NECU (2011): ПОРІВНЯЛЬНИЙ АНАЛІЗ ПОДАТКУ НА ВИКИДИ СО2 ТА СИСТЕМИ ТОРГІВЛІ ВИКИДАМИ: ВИСНОВКИ ДЛЯ УКРАЇНИ, Report by the National Ecological Center of Ukraine. NECU (2010): Problems of Ukraine‟s Coal Sector and Greenhouse Gas Emissions from Coal Mining and Consumption, Report by the National Ecological Center of Ukraine.

NERA (2012): Потреба в інвестиціях у зменшення викидів парникових газів: крива граничних витрат на зменшення викидів в Україні, Report prepared for the EBRD. OECD (2012): Green Growth and Environmental Governance in Eastern Europe, Caucasus, and Central Asia, OECD Green Growth Papers. OECD (2012): Financing Climate Change Action, overview and key messages. OECD (1997): National Innovation Systems, Report by the Organisation for Economic Co-Operation and Development. Opitz, P. (2010): Ineffizient und Intransparent: der Ukrainische Energiesektor, Osteuropa, 60 (2-4). Opitz, P.; Dodonov, B.; Pfaffenberger, W. (2004): How much do electricity tariff increases in Ukraine hurt the poor?, Energy Policy, Volume 32, (7). Opitz, P. (2003): Innovative approaches to finance energy efficiency projects in Russia, Commissioned paper to the ECEEE Summer Study.


Key policy steps


19

Pavel, F. (2007): Energy Price Shocks and Market Reforms: A quantitative Assessment, IER advisory papers, May 2007.

Pavel, F. and Chukhai, A. (2006): Household gas prices in Ukraine. How to combine economic and social requirements, IER advisory papers, December 2006.

Pavel. F. and Chukhai, A. (2005): Regulatory scheme for utilities: proposal for Ukraine? IER advisory papers, November 2005.

Pavel, F. and Poltavets, I. (2005): Ukraine‟s gas sector: Time for reforms, IER advisory papers, May 2005. Stern, N. (2008): The economics of climate change, American Economic Review: Papers & Proceedings, 98:2 –37. Trypolska, G. (2012): Feed-in tariff in Ukraine: The only driver of renewables‟ industry growth? Energy Policy 45 pp. 645–653. UKEEP (2012) Energy Efficiency Case Studies by the Ukraine Energy Efficiency Programme, www.ukeep.org/en/case-studies. UNDP (2011): Human Development Report 2011 - Sustainability and Equity: A Better Future for All. UNECE (2010): Financing Energy Efficiency Investments for Climate Change Mitigation, Report by the United Nations Economic Commission for Europe. UNEP (2008): Reforming Energy Subsidies- Opportunities to Contribute to the Climate Change Agenda, Report by the United Nations Economic Programme. UNFCCC (2007): Climate Change- Impacts, Vulnerabilities and Adaptation in Developing Countries. UNFCCC (2011): National greenhouse gas inventory data for the period 1990–2009, Note by the Secretariat of the Subsidiary Body for Implementation. UNFCCC (2012a): Greenhouse Gas Inventory Data by Party, accessed at unfccc.int/di/DetailedByParty.do. UNFCCC (2012b): GHG emission profiles for Annex I Parties and major groups. World Bank (2011): Transition to a Low Emissions Economy in Poland, The World Bank Poverty Reduction and Economic Management Unit. World Bank (2008): Financing Energy Efficiency- Lessons from Brazil, India, China and Beyond, Report No. 42529.


Key policy steps


20


Final Report

Appendix C-3: Green Growth Technical Paper No. 1

Appendix C-3

Assessing the innovation potential in

Ukraine

Low Carbon Ukraine – Technical Paper No. 1 (April 2013)


Final Report


Assessing the innovation

potential in Ukraine

Recent track record and implications for low-carbon

development

Low Carbon Ukraine – Technical Paper No. 1 (April 2013)

Project



Green Growth Technical Paper No. 1

iv

Contact:

DIW econ GmbH

Dr. Lars Handrich

Mohrenstraße 58

10117 Berlin

Germany

Phone +49.30.20 60 972 - 0

Fax +49.30.20 60 972 - 99

[email protected]

www.diw-econ.de




v

Table of contents


1. Introduction ..................................................................................................................... 1

2. Ukraine‟s innovation record over time and across sectors .............................................. 2

2.1 Inputs: R&D expenditures ......................................................................................... 2

2.2 Outputs: Patents and innovative products ................................................................. 3

3. Ukraine‟s innovation record in international comparison ................................................. 7

3.1 Inputs: R&D expenditures ......................................................................................... 8

3.2 Outputs: patents per capita ....................................................................................... 8

4. Domestic potential for innovative growth ........................................................................ 9

4.1 Research intensity of patents .................................................................................... 9

4.2 Patents and economic growth ................................................................................. 11

5. Conclusions ...................................................................................................................12



vi

Executive Summary


growth trajectory. This technical paper assesses the current innovation potential in Ukraine

and infers to what extent innovations contribute to economic growth.

We analyse input and output factors of innovation in Ukraine over the recent past and across

different economic sectors:

We find that expenditures in R&D have fallen at a rate of 7% between 2005 and

2011. Thus spending in R&D measured as a share of GDP decreases from 0.14% in

2005 to 0.08% in 2011.

Sectoral R&D funding fluctuates heavily over time and has declined across all

industrial sectors except for food processing between 2009 and 2011.

Despite decreasing expenditure in R&D, patent applications and registrations have

increased from 2009 onwards. This is due to the fact that the share of foreign patent

holders increased over the last years.

Innovative outputs show high volatility and sensitivity to business cycle downturns.

The share of innovative industrial production has contracted sharply by 40%

between 2007 and 2009 and has still not reached the pre-crisis levels by 2011.

The innovation intensity of output varies widely between industrial sectors, with some

small sectors showing substantial innovative capacity.

When comparing Ukraine with other benchmark countries we find that Ukraine is placed in

the middle field regarding the expenditure in R&D, spending a larger share of GDP on R&D

than Poland, Belarus or Kazakhstan. Compared to Russia, however, Ukraine would need to

increase R&D expenditure by a factor of 1.5. Measuring innovation by the number of

patents per capita Ukraine currently takes a place in the lower half among the

benchmark group, having 3 times less patented inventions per year, than Belarus or

Russia. The difference to the advanced economies such as the EU and the United States is

even larger.

Ukraine spends little R&D per patent. Most advanced economies spend more resources

per patent. In this regard, a low level of spending per patent may not be so much a signal of

efficiency, but rather an indication that the registered patent is not the result of prolonged

domestic innovative research.



vii

We evaluate the capacity of patented technology to induce economic growth and conclude

that growth of Ukrainian GDP was driven much less by R&D than in other nations,

implying that Ukraine‟s domestic capacity for a growth path driven by technological

innovation is still limited at the moment.

We conclude that the switch of the Ukrainian economy towards a low carbon economic

growth trajectory will require initially large transfers of technology from abroad. This should

be accompanied by efforts to increase domestic research capacity.



1

1. Introduction


growth trajectory85. This technical paper assesses the current innovation potential in Ukraine

as well as to what extent innovations contribute to economic growth. Firstly, innovations lead

to products and services with high value added. This in itself can raise GDP and improve the

economy‟s future capability for growth. Secondly, a focus on intensive growth through

innovation, rather than extensive growth through the accumulation of production factors,

stresses less the environment. The extent of intensive growth is also not limited by the

availability of finite natural resources. Thirdly, the realisation of sustainable low carbon

growth relies on the development and implementation of advanced green technologies, like

for example efficient methods of steel making. Such technologies can either be developed

domestically, or be imported from abroad. If these innovative products are produced

domestically, this will present additional sources of value creation and economic growth in

Ukraine.

Ukraine has undertaken some steps towards stimulating its innovation potential as outlined in

the “Strategy for Innovative Development of Ukraine”, adopted in 2009. This is supplemented

by the “Concept for reforming the government policy in the area of innovation until 2014”, as

well numerous policy initiatives that have identified strategic sectoral and regional priorities of

innovative development.

These steps indicate the awareness among policy makers of the importance of innovations

for economic growth in Ukraine. But it is yet too early to assess the impact of the recent

policy changes86. In the remaining part of the technical paper we evaluate Ukraine‟s current

track record and potential of innovation, rather than gauging the outcome of specific policies.

In order to accomplish that, we adopt three different perspectives. We first evaluate Ukraine‟s

track record of innovation over time, placing special emphasis on the evolution of innovation

in sectors of strategic importance to low carbon and innovative growth. Secondly, we

compare Ukraine‟s performance against a suitable international benchmark group of

countries. Finally, we appraise Ukraine‟s current domestic capacity for innovative growth.

85 See for example Aghion, Hemous and Veugelers (2009): No Green Growth Without Innovation. Bruegel Policy Brief 2009/07

86 For a qualitative assessment of the policies and institutions of the national innovation system, see United Nations Economic Commission for Europe (2013): Innovation Performance Review of Ukraine



2

2. Ukraine‟s innovation record over time and

across sectors

For assessing innovation we study inputs used in the research and development (R&D)

chain, and the outputs from that process. Input criteria primarily include spending on R&D.

Output criteria are registered patents, or the money value of innovative production.

2.1 Inputs: R&D expenditures

As shown in Figure 1, real spending in R&D in Ukraine has generally exhibited a downward

trend over the past years. Having reached a peak in 2006 by spending 910 million hryvnia

over all industrial sectors, expenditures have decreased to a value of 395 million hryvnia net

of consumer price inflation in 2011. This implies an annual decline of 7%87 for the years 2005

to 2011.

Figure 1: Real domestic spending on R&D in Ukraine 2005-2011, by industrial sector

Spending deflated by consumer price index, prices of 2005.

87 Given the relatively high rates of inflation in Ukraine, the calculation of real money values is sensitive to the choice of the price index used in deflating the nominal spending figures. If instead of the consumer price index, the official GDP deflator is used, compound annual growth rate will decrease to -11%.

0.00

0.05

0.10

0.15

0.20

0.25

0

100

200

300

400

500

600

700

800

900

1,000

2005 2006 2007 2008 2009 2010 2011

R&

D s

pe

nd

ing,

% o

f G

DP

Re

al R

&D

sp

en

din

g (m

io.

hry

wn

ja)

Others

Processing of

other Minerals

Food Processing

Metallurgy

Chemicals and Petrochemicals

Machinery amd Equipment

R+D spending, % of GDP



3

Source: State Statistic Committee of Ukraine. Calculations: DIW econ

The largest share of expenditure in R & D is held by the machinery and equipment industry.

Hence the development of expenditure is mainly driven by this sector. Between 2006 and

2011, expenditure in R&D in this sector reduced by 56%. Another large part is accounted for

the chemical and petrochemicals industry which reduced its expenditure by 28%. Only the

food processing industry increased their R&D expenditure - albeit from extremely low levels -

from 1.7 million hryvnia in 2005 to 10.9 million hryvnia in 2011, which implies a growth factor

of 6.4.

However, over the same time period, Ukraine also registered a rise in GDP, which has

moved contrary to the R&D spending. As shown by the line in Figure 1, this implies that R&D

spending relative to GDP has decreased over the period. Whereas in 2005 the amount

equivalent to 0.14% of GDP was spent for R&D, this share had fallen to only 0.08% of GDP

by 2011. Furthermore, R&D often requires long-term efforts, which are disrupted by strong

annual budget fluctuations. The latter is apparently the case in Ukraine.

In most innovative economies, a significant portion of R&D is spend at the firm level. The

proximity to market demands allows firms to develop products with a potential of being

commercially successful. Developing innovation at the firm level should therefore be a crucial

part of a national innovation strategy (UNECE, 2013).

2.2 Outputs: Patents and innovative products

Patents are often used as a proxy measure for research output. Patents represent an

inventor‟s recognised claim to the result of the research process, and therefore constitute

one step towards bringing innovative products to the commercial market. Figure 2 gives an

impression of the evolution of patent applications and officially granted patents in Ukraine

from 2006 onwards. The patents illustrated are on inventions only.



4

Figure 2: Patent applications and approvals in Ukraine, 2006-2011

Data: State Statistic Committee of Ukraine. Calculations: DIW econ

Despite decreasing R&D spending, the number of patent applications and patents

granted increased from 2009 onwards. Applications and grants move very closely over the

years implying an exceptionally high success rate of patent applications in Ukraine. Over the

six years observed, a cumulative total of almost 96% of applications were approved88. This

suggests that a large share of patents registered in Ukraine do not correspond to completely

new inventions, but rather represent a transfer of technologies that have already been

successfully patented in other countries.

Over the last years the share of invention patents held by foreign residents increased. While

in 2005, 37% were held by foreign patent holders, this share increased to 53% in 2011

(Figure 3). This might be the reason for a growing number of patent applications and

decreasing R&D spending at the same time.

88 In comparison, the USA exhibited a cumulative approval rate of only 41% over the same time period, whereas the corresponding figure for Germany is even lower at 34%.

0

500

1000

1500

2000

2500

3000

3500

2006 2007 2008 2009 2010 2011

Nu

mb

er

of

pat

en

ts

Patents applications

Patents granted



5

Figure 3: Share of invention patents held by domestic and foreign residents in Ukraine, 2008-2011

Data: WIPO. Calculations: DIW econ

Although patents are a useful measure of scientific output, they do not offer any information

on the economic value of the underlying inventions. A suitable metric of the economic value

of innovative output is the money value of innovative production. In absolute figures,

innovative production in industrial sectors (including extraction of natural resources) in

Ukraine amounted to 42 billion hryvnia in 2011. Figure 4 tracks this metric expressed as a

percentage of total output (GDP) over the past seven years, as well as displaying the

innovative contribution of key industry sectors to total GDP.

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2008 2009 2010 2011

Foreign residents

Domestic residents



6

Figure 4: Value of innovative industrial production in Ukraine as percentage of GDP 2007-2011, by industrial sectors

Data: State Statistic Committee of Ukraine. Calculations: DIW econ

As shown figure 4, the share of innovative industrial production has contracted sharply

during the downturn of the business cycle decreasing to 60% of its original share of GDP in

2009. Due to the fact that innovative production in the coke and oil refining sector has

experienced a remarkable upswing, total innovative industrial output remains at more or less

constant levels.

The coke and oil refining sector was the only sector able to expand its innovative production

during and after the crisis. Starting in 2005 when the share of GDP was at 0.16% it increased

to 1.25% in 2011, representing an innovative output that is 24 times higher in 2011. In

addition to that, the machinery and equipment sector as well as the metallurgy sector

decreased strongly from 2008 to 2011. Both sectors together have accounted for the bulk of

innovative production in the industrial sector during the past years.

Expressing the volume of innovative production in a sector as a share of total production in

that sector, we arrive at a measure of innovation intensity of output in a sector. This measure

is graphed in Figure 5. Clearly, the innovation intensity of output varies widely by sector.

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

2005 2006 2007 2008 2009 2010 2011

% o

f G

DP

Food Processing

Wood

Coke and Oil Refining

Chemicals and Petrochemicals

Metallurgy

Machinery and Equipment

Others



7

As expected, the coal and oil refining industries in particular as well as the machinery and

equipment industries produce a comparatively high percentage of innovative output. These

industries can accordingly be classified as highly innovative.

Figure 5: Share of innovative production in total sectoral production in key industrial sectors, 2011

* The value for the sector cut at 10% for better representation, complete value: 21.6%. Data: State Statistic Committee of Ukraine. Calculations: DIW econ

3. Ukraine‟s innovation record in international

comparison

This section puts Ukraine‟s innovation record into a comparative perspective by contrasting it

against an international benchmark group of countries. This group includes relevant peers

among the transition economies of Eastern Europe and the Commonwealth of Independent

States (CIS), Turkey and China, as well as the United Kingdom, Germany and the USA..

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

8.00

9.00

10.00

Shar

e o

f in

no

vati

ve o

utp

ut

in s

ect

or

ou

tpu

t (%

)



8

3.1 Inputs: R&D expenditures

In order to make R&D expenditures across countries comparable, we use data assembled by

UNESCO on harmonised Gross Domestic Expenditure on R&D (GERD), which includes

research outlays by private and public institutions and enterprises. Figure 6 shows the

relevant data for the total group of 12 countries.

Figure 6: Expenditure on R&D (GERD) as % of national GDP in 12 countries, 2009

Data: UNESCO, Calculations: DIW econ

Clearly, Ukraine needs to drastically increase its spending in R&D if it is to catch up with the

advanced economies. But in comparison to the other transition economies in this sample

Ukraine takes a middle place. If Ukraine were to catch up to the level of its neighbour Russia,

it would need to increase spending only by a factor of 1.5, whereas trying to achieve the

value of Germany would imply an increase by a factor of 3.3.

3.2 Outputs: patents per capita

Figure 7 displays the number of patents for invention as registered by the World Intellectual

Property Organisation (WIPO) per million inhabitants. Using this measure, Ukraine takes

only a lower place among the benchmark group. Thus in comparison to Russia or Belarus

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

Pe

rce

nta

ge o

f n

atio

nal

GD

P



9

Ukraine registers 70% less patents per million inhabitants and so the gap to the advanced

economies in Europe and North-America remains very large.

Figure 7: Patents for inventions per million inhabitants in 12 countries, 2009

* The value for USA cut at 800 for better representation, complete value: 1228 Data: World Intellectual Property Organisation (WIPO), Calculations: DIW econ

4. Domestic potential for innovative growth

This section assesses the potential of domestic Ukrainian R&D to create innovative growth.

Two links therefore need to be evaluated: firstly the capacity of R&D spending to generate

domestic innovation (measured by patents), and secondly the capacity of the innovation to

generate economic growth.

4.1 Research intensity of patents

Putting input and output indicators of innovation together, the R&D intensity of a patent,

which is the amount of spending necessary to trigger a single patent, can be derived for each

0.0

100.0

200.0

300.0

400.0

500.0

600.0

700.0

800.0

Pate

nts

per

mio

llio

n p

op

ula

tio

n



10

country. This is a measure of the capacity of research spending to create innovation,

sometimes referred to as the “efficiency” of R&D89. This metric is displayed in Figure 7.

Figure 8: R&D spending per patented invention in 12 countries, 2009

GDP in thousands of US dollar at purchasing power parity. Data: WIPO / UNESCO, Calculations: DIW econ

Using this measure, Ukraine is placed in the lower half of this sample of countries. Most

advanced economies spend more resources per patent. In this regard, a low level of

spending per patent may not be so much a sign of efficiency, but rather indicates that the

registered patent is not the result of prolonged domestic innovative research. This

interpretation would be in concordance with the assessment of the high success rate of

patent applications in Section 2.2: many patents registered in Ukraine may constitute partial

transfers of already established foreign technologies, which is a process that takes up

comparatively little domestic R&D spending. These the figures of patents do not primarily

present wholly original domestic research. However, the are no other data available, which

would allow a more precise assessment of domestic innovative capacity. Figure 9 presents

data on the place of residence of patent holders in Ukraine, which is the closest measure

89 See for example World Bank (2011): Igniting innovation: Rethinking the Role of Government in Emerging Europe and Central Asia. The authors calculate a similar measure, based on US Patent Office (USPTO), rather than WIPO patent data.

0

500

1000

1500

2000

2500

3000

3500

4000

Th

ou

san

d U

S -

$ a

t P

PP



11

available. As the graph shows, more than half of the patents filed in Ukraine come from

foreign residents. Only Hungary has a larger proportionally share of foreign patent holders

than Ukraine.

In Ukraine patents applications are not as dependent on expenditure in R&D because of its

large share of foreign patent holders. It is obvious that a large part of the expenditure in R&D

and the development of technology are made abroad.

Figure 9: Share of invention patents held by domestic and foreign residents in 12

countries, 2011

Data: WIPO, Calculations: DIW econ

4.2 Patents and economic growth

We now proceed to evaluate the effect of Ukraine‟s patents. In the context of a low carbon

economic growth strategy, the main purpose of patented technologies is to lead to resource

saving innovations that promotes growth. To this end, the capacity of patented technology to

induce economic growth is evaluated by comparing the correlation over time between

granted patents and GDP in six countries from the international benchmark group (Table 1).

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Domestic residents Foreign residents



12

Table 1: Strength of correlation between GDP and granted invention patents in selected countries, 2003-2011

Country Correlation coefficient

USA 0.985

Germany 0.916

Russia 0.903

UK 0.895

Poland 0.878

Ukraine 0.330

GDP at purchasing power parity, constant 2005 prices.

Data: WIPO. Calculations: DIW econ

The correlation coefficient can take on values between -1, which indicates a perfectly strong

negative relationship and +1, indicating a perfectly strong positive relationship between

developments in GDP and granted patents. The results show strong positive relationships in

all countries except Ukraine. This indicates that growth in Ukrainian GDP was driven

much less by patents than in other nations, implying that Ukraine‟s domestic capacity for

a growth path driven by technological innovation is still limited at the moment90.

5. Conclusions

This paper has investigated Ukraine‟s innovation record over time and provided an

assessment of Ukraine‟s potential to domestically generate innovation-driven economic

growth.

Generally, both input and output measures of innovation show no clear upward trend over

the last decade, even during Ukraine‟s remarkable phase of economic growth. Conversely,

industrial innovation output does seem to contract sharply in the face of business cycle

downturns. This may suggest that many enterprises still perceive R&D investments as being

a risky “extra” rather than an essential part of core business activity. Presenting businesses

with better risk smoothing mechanisms and more stable and more long-term financing for

90 The correlation coefficient does not specify the direction of causation (if any exists) between the two variables, so that it is technically possible that a higher GDP leads to more innovation and hence to more patents instead of the reverse direction. However, as patents are the outcome of a lengthy research process as well as a lengthy administrative registration procedure, it is unlikely that higher GDP leads of more patents within the same year. This means the chain of causation implied in this paper is the most probable one.



13

promising innovative research, may help to improve both the level as well as the resilience of

innovative output in Ukraine.

In the recent past we observe from the official statistics a rather worrying development in

Ukraine, as the share in innovative production of the usually as R&D intensive classified

sectors, primarily machinery and equipment and chemicals, has declined considerably. At

the same time the share of less R&D intensive sectors like coke and refineries started to

dominate the innovative output in Ukraine.

To counter this unfavourable development policy efforts need to be intensified in order to

diversify into sectors that display high innovation intensity and thus have a more a long

term outlook for development of greener technologies and low carbon economic growth.

From an international perspective, it is clear that Ukraine has not yet devoted as large a

share of its national income to innovation as relevant benchmark countries. This clearly

implies the need for Ukraine to significantly raise the volume of R&D spending if it is to

generate the capacity for domestic innovative growth in the future.

At present, the capacity for domestic innovative growth is constrained, as indicated by the

low research intensity of the patents registered in Ukraine, as well as the low capacity of

these patents to generate GDP growth.

Shifting the economy on a low carbon economic growth trajectory will require that Ukraine

initially relies on technology transfers from abroad. Once a large stock of modern

technologies is imported, this may help to stimulate domestic innovation and economic

activity. In parallel, domestic efforts to increase Ukraine‟s innovative capacity must continue

to be supported.


Final Report


Appendix C-4

The 2012 Doha Amendment to the

Kyoto Protocol: Implications and

Recommendations for Ukraine

Low Carbon Ukraine - Policy Paper No. 3 (July 2013)


Final Report


The 2012 Doha Amendment to

the Kyoto Protocol: Implications

and Recommendations for

Ukraine

Low Carbon Ukraine - Policy Paper No. 3 (July 2013)

Project


The 2012 Doha Amendment:

Implications and Recommendations for Ukraine


ii

Contact:

DIW econ GmbH

Dr. Lars Handrich

Mohrenstraße 58

10117 Berlin

Germany

Phone +49.30.20 60 972 - 0

Fax +49.30.20 60 972 - 99

[email protected]

www.diw-econ.de





iii

Content


1. Introduction ..................................................................................................................... 1

2. The Kyoto Protocol and its implications for Ukraine ........................................................ 1

2.1 Ukraine as a major beneficiary in CP1 ...................................................................... 1

2.2 The 2012 Doha Amendment and its implications for Ukraine .................................... 3

3. The case of ratification of the Doha Amendment ............................................................ 7

4. Policy Recommendation ................................................................................................. 9

References ...........................................................................................................................10

Endnotes ..............................................................................................................................11




iv

List of Abbreviations

AAU Assigned Amount Unit

CER Certified Emission Reduction

CP1 First Commitment Period

CP2 Second Commitment Period

ERU Emission Reduction Unit

EU European Union

FDI Foreign Direct Investment

GHG Greenhouse Gas

JI Joint Implementation

LULUCF Land Use, Land-Use Change and Forestry

PPP Purchasing Power Parity

QELRO Quantified Emission Limitation or Reduction Objective

UNFCCC United Nations Framework Convention on Climate Change




v

Executive Summary

The international climate negotiations in Doha at the end of 2012 resulted in the adoption of

an amendment to the Kyoto Protocol regulating the second commitment period (CP2) from

2013 to 2020. Although Ukraine joined the negotiation text with a 20 percent reduction target

for 2020, it indicated that it may decide not to ratify the Doha Amendment. This paper

outlines the implications of the new regulations for Ukraine and discusses the benefits of

participation in CP2.

During the first commitment period (CP1) of the Kyoto Protocol (2008-2012), Ukraine

significantly benefited from the financial opportunities available through the flexible

mechanisms. With more than 47 million sold assigned amount units and about 470 million

Euros received through emission trading, Ukraine was one of the major beneficiaries of CP1.

The regulations for CP2 restrict the quantity of emission allowances for a country to its

average emissions from 2008 to 2010 times eight. For Ukraine, this corresponds to emission

allowances of about 3.1 billion tons of CO2 equivalents for CP2 and to an average of about

0.39 billion tons of CO2 equivalents per year. Compliance with this ambitious reduction target

is only possible if Ukraine undertakes immediate structural reforms to fundamentally shift

away from its current carbon-intensive growth path towards significant improvements in

energy efficiency. Further active engagement in a Low Carbon Growth Strategy should

therefore be a focus of Ukrainian policy.

Despite the challenging emission target, the arguments in favour of participation in CP2

predominate. Participating in CP2 would foster Ukraine‟s political and economic integration

with the European Union (EU) which is of great importance for Ukraine considering its

interest in the association to the EU. Furthermore, it would increase the international

competitiveness of Ukrainian exports and represent an important step of preparation for a

post-2020 global climate framework.

Finally, Ukraine should consider engaging in bilateral agreements with the European Union

or South Korea to receive short-term financial or technological assistance in compliance with

the emission targets.




1

1. Introduction

Worldwide greenhouse gas (GHG) emissions reached a growth rate of 3 percent in the last

decade. Top emitters are China, United States, Brazil and India, but also Ukraine remains

one of the most carbon-intensive economies in the world. With a carbon intensity of more

than one metric ton of CO2 per thousand US Dollar91 (in PPP) compared to an EU-27

average of 0.27 metric tons of CO2 (EIA 2013), Ukraine has a significant potential for

reducing GHG emissions.

The Kyoto Protocol is the first international agreement with legally binding GHG emission

reduction obligations for its signatory parties. The first commitment period (CP1) lasted from

2008 to 2012. During the Doha meeting in December 2012, the Parties to the Kyoto Protocol

including Ukraine agreed to extend the Kyoto Protocol to the second commitment period

(CP2) from 2013 to 2020 and set the date of 2015 for the development of a successor

document to be implemented from 2020 onwards. Although Ukraine initially gave its written

consent to join CP2, it later indicated that it may decide not to ratify the Doha Amendment.

This paper assesses the implications of the amendment for Ukraine.

2. The Kyoto Protocol and its implications for

Ukraine

2.1 Ukraine as a major beneficiary in CP1

Classified as Annex B country92, in the first commitment period Ukraine had the obligation not to

exceed its GHG emission level of 1990. After the dissolution of the Soviet Union and during a

long recession Ukraine remained well below the set emission levels throughout CP1. In

2008, Ukraine‟s level of emissions was only 46 percent of 1990. Consequently, Ukraine

91 base year 2005.

92 with the status of being “undergoing the process of transition to a market economy”, UNFCCC

(1998): Kyoto Protocol to the United Nations Convention on Climate Change.

http://unfccc.int/kyoto_protocol/items/2830.php.




2

received an estimated surplus of assigned amount units (AAUs)93 of 2.6 billion tonnes of CO2

equivalents (Carbon Market Watch 2013). These surplus AAUs are often referred to as “hot

air” since the surplus was the result of weak targets rather than real emission reduction

efforts.

During the first commitment period Ukraine heavily relied on the flexible mechanisms, in

particular the Joint Implementation (JI)94 projects and the Green Investment Scheme (GIS)95.

Among the former Soviet Union countries, Ukraine has been the major beneficiary of the

flexible mechanisms: With 184 registered JI projects and 130 million issued Emission

Reduction Units (ERUs)96, Ukraine is the biggest supplier of ERUs (Thomson Reuters 2013).

Furthermore, from 2008 to 2012, Ukraine sold about 47 million assigned amount units,

turning Ukraine into the third largest seller of AAUs. The total amount of funds received by

Ukraine through the GIS during the first commitment period was about 470 million Euros

(National Ecological Centre of Ukraine 2012).

Hence, participating in the first commitment period has been clearly beneficial for Ukraine.

The funding provided through the flexible mechanisms opened up opportunities in attracting

foreign investments for the modernization of the national economy. This was particularly

important for the sectors lacking capital due to high risks or low financial returns.

93 “Assigned Amount Units (AAUs) are emission rights that were introduced under the Kyoto Protocol. One AAU allows a country to emit 1 tonne of CO2. Each country with an emission reduction commitment received AAUs that were equivalent to the number of tonnes it was allowed to emit during the Kyoto Protocol‟s first 5-year commitment period.” CCAP-Europe, CDM-Watch (2012): The Phantom Menace - An introduction to the Kyoto Protocol Allowances surplus. Policy Brief. July 2012. 94

“The mechanism known as “joint implementation”, defined in Article 6 of the Kyoto Protocol, allows a country with an emission reduction or limitation commitment under the Kyoto Protocol (Annex B Party) to earn emission reduction units (ERUs) from an emission-reduction or emission removal project in another Annex B Party, each equivalent to one tone of CO2, which can be counted towards meeting its Kyoto target. Joint implementation offers Parties a flexible and cost-efficient means of fulfilling a part of their Kyoto commitments, while the host Party benefits from foreign investment and technology transfer.” UNFCCC (2013), http://unfccc.int/kyoto_protocol/mechanisms/joint_implementation/items/

1674.php. 95

“The Green Investment Scheme (GIS) is a newly developed mechanism in the framework of International Emission Trade (IET). It is designed to achieve greater flexibility in reaching the targets of the Kyoto Protocol while preserving environmental integrity of IET. Under the GIS a Party to the Protocol […], can sell the excess of its Kyoto quota units (AAUs) to another Party. The proceeds from the AAU sales should be “greened”, i.e. channelled to the development and implementation of the projects either acquiring the greenhouse gases emission reductions (hard greening) or building up the necessary framework for this process (soft greening).”

http://archive.rec.org/REC/Programs/ClimateChange/green-investment-scheme.html 96

See endnote 94.




3

2.2 The 2012 Doha Amendment and its implications for Ukraine

At the Doha round in December 2012, the parties adopted an amendment to the original text

of the Kyoto Protocol regulating the second commitment period (see UNFCCC 2013a). The

amendment has not yet entered into legal force.

As listed in the amendment, Ukraine pledged to keep its GHG emissions 20 percent below

1990 levels in 2020 (see Figure 1) and offered a Quantified Emission Limitation or Reduction

Objective (QELRO)97 for the second commitment period of 76 per cent compared to the base

year 1990 (UNFCCC 2013a). This corresponds to approximately 707 million tons of CO2

equivalents per year excluding LULUCF98 (see Table 12). This represents an over 70 percent

increase from current emission levels and the least ambitious target of all post-2012 targets

proposed by Annex I countries of the UNFCCC (UNDP 2013). Furthermore, Ukraine

requested that there is no cancellation or limitation of the use of any of its assigned amount

units.99

Under the new regulations for CP2 the initial assigned amount, i.e. the number of AAUs a

country receives at the beginning of the second commitment period (Carbon Market Watch

2013), is restricted to a country‟s average emissions between 2008 and 2010. This implies

that emissions should be stabilized at a level corresponding to the period of the global

economic crisis which was accompanied by significant reductions in production and

correspondingly in GHG emissions.100 In Ukraine, emissions dropped from more than 420

million tons of CO2 equivalents in 2008 to about 365 million tons of CO2 equivalents in 2009

(see Figure 1). Furthermore, the amendment to the Kyoto Protocol involves the cancellation

of assigned amount units that exceed the number of AAUs equivalent to the average

emissions between 2008 and 2010 times eight101. The basic idea behind these strict

97 “The QELRO, expressed as a percentage in relation to a base year, denotes the average level of

anthropogenic carbon dioxide equivalent emissions of greenhouse gases […] that a Party […] would be allowed to emit on an annual basis during a given commitment period.” UNFCCC (2011): Issues relating to the transformation of pledges for emission reductions into quantified emission limitation and reduction objectives: methodology and examples. Revised technical paper. FCCC/TP/2010/3/Rev.1.) 98

Land use, Land-use change and forestry. 99

This request is expressed in the footnote accompanying Ukraine‟s quantified emission reduction target in the Doha Amendment: “Should be full carry-over and there is no acceptance of any cancellation or any limitation on use of this legitimately acquired sovereign property.” (UNFCCC 2013a)

100 The amendment does not specify any fines or penalties binding in the case that a party does not

meet its emission targets. 101

Doha Amendment, Article 3, paragraph 7: “Any positive difference between the assigned amount of the second commitment period for a Party included in the Annex I and average annual emissions for

the first three years of the preceding commitment period multiplied by eight shall be transferred to the cancellation account of that Party.” (UNFCCC 2013a) Following the interpretation of Carbon




4

limitations of the quantity of assigned amount units is to avoid the accumulation of new

surplus or new hot air as it was the case in CP1.

Table 12: Impact of Doha Amendment on Ukraine’s emission allowances

in kt CO2 equivalents excl. LULUCF

Base year GHG emissions 1990 929,894

Pledge 2020 (1990-20%) 743,915

QELRO: 76% of base year 706,719

Initial assigned amount 2013-2020 (76% of base year x 8)

5,653,753

Yearly Emissions

2008 421,261

2009 365,307

2010 383,211

Average 2008-2010 389,926

Share of level of emissions of base year 0.4193

De facto available AAUs 2013-2020: Average of (2008-2010) x 8

3,119,411

Yearly available AAUs if distributed uniformly 389,926

AAUs to be transferred to cancellation account (Initial assigned amount minus de facto available AAUs)

2,534,342

Source: UNFCCC 2013c, own calculations102

In Ukraine, average emissions of 2008, 2009 and 2010 amount to about 390 million tons of

CO2 equivalents excluding LULUCF103 (see Table 12). This corresponds to approximately 42

percent of the level of emissions in 1990. Following the Doha regulations and multiplying the

average emissions by eight (the number of years of the second commitment period), Ukraine

receives about 3.1 billion assigned amount units for the second commitment period (see

Table 12). The Doha regulations also imply - in contrast to Ukraine‟s request - the

cancellation of more than 2.5 billion AAUs that have to be transferred to the national

Market Watch 2013, we assume that “assigned amount” refers to “the number of AAUs a country receives based on the QELRO it submitted”, i.e. to the initial assigned amount which is fixed. For a detailed discussion on the difference between assigned amount and initial assigned amount see Carbon Market Watch 2013: “Doha decisions on the Kyoto surplus explained”.

102 Displayed values are rounded.

103 GHG emissions are presented excluding LULUCF following Article 3, Paragraph 7 of the Doha

Amendment: “[…] Those Parties included in Annex I for whom land-use change and forestry constituted a net source of greenhouse gas emissions in 1990 shall include in their 1990 emissions base year or period the aggregate anthropogenic carbon dioxide equivalent emissions by sources minus removals by sinks in 1990 from land-use change for the purposes of calculating their assigned amount.” (UNFCCC 2013a)




5

cancellation account and cannot be used for compliance with the emission targets (see Table

12).

Figure 1: Emissions, pledge 2020 and available AAUs for CP2 based on Doha Amendment

Data source: UNFCCC (2013c)

Although Ukraine disposes over a significant surplus of AAUs from the first commitment

period (see section 2.1), the Doha surplus rules104 prohibit the use of these excess units for

compliance in CP2 since Ukraine‟s CP2 emissions do not exceed its initial assigned

amount.105 In order to cover emissions that are above the 2008-2010 average, Ukraine would

therefore need to buy emission allowances from other countries.

104

Paragraph 25 of decision 1/CMP.8 (bold added): “Decides further that units in a Party‟s previous period surplus reserve account may be used for retirement during the additional period for fulfilling commitments of the second commitment period up to the extent by which emissions during the second commitment period exceed the assigned amount for that commitment period [...].” UNFCCC (2013b)

105 If on the contrary, CP2 emissions were higher than a country‟s initial assigned amount, there would

be no limit on how much of the CP1 surplus a country could use to comply with is CP2 target

0

100 000

200 000

300 000

400 000

500 000

600 000

700 000

800 000

900 000

1 000 000

GHG emissions (excl. LULUCF) in kilotons CO2 equ.

Level of GHG emissions in 1990 (excl. LULUCF)

Pledge 2020 (1990-20%)

Yearly available AAUs 2013-2020 (if distributed uniformly)

- 20% of 1990 emission level




6

In theory, Ukraine could also sell its CP1 AAU surplus to other countries in exchange for CP2

AAUs that can be used for compliance in the second commitment period. In practice

however, this option is ruled out since the potential buyers of excess quotas, i.e. Australia,

Japan, Liechtenstein, Monaco, Norway, Switzerland and the European Union declared that

they will not purchase any assigned amount units transferred from the first commitment

period to the second (see statements in Annex II of UNFCCC 2013b).

Hence de facto Ukraine is allowed to emit a total quantity of about 3.1 billion tons of CO2

equivalents in CP2. If distributed uniformly106 this implies emission allowances of about 0.39

billion tons of CO2 equivalents per year (see red line in Figure 1 for a graphical illustration).

This is an ambitious but not unrealistic emission target for Ukraine. If the policy measures

and the energy efficiency efforts set out in the new draft Energy Strategy107 of Ukraine are all

realized, GHG emissions would even reach a lower level than the one required by the Kyoto

regulations. An illustration of the assumptions under which Ukraine will be able to achieve

the Kyoto emission targets, will follow in Chapter 4 of the Third Project Report, where the

business-as-usual economic scenarios till 2020 and 2050 are developed.

Concerning the Joint Implementation mechanism the Doha round has not brought up a final

decision on its approval or adoption. A review of the guidelines is assumed to continue in

subsequent negotiating sessions under the Subsidiary Body of Implementation (SBI) (Carbon

Market Watch 2013). However, even in the unlikely case that the JI mechanism is continued

in CP2, it is questionable whether there would be any buyers of Emission Reduction Units

generated by the JI projects.

Given the conflicting targets pledged by Ukraine and set by the Doha Amendment, Ukrainian

policy makers need to weigh up whether or not to ratify the amendment.

(Carbon Market Watch 2013). In other words, if Ukraine set its QELRO to the level of its 2008-2010 average emissions, it could use its surplus AAUs from CP1 for compliance in CP2 and would without any problem achieve its emission target. For a detailed discussion of this option, see Carbon Market Watch 2013: “Doha decisions on the Kyoto surplus explained”. However, this alternative option may be difficult to implement politically.

106 Of course, Ukraine could also distribute its allowances non-uniformly or even non-linearly.

107 Ministry of Energy and Coal Industry of Ukraine (2012): Draft version of the updated Energy

Strategy of Ukraine till 2030. June 7, 2012. Original title: Оновлення Енергетичної стратегії України на період до 2030 р. Проект документу для громадських обговорень. 7 червня 2012 р. м. Київ.




7

3. The case of ratification of the Doha

Amendment

If Ukraine ratifies the Doha Amendment, it faces an ambitious emission target requiring

considerable efforts to achieve it. The biggest challenge is the predetermined short time

period. Only if Ukraine undertakes immediate structural reforms to turn around its current

economic model towards less energy consumption and significant improvements in energy

efficiency, compliance with the emission targets is realistic. This requires an economic

strategy for low carbon growth and implies substantial investment expenditures. However,

such reforms require some time until they can deliver first benefits.

In spite of the challenging new emission target, participation in CP2 is part of a much wider

context and has several advantages for Ukraine.

The integration process with the European Union (EU) is an official strategic goal of

Ukrainian policy and has already led to several political achievements:

Ukraine cooperates with the EU under the Eastern Partnership umbrella which aims

to accelerate political association and deepen economic integration between the EU

and the Eastern European partner countries (e.g. Armenia, Belarus, Georgia,

Moldova, Ukraine) (IEA 2012).

The EU and Ukraine have initialled an Association Agreement to further strengthen

political and economic cooperation between the two parties. While negotiations of

the agreement were launched in 2007, the signing of the agreement is planned for

the Eastern Partnership summit in Vilnius in November 2013 (EU 2012108).

Not participating in CP2 would imply a significant step backwards with regards to

Ukraine‟s political and economic integration with the EU and would dramatically weaken

their bilateral relationship.

Even if Ukraine decided not to ratify the Doha CP2 Amendment, it would still need to

engage in emission reduction policies due to other commitments:

108 European Union (EU) – External Action (2012): Information on the EU-Ukraine Association

Agreement. http://eeas.europa.eu/top_stories/2012/140912_ukraine_en.htm.




8

In February 2011, Ukraine officially acceded the European Energy Community

Treaty (IEA 2012)109. Under that agreement, Ukraine has undertaken the obligation

to implement a number of measures to reduce emissions from large combustion

plants until 2018 and to achieve a share of 11 percent of renewable energy in the

structure of gross energy consumption until 2020.

Within the context of the draft Updated Energy Strategy of Ukraine till 2030110,

Ukraine aims, inter alia, to reduce energy consumption in industries by 30-35 percent

until 2030 compared to the base year 2010 (Ministry of Coal and Energy Industry

2012).

International discussions on preventing climate change will continue and a gradual

increase of climate obligations will follow for all countries. Ukraine will therefore need

to prepare for the likely implementation of a post-2020 global climate framework.

Along with an increasing focus on sustainable development in other countries, Ukraine‟s

carbon intense exports potentially face increasingly difficult prospects. The tendency to

limit the access of carbon intensive products to markets may become a matter of survival

for Ukrainian exports to European markets. Not participating in CP2 may therefore imply

future higher trade barriers for Ukrainian products failing to satisfy “green and

sustainable” standards.

Finally, Ukrainian policy makers often argue that emission reductions restrict economic

growth and lead to negative impacts on the competitiveness of the economy. Indeed,

emission reductions require costly investments and thus, reduce short-term GDP growth.

On the other hand however, energy-efficiency investments stimulate demand for

machinery, engineering, construction services etc., which tends to increase GDP.

Moreover, the financing of costly investments can be facilitated through – and might even

initiate in the first place – foreign direct investments (FDI) and capital transfers from

abroad (for example through bilateral channels with the EU), which in turn increases

rather than decreases GDP. However, FDI and in particular foreign capital transfers will

require Ukraine‟s participation in Kyoto CP2.

109 The Energy Community Treaty constitutes the legal and economic framework for Network Energy

between the EU and a number of third countries to extend the internal EU energy market to Southeast Europe and beyond. http://www.energycommunity.org/portal/page/portal/ENC_HOME/ENERGY_COMMUNITY/Legal/. 110

See endnote 107.




9

To determine whether and to which extent the Kyoto emission targets will be achieved is not

a simple matter. A profound economic analysis is necessary which will also serve as a basis

for a Low Carbon Development Plan (see Chapter 6 of the Third Project Report). This is the

objective of the ongoing project “Capacity Building for Low Carbon Growth in Ukraine”.

4. Policy Recommendation

Considering the wider context and the potential benefits for Ukraine of participation in the

second commitment period of the Kyoto Protocol opting out is not recommendable. Although

reducing GHG emissions to the 2008-2010 level by 2013/2014 - as implied by the Doha

Amendment - constitutes an ambitious short-term target, the benefits of ratifying the

amendment predominate. Participation in the second commitment period would for example

foster Ukraine‟s political and economic integration with the European Union, increase the

international competitiveness of Ukrainian exports and represent an important step of

preparation for a post-2020 global climate framework.

However, big efforts are needed in order to achieve the emission targets. Ukraine needs to

fundamentally shift away from its current carbon-intensive growth path towards less energy

consumption and significant improvements in energy efficiency.111 This necessarily implies

the decoupling of energy consumption and GHG emissions from economic growth. Only if

Ukraine actively engages in a Low Carbon Growth Strategy to overcome inefficient und

unsustainable production structures, compliance with the GHG emission targets under Kyoto

is realistic.

Considering the immediate nature of the emission reduction obligations, Ukraine should

consider engaging in bilateral agreements with the European Union or other countries, e.g.

South Korea, to receive assistance in compliance with its emission targets. This assistance

could for example take the form of technology transfers facilitating short-term modernization

processes and energy improvements in the economy.

111 For a detailed discussion of the economic sectors and policy measures with the greatest potential

for energy efficiency improvements, see DIW econ (2013): “Towards a low carbon growth strategy for Ukraine: Key policy steps.”




10

References

Carbon Market Watch (2013): Doha decisions on the Kyoto surplus explained. Carbon

Market Watch Policy Brief.

DIW econ (2013): Towards a low carbon growth strategy for Ukraine: Key policy steps.

Project: Capacity Building for Low Carbon Growth in Ukraine. Low Carbon Ukraine -

Policy Paper No.2. April 2013.

International Energy Agency (IEA) (2012): Ukraine 2012. Energy Policies Beyond IEA

Countries.

Ministry of Energy and Coal Industry of Ukraine (2012): Draft version of the updated Energy

Strategy of Ukraine till 2030. June 7, 2012. Original title: Оновлення Енергетичної

стратегії України на період до 2030 р. Проект документу для громадських

обговорень. 7 червня 2012 р. м. Київ.

National Ecological Centre of Ukraine (2012): Review of funds expenditure obtained under

the international emissions trading in Ukraine.

Thomson Reuters Point Carbon (2013): Status of the Domestic Emissions Trading Scheme

in Ukraine. A discussion document for stakeholders in the PETER Project

(Preparedness for Emissions Trading in the EBRD Region), a project sponsored by

the European Bank for Reconstruction and Development (EBRD).

Ukrainian Nature and Conservation Society (2013a): Analytical Report. Problems of

determination of Ukraine‟s position on obligations for the second validity term of the

Kyoto Protocol. Project: Consulting services on economic analysis for low carbon

projects in Ukraine. Kiev 2013.




11

Ukrainian Nature and Conservation Society (2013b): Analytical Report. Status quo and

climate policy plans in Ukraine. Project: Consulting services on economic analysis for

low carbon projects in Ukraine. Kiev 2013.

United Nations Development Programme (UNDP) – Ukraine (2013): Capacity Building for

Low Carbon Growth in Ukraine. http://www.undp.org.ua/en/energy-and-

environment/35-energy-and-environment-/1351-capacity-building-for-low-carbon-

growth-in-ukraine.

United Nations Framework Convention on Climate Change (UNFCCC) (2013a): Doha

amendment to the Kyoto Protocol. Article 1: Amendment. Doha, 8 December

2012.

United Nations Framework Convention on Climate Change (UNFCCC) (2013b): Conference

of the Parties serving as the meeting of the Parties to the Kyoto Protocol on its eighth

session, held in Doha from 26 November to 8 December 2012. Addendum. Part Two:

Action taken by the Conference of the Parties to the Kyoto Protocol at its eighth

session. Advance Version. http://unfccc.int/resource/docs/2012/cmp8/eng/13a01.pdf.

United Nations Framework Convention on Climate Change (UNFCCC) (2013c): Greenhouse

Gas Inventory Data - Detailed data by Party. http://unfccc.int/di/DetailedByParty.do.

U.S. Energy Information Administration (EIA) (2013): International Energy Statistics,

Indicators, Carbon Intensity. http://www.eia.gov/cfapps/ipdbproject/IEDIndex3.cfm?tid

=91&pid=46&aid=31.


Final Report


1

Appendix C-5



options

Low Carbon Ukraine - Technical Paper No. 2 (August 2013)


Final Report


2

Benchmarking for sustainable

and economically viable

technology options

Selected industries in Ukraine

Low Carbon Ukraine - Technical Paper No. 2 (August 2013)

Project





iv

Contact:

DIW econ GmbH

Dr. Lars Handrich

Mohrenstraße 58

10117 Berlin

Germany

Phone +49.30.20 60 972 - 0

Fax +49.30.20 60 972 - 99

[email protected]

www.diw-econ.de





v

Table of contents

Executive Summary .............................................................................................................. vi

1. Introduction ..................................................................................................................... 1

2. The benchmarking approach .......................................................................................... 1

3. Benchmarking the non-metallic mineral products industry in Ukraine ............................. 3

3.1 Database .................................................................................................................. 3

3.2 Benchmarking methodology ..................................................................................... 5

3.3 Benchmarking results ............................................................................................... 8

3.4 Implications for the minerals industry of Ukraine ..................................................... 10

4. Benchmarking the chemicals and chemical products industry in Ukraine ......................15

4.1 Database ................................................................................................................ 15

4.2 Benchmarking results ............................................................................................. 16

4.3 Implications for the chemical industry of Ukraine .................................................... 20

5. Conclusions and outlook ................................................................................................22

References ...........................................................................................................................23

Appendix ..............................................................................................................................24




vi

Executive Summary

To determine green growth potentials in Ukraine a detailed sectoral analysis is necessary.

This includes assessing the economic viability and the environmental sustainability of the

different sectors. The focus of this paper is on the chemicals and chemical products industry

as well as on the non-metallic mineral products industry in Ukraine.

The presented international benchmarking approach identifies the countries that have the

best combination of sustainability and economic viability. That will take into account

comparing the performance of:


revenues (values),


Low levels of factor inputs like labour or energy use as well as other arising

production costs.

Based on detailed analysis of the structural characteristics of the industries, feasible peer

countries for Ukraine are identified. As a result, a technological yardstick allowing to quantify

the potential for reducing greenhouse gas emissions is determined for each sector. For the

non-metallic mineral products industry a full realisation of this potential would result in

abating 8.2 Mt of CO2 equivalents per year. For the chemicals and chemical products

industry our analysis shows that there is an emission savings potential of at least 1.3 Mt of

CO2 equivalents per year through technical improvement. The analysis also shows an

additional emission savings potential through scale adjustments. However, to identify this

potential further research is needed.




1

1. Introduction

Developing a low-carbon growth strategy requires an understanding of the mitigation

potential in the most relevant sectors of the economy. Therefore, we apply a sector-specific

analysis of mitigation potentials that takes into account economic viability as well as

environmental sustainability. The methodology applied to the chemicals and chemical

products industry and the non-metallic mineral products industry is the same methodology

we applied to the metal industry in Ukraine in Policy Paper No. 1112.

2. The benchmarking approach

The key objective of our benchmarking approach is to identify technology options for a given

industrial sector to best combine sustainability and economic viability. The yardstick for this

comparison is a balanced combination of:

High levels of desired outputs such as production volumes (in physical units) or

revenues (values),



The focus of the benchmarking approach is on technologies that are currently used in

practice, while theoretical solutions and technologies that are not yet implemented are not



In economic terms, the best combinations of desired outputs, undesired outputs and inputs

are considered to be efficient. Theoretically, efficiency levels of different technologies can be

measured as well as decomposed into different subcomponents related to technology, scale

and price levels (see Box 1). For practical applications, however, such a comparison is

strongly limited by the availability of data and relevant information. In particular, micro-level

benchmarking of different installations or companies is rather difficult and requires access to

112 DIW econ (2012): Benchmarking for sustainable and economically viable technology options, The case of

the metal industry in Ukraine; Low Carbon Ukraine - Policy Paper No. 1 (December 2012)




2

private and often confidential information. Alternatively, one can benchmark the same

industry across different countries. That way, detailed company- or even installation-specific

information is compensated by aggregate information from a range of countries, which is

more easily available. Such an international benchmark allows identifying the countries with

the most efficient technologies in use.


Efficiency is an economic concept which describes the optimal use of production factors in



inputs) and the specific goods such as steel, chemicals or food (henceforth outputs) which

are produced from these inputs. It is typically defined as either:



The highest-possible level of outputs that can be produced from a given set of inputs




Technical efficiency describes the ability of a firm to obtain optimal combinations of input

and output quantities;

Scale efficiency describes the ability of a firm to produce at optimal combinations of input

and output quantities while optimising all scale economies; and



In this analysis, efficiency will be measured in terms of technical efficiency and scale

efficiency.




3

3. Benchmarking the non-metallic mineral

products industry in Ukraine

This section provides the benchmarking approach for the non-metallic mineral industry in

Ukraine. The focus of interest is the relationship between the inputs used in the production

processes in different countries (i.e. labour, capital and energy) and the respective outputs in

terms of the gross output, greenhouse gas (GHG) emissions and non-metallic mineral

products. For ease of notation the non-metallic mineral products industry will be referred to

as minerals industry in the following.

3.1 Database

The two major sources providing data on the minerals industry in different countries are:


of scientific organizations with financial support of the European Union113, and

the National Inventory Submissions 2013, United Nations Framework Convention on

Climate Change (UNFCCC)114.

Additional data stems from

the Minerals Yearbook, United States Geological Survey (USGS) Mineral Resources

Program115, and

the SDBS Structural Business Statistics (ISIC Rev 3), Organisation for Economic

Co-operation and Development (OECD) 116

The databases of WIOD and OECD are broken down by various industries that are based on

the ISIC standard of the United Nations Statistics Division. The UNFCCC data base


114http://unfccc.int/national_reports/annex_i_ghg_inventories/national_inventories_submissions/items/

7383.php 115

http://minerals.usgs.gov/ 116



http://minerals.usgs.gov/




4

additionally contains detailed information about industrial products. The data of the USGS

Minerals Yearbook solely refers to mineral and mineral products.

With respect to the countries that are included in the international benchmarking approach,

our intention was to primarily cover technological leaders in the relevant sector. For the

present analysis 18 EU countries and 10 non EU countries are included in the data base (as

listed in Since the production data is not completely available for all countries, some of the

entries in Table 2 are left blank.

Table 2 below) for which the following information is available:

GHG emissions (in thousand tonnes of CO2 equivalent, source: wiod.org),

Energy Use, Emission Relevant (in TJ, source: wiod.org),

Gross Output (in millions of US dollars, source: wiod.org),



Total production of clinker (in kilo tonnes, source: UNFCCC, USGS),

Total production of glass (in kilo tonnes, source: UNFCCC, OECD),

Production of lime (in kilo tonnes, source: UNFCCC, USGS),

Production of soda ash (aluminium kilo tonnes, source: UNFCCC, USGS)

Ukraine is not included in the WIOD dataset therefore the data (gross output, energy use,

capital stock and persons employed) was gained from national sources.

Note that production data is not completely available for all countries. Nevertheless we can

use this sample of countries for a first assessment of the benchmark analysis. Since the

most recent information for all countries is available for 2007, this year is chosen as base

year for the benchmarking analysis.117

117 In fact, 2007 is a good choice for a base year since it is the last year before the start of the global

economic crises.




5

3.2 Benchmarking methodology

Under ISIC the minerals industry is described as “Manufacturing of other non-metallic

mineral products”.118 This includes among others the production of cement, glass and glass

products, ceramic products, lime, plaster as well as articles of concrete, plaster and cement.

For the structural analysis of the minerals industry we will focus on the production of clinker,

lime, glass and soda ash which henceforth is referred to as production:

Clinker is an intermediate product in the production of cement and is made of limestone

and clay or shale. When these raw materials are heated in the cement kilns, they are

formed into lumps or nodules which are called clinker. To produce cement, the clinker -

sometimes together with a small portion of calcium sulphate - is pulverized into fine

powder. This procedure is used to produce Portland and other types of hydraulic

cements.

Lime is calcium oxide or calcium hydroxide and is made out of limestone. The limestone

is heated in different types of lime kilns to decompose the carbonates. Inter alia it is used

as building and engineering material and as chemical feedstock.

Glass production can be divided into four major manufactured products: containers, flat

(window) glass, fibre glass, and specialty glass. The first two types are the most common

ones and are almost completely soda-lime glass. This glass is produced by melting

silicon dioxide, sodium carbonate, and lime with a small amount of aluminium oxide and

other alkalis and alkaline earth.

Soda ash production can be divided into the production of natural and synthetic soda

ash. The natural soda ash is produced from trona or sodium-carbonate-bearing brines

whereas the synthetic soda ash is produced by one of several chemical processes that

use limestone, salt and coal as feedstock. It is commonly used as raw material in glass,

chemicals, detergents, and other important industrial products.

Since the production data is not completely available for all countries, some of the entries in

Table 2 are left blank.

Table 2 gives a first impression of the performance of different countries in the minerals

industry. The first two columns refer to the sustainability (emissions per output) and the third

and fourth column to economic viability (output per capital input) of the production processes

118 ISIC Rev 3.1 division 26.




6

in the different countries.119 For ease of comparison the three top performers in each column

are shaded in grey. With respect to the sustainability (columns i and/or ii) Czech Republic,

Finland, Ireland, the Netherlands and Romania show top performance while Canada,

Romania, Russia, Ukraine and the United Kingdom are the top countries with respect to

economic viability (columns iii and/or iv) . As can be seen in Since the production data is not

completely available for all countries, some of the entries in Table 2 are left blank.

Table 2 the gap between Ukraine and the leading countries is significantly higher with

respect to sustainability as compared to economic viability.

Table 13: Comparison of capital and emissions intensities across countries, year 2007

2007 Emissions per

revenue



Volume of production per capital

stock

(tons of CO2-e per thousand

US-$)

(tons of CO2-e per ton of mineral product)

(US-$ per US-$)

(tons of mineral product per

thousand US $)

(i) (ii) (iii) (iv)

AUSTRALIA 1.08 0.83

AUSTRIA 0.85 1.15 1.42 1.05

BELGIUM 1.43 1.04 1.05 1.44

BRAZIL 1.56 0.94

CANADA 1.09 2.05

CZECH REPUBLIC 0.85 0.60 1.05 1.48

DENMARK 1.17 1.25 1.26 1.18

FINLAND 0.61 0.82 1.77 1.32

FRANCE 0.77 0.98 1.68 1.32

GERMANY 0.78 0.92 1.46 1.22

HUNGARY 1.48 0.97 1.03 1.56

INDIA 3.32 0.58

IRELAND 0.73 0.55 1.09 1.44

ITALY 1.07 1.13 1.00 0.95

JAPAN 0.81 0.85 0.69 0.66

SOUTH KOREA 1.30 1.33

NETHERLANDS 0.32 0.89 1.64 0.60

POLAND 1.41 0.97 1.52 2.21

PORTUGAL 1.34 0.88 1.13 1.73

119 For countries where data on production is not completely available, values for columns ii and iv

could not be provided.




7

ROMANIA 3.82 0.70 1.27 6.99

RUSSIAN FEDERATION 5.04 1.14 1.79 7.91

SLOVAKIA 1.33 0.88 1.72 2.58

SPAIN 1.35 1.29 1.23 1.28

SWEDEN 0.94 0.97 1.59 1.54

TURKEY 1.45 1.16

UKRAINE 4.41 1.26 1.09 3.80

UNITED KINGDOM 0.85 0.93 1.95 1.78

UNITED STATES OF AMERICA 1.65 1.57

Source: DIW econ based on wiod.org, UNFCCC, USGS,

OECD, State Statistics Service of Ukraine

However, the comparison of different indicators does not yet allow for deriving overall

conclusions. In fact, it must be emphasized that:

First, output can be measured as value or in physical quantities (i.e. in millions of Dollars

or in tons of output). However, minerals industries produce a range of different products

such as cement, lime and glass based on different production processes. Hence, a

feasible output measure must consider the relevant structural characteristics.

Second, the costs of production (inputs) do not only include capital but also other key

inputs such as labour and energy.

Third, the comparison of different indicators does allow the identification of the leaders in

each respective category, but not necessarily the identification of those countries that

perform relatively well in all categories. However, the objective of the benchmarking

analysis is to identify the best combinations of both, sustainability as well as economic

viability.

In order to determine the countries with the most-efficient combinations of inputs and outputs

(i.e. the most efficient technologies) we apply a specific empirical estimation technique, the

Data Envelopment Analysis (DEA). This is a well-established methodology for estimating

different efficiency measures (as described in Box 1 above) based on a large variety of

different input and output measures. For benchmarking the minerals industries, we consider

the use of capital, labour and energy as key inputs and gross output and emissions as

output.




8


Our benchmarking analysis of the minerals industry identifies the countries that operate at an

efficient scale and are able to produce the highest volumes of outputs with the lowest levels

of emissions from a given set of inputs (output-oriented efficiency measures of technical

efficiency und scale efficiency (see Box 1)). All efficiency estimates are given as indices

ranging from zero to one, where one stands for being efficient. For example, a technical

efficiency score of one for a given country of the sample indicates that in no other country

within our sample the minerals industry produces more outputs from the same combination

of inputs. Likewise, a technical efficiency score below one suggests that at least in one other

country the minerals industry is capable to produce higher outputs from the same inputs.

Similarly, a scale efficiency score equal to one indicates that the country‟s minerals industry

is producing at efficient scale while a score of less than one indicates that other countries are

better in utilizing scale economies.

Figure 43: Overall efficiency levels (technical efficiency & scale efficiency) of minerals industries in selected countries (in 2007)

Source: DIW econ

Figure 1 shows the outcome of the DEA regarding the overall efficiency levels (technical

efficiency & scale efficiency) of the minerals industries in selected countries. The results for




9

the technical and scale efficiency are shown in the appendix. The overall performance of the

selected countries is as follows:

In 8 of the 28 countries in the sample (Australia, Canada, Finland, France, Ireland,

Japan, the Netherlands and Slovakia) the minerals industry operates fully efficient.

These countries determine the technology frontier of the international minerals industry in

2007.

Among the inefficient countries, two different subgroups can be identified based on the

additional results for technical efficiency and scale efficiency as shown in the Appendix:

in Germany, the United Kingdom and the United States, the minerals industries are

technically efficient but operate at a too large scale (i.e., underutilization of available

production capacities), while

in Austria, Belgium, Brazil, Czech Republic, Denmark, Hungary, India, Italy, Korea,

Poland, Portugal, Romania, Russia, Spain, Sweden, Turkey and Ukraine, the

minerals industry is also technically inefficiency.

For all countries where the minerals industry does not operate at full efficiency, the analysis

provides insights for possible improvements. For example:

The overall efficiency level for the German minerals industry is estimated at 85% due to

operations at an inefficient scale. Likewise, overall efficiency of the British minerals

industry equals 95% due to inefficient scales of operation. This suggests that the

German industry could produce the same output at only 85% of its current scale (i.e. its

current input levels), whereas the British industry could reduce its current input levels by

roughly 5%.

The overall efficiency level for the minerals industry in the Czech Republic is estimated at

55% due to technical inefficiency (technical efficiency score of 0.99, see Appendix) and

inefficient scales of operation (scale efficiency score of 0.56, see Appendix). This

suggests that

the industry could produce the same output at only 55% of its current scale (input

levels), and

given operations at an efficient scale (input levels), output could be increased by 1%

(=1-0.99).




10

Ukraine only reaches a technical efficiency score of 0.85. In addition, it operates at a too

large scale (scale efficiency 0.65). Thus, overall efficiency only reaches 0.55. As can be seen

in Figure , Ukraine belongs to the low performers of the benchmark.

3.4 Implications for the minerals industry of Ukraine

The DEA identifies peer countries for each inefficient country. For Ukraine, Finland and the

Netherlands, which both operate fully efficient, are identified as peer countries. However the

applied DEA is fairly coarse as it does not take into account the structural characteristics of

the minerals industries of the countries. Hence, an additional approach to identify peer

countries is to analyze the output composition and to determine those countries as peer

countries that have a similar structure and are either overall efficient or at least technically

efficient.




11

Figure 44: Structural characteristics of the minerals industry in different countries

d) Output composition in kilotons

Source: DIW econ

b) Structure of minerals manufacturing

Source: DIW econ




12

The most relevant structural characteristics of the minerals industries across the different

countries are shown in Figure 41120. Figure 41 a) gives a first impression of the total output of

the non-metallic minerals production. All 21 countries shown in the figure produce clinker.

With the exception of the Netherlands all countries produce lime. Soda ash is only produced

by 10 countries (i.e. France, Germany, Italy, Japan, the Netherlands, Portugal, Spain,

Romania, Russia, and Ukraine).

More important than the total production output of the minerals industry is its structure

(Figure 41 b). Ukraine‟s output composition is made up of 63% of clinker, 26% of lime, 7% of

glass and 5% of soda ash. The only other countries that produce all 4 products are France,

Germany, Italy, Japan, Portugal, Spain, Romania and Russia. France, Germany, Romania

and Russia have a very similar output composition to the one of Ukraine, whereas the output

composition in Italy, Japan, Portugal and Spain is only slightly similar to the one of Ukraine.

The results of this comparison are summarised in Ошибка! Источник ссылки не найден.

Out of the group of countries with very similar output composition to the one of Ukraine (i.e.

France, Germany, Romania and Russia), France is overall efficient and Germany is

technically efficient. With respect to the slighter similar countries, (i.e. Italy, Japan, Portugal

and Spain), only Japan is overall efficient. All other countries identified as very similar or

slightly similar to Ukraine in terms of output composition are operating at an inefficient scale.

120 For Australia, Brazil, Canada, India, Korea, Turkey and USA no complete production data is

available, therefore they will not be part of the further analysis.




13

Table 14: Comparing the minerals industry of Ukraine with other countries

2007 Countries with a

structurally similar output composition

Efficiency score

(technical efficiency) (overall efficiency)

Austria 0.97 0.84

Belgium 0.96 0.95

Czech Republic 0.99 0.55

Denmark 0.99 0.97

Finland 1.00 1.00

France X 1.00 1.00

Germany X 1.00 0.85

Hungary 0.99 0.77

Ireland 1.00 1.00

Italy x 0.91 0.68

Japan x 1.00 1.00

Netherlands 1.00 1.00

Poland 0.93 0.74

Portugal x 0.95 0.60

Romania X 0.97 0.97

Russia X 0.92 0.87

Slovakia 1.00 1.00

Spain x 0.85 0.71

Sweden 1.00 1.00

United Kingdom 1.00 0.95

Key Strong similarity

Slight similarity

Source: DIW econ

The following countries come into consideration as peer countries for identifying sustainable

and economically viable technology options for the Ukrainian minerals industry.

Purely based on the efficiency benchmarking (DEA)

Finland,

Netherlands,

Based on the efficiency benchmarking (DEA) as well as on similarity of output structure

France,




14

Germany,

Japan.

Ошибка! Источник ссылки не найден.45 presents the indicators of emission intensity

(CO2-eq per volume of production) and economic viability (revenue per capital stock). The

reversed direction of the bars for emission intensity illustrates that emissions are an

undesired output.

Figure 45: Comparison of Ukraine with peer countries

Source: DIW econ

The countries identified as peer countries differ in their emission intensity and economic

viability, which is also caused by different structural characteristics. France and the

Netherlands show similar performances in economic viability but the Netherlands have a

lower emission intensity. Japan shows the worst performance with respect to economic

viability but has the second lowest emission intensity out of this sample of peer countries.

Finland shows the best performance in economic viability as well as in sustainability. With

exception of Germany, which is only technically efficient, all peer countries for Ukraine

operate fully efficient. In 2007, emissions per unit of production in the minerals industries in




15

Ukraine were 35% higher than in Finland, illustrating a great difference in the technology

levels between Finland and Ukraine in this sector. This shows that there is a very high

potential of saving emissions in Ukraine which would allow abating 8.2 Mt121 CO2 equivalents

per year.

4. Benchmarking the chemicals and chemical

products industry in Ukraine

A benchmark like the one implemented for the non-metallic mineral products industry can

also be applied to the chemicals and chemical products industry in Ukraine. The same

relationships between the inputs (i.e. labour, capital and energy) and the outputs (gross

output, greenhouse gas (GHG) emissions and chemicals and chemical products) are of

interest. For ease of notation the chemicals and chemical products industry will henceforth

be referred to as chemicals industry.

4.1 Database

As described above the two main sources providing data, now on the chemicals industry in

different countries are:


of scientific organizations with financial support of the European Union122, and

the National Inventory Submissions 2013, United Nations Framework Convention on

Climate Change (UNFCCC)123.

For the analysis of the chemicals industry 21 EU countries and 11 non-EU countries are

included in the database (as listed in Table 15) for which the following information is

available:

121 35% of 46 Mt CO2 equivalent emitted in the minerals industry in Ukraine in 2007.


123http://unfccc.int/national_reports/annex_i_ghg_inventories/national_inventories_submissions/items/

7383.php





16

GHG emissions (in thousand tonnes of CO2 equivalent, source: UNFCCC124),

Fuel combustion (in TJ, source: UNFCCC125),

Gross output (in millions of US dollars, source: wiod.org),



Unfortunately, there is no complete database on production data (physical output) for

chemicals or chemical products. The UNFCCC database provides production data for 28 of

the 32 countries on different chemicals. However, due to confidentiality it is incomplete. The

United States Geological Survey (USGS) Mineral Resources Program provides data on

Ammonia but no data for any other relevant chemicals. Alternative data sources are the

Eurostat Production of Manufacturing Goods (Prodcom) database126, the Eurostat Structural

Business Statistics (SBS)127 or the OECD Structural Analysis (STAN) database128. The

Prodcom database provides data for the 28 EU countries plus Iceland, Norway and Turkey

for different chemicals. The Eurostat SBS database provides data for the 28 EU countries

plus Albania, FYR of Macedonia, Norway and Switzerland on various industries that are

based on the statistical classification of economic activities. The STAN database provides

data for 32 OECD countries and various industries based on the ISIC standard. The last two

databases only provide data in monetary outputs. For all mentioned databases the problem

of confidentiality arises so that no representative database can be provided.


Due to the lack of detailed production data, a structural comparison of the sector is not

possible. Nevertheless it is possible to identify the efficient countries in a first step of the

analysis. Ошибка! Источник ссылки не найден. gives an overview of the performance of

the different countries in the chemicals industry. Because of the lack of production data there

is only one column for the sustainable performance (column i) and one for the economic

viability (column ii). In addition, the third column contains a ratio on emissions per energy



126 NACE Rev. 2 version http://epp.eurostat.ec.europa.eu/portal/page/portal/prodcom/data/database

127 Annual detailed enterprise statistics on manufacturing, NACE Rev. 1.1 D

http://epp.eurostat.ec.europa.eu/portal/page/portal/european_business/data/database 128

ISIC Rev. 3 version of STAN http://www.oecd.org/industry/ind/stanstructuralanalysisdatabase.htm




17

use. For ease of comparison the three top performers in each column are shaded in grey.

With respect to the sustainable indicator Italy, Slovenia and Sweden show top performance,

while China, France and Turkey are the best countries with regard to economic viability. The

lowest emissions per energy used are in Korea, Slovenia and the USA. The gap between

Ukraine and the top performers in the chemicals industry is fairly large.




18

Table 15: Comparison of different countries in the chemical industry, year 2007

2007 Emissions per

revenue Revenue per capital

stock Emissions per

Energy use

(tons of CO2-e per thousand US-$) (US-$ per US-$)

kilotons CO2-eq per TJ Energy

(i) (ii) (iii)

Australia 0.85 0.90 0.14

Austria 0.17 1.76 0.09

Belgium 0.30 1.67 0.09

Brazil 0.41 0.79 0.07

Bulgaria 2.40 2.21 0.10

Canada 0.41 2.11 0.10

China 0.79 3.73 0.07

Czech Republic 1.65 1.23 0.10

Estonia 1.30 1.73 0.16

Finland 0.40 1.79 0.20

France 0.19 3.96 0.09

Germany 0.21 1.80 0.07

Greece 0.44 1.76 0.09

Hungary 1.06 0.48 0.15

India 0.80 0.92 0.11

Italy 0.16 1.33 0.08

Japan 0.22 0.81 0.07

Korea 0.18 2.53 0.05

Lithuania 6.13 1.69 2.26

Netherlands 0.43 2.09 0.10

Poland 0.80 2.21 0.20

Portugal 0.52 1.58 0.10

Romania 2.96 1.82 0.13

Russia 1.45 1.38 0.25

Slovakia 1.32 2.21 0.12

Slovenia 0.11 1.31 0.06

Spain 0.23 1.60 0.07

Sweden 0.09 1.85 0.06

Turkey 0.18 3.09 0.22

Ukraine 1.83 1.06 0.12

United Kingdom 0.25 1.31 0.10

United States of America 0.38 1.84 0.05

Source: DIW econ based on wiod.org, UNFCCC,

State Statistics Service of Ukraine




19

Here it also occurs that the comparison of single indicators does not allow any conclusion on

the overall performance. Of interest is the ideal combination of sustainable performance and

economic viability. For this reason the DEA is applied again, defining capital, energy and

labour as key inputs and gross output and emissions as output. Figure 46Ошибка!

Источник ссылки не найден. presents the results of the DEA for the overall score.

Figure 46: Overall efficiency levels for chemical industries in selected countries (in 2007)

Source: DIW econ

The results of the DEA concerning the overall efficiency are shown in Figure 47Out of the 32

countries of the sample only four countries are overall efficient (i.e. Estonia, France,

Lithuania and Turkey). As can be seen in Figure 47 the technical efficiency scores are very

similar (with the exception of India all countries have a score above 0.9). Although Ukraine

has a score of 0.93 it still belongs to the lower third. This indicates that there still is a huge

potential for improvement regarding the technology level. The fairly low score of scale

efficiency is an indicator for a great underutilization of available production capacity in this

sector. The low scale efficiency of 0.30 leads to a low overall efficiency score of 0.28. (The

results of the scale efficiency can be seen in the Appendix)




20

Figure 47: Technical efficiency levels for chemical industries in selected countries (in 2007)

Source: DIW econ

4.3 Implications for the chemical industry of Ukraine

Since the chemical industry is a very heterogeneous industry, emissions per output are not a

useful indicator for the emission savings potentials. Therefore, the savings potentials are

calculated directly from the DEA. The DEA identifies Slovenia and Sweden as peer countries

for Ukraine. Both countries are only technically efficient because they operate at too large

scale (scale efficiency: Slovenia 0.95, Sweden 0.98). Nevertheless, both countries could be

used as peer countries for the technology levels.

The technical efficiency score of the chemical industry in Ukraine amounts to 0.93 and

indicates that given current input levels output levels need to increase by 7 percent to reach

technical efficiency. This implies an emissions reduction potential for the chemical industry in

Ukraine of around 1.3 Mt129 CO2 equivalents per year (see Ошибка! Источник ссылки не

найден.) which can be achieved through technical improvements for which Slovenia and

Sweden could serve as an example. The scale efficiency of 0.30 indicates that the savings

potential through structural adjustments amounts to 70 percent of the current input level.

Through improving the scale efficiency there is an even larger potential of saving emissions

129 7% of 19 Mt CO2 equivalent emitted in the minerals industry in Ukraine in 2007.




21

for the chemical industry in Ukraine which would allow abating 13.6 Mt130 CO2 equivalents

per year. This high reduction potential is the result of a fairly coarse DEA as it is based on

highly aggregated data. This entails that the chemical industries of the different countries are

treated alike, not taking into account the structural differences of the chemical industries.

This is in particular relevant for the manufacturing process of chemicals as, for example,

basic chemicals are very energy intensive. The determined emission savings potential of 7%

through technical improvement can be seen as a minimum reduction potential.131 The very

low scale efficiency indicates additional emissions avoidance potential through scale

adjustments. However, to quantify this potential we need to take into account the structural

differences of the chemical industry in a further, more detailed analysis.

Figure 48: Emissions saving potential for the chemical industry in 2007 in Gg

Source: DIW econ

130 70% of 19 Mt CO2 equivalent emitted in the chemical industry in Ukraine in 2007.

131 Note that relative to other countries in our sample, Ukraine is among the countries with lowest

efficiency score, i.e. highest potential for emission reduction (see Ошибка! Источник ссылки не найден.).




22

5. Conclusions and outlook

The developed international benchmark takes into account environmental sustainability and

economic viability. Thus, it is possible to not only identify countries that have a good

performance in single aspects of efficiency like emissions intensity or profitability, but also to

determine those countries that have the best combination of sustainability and economic

viability. The combined performance can be measured using the economic concept of

efficiency for a given industry in different countries and used for comparison. The structure of

the respective sector plays an important role in this process.

An even more detailed analysis of the sector especially concerning the subsectors and their

influence on the efficiency score should be carried out. Here it is necessary to establish a

representative database on chemical products. The development of the benchmark over time

should also be analysed.




23

References

Colli, Timothy j., et al (2005): An Introduction to Efficiency and Productivity Analysis. Second

Edition, United States of America: Springer


Greenhouse Gas Inventories http://www.ipcc-nggip.iges.or.jp/public/gl/invs1.html


Greenhouse Gas Inventories http://www.ipcc-nggip.iges.or.jp/public/2006gl/index.html

Organisation for Economic Co-operation and Development (OECD) (2013): SDBS Structural

Business Statistics (ISIC Rev 3), http://stats.oecd.org/Index.aspx?DataSetCode=SSIS_BSC

United Nations Framework Convention on Climate Change (UNFCCC) (2013): Annex I Party

GHG Inventory Submissions

http://unfccc.int/national_reports/annex_i_ghg_inventories/national_inventories_submissions/

items/7383.php

United Nations Framework Convention on Climate Change (UNFCCC) (2006): Updated

UNFCCC reporting guidelines on annual inventories following incorporation of the provisions

of decision 14/CP.11 http://unfccc.int/resource/docs/2006/sbsta/eng/09.pdf

United States Geological Survey (USGS): Mineral Resources Program: Minerals Yearbook,


World Input Output Database (WIOD) (2012): Environmental Accounts


World Input Output Database (WIOD) (2012): Socio-Economic Accounts


World Input Output Database (WIOD) (2012): Contents, Sources and Methods, Version 0.9 http://www.wiod.org/database/index.htm

http://www.ipcc-nggip.iges.or.jp/public/gl/invs1.html

http://www.ipcc-nggip.iges.or.jp/public/2006gl/index.html


http://unfccc.int/national_reports/annex_i_ghg_inventories/national_inventories_submissions/items/7383.php

http://unfccc.int/national_reports/annex_i_ghg_inventories/national_inventories_submissions/items/7383.php

http://unfccc.int/resource/docs/2006/sbsta/eng/09.pdf




http://www.wiod.org/database/index.htm




24

Appendix

Figure A1: Technical efficiency levels of minerals industries in selected countries (in 2007)

Source: DIW econ

Figure A2: Scale efficiency levels of minerals industries in selected countries (in 2007)

Source: DIW econ




25

Figure A3: Scale efficiency levels of chemical industries in selected countries (in 2007)

Source: DIW econ




26


Final Report


Appendix C-6

Towards ratification of the 2012 Doha

Amendment to the Kyoto Protocol by

Ukraine: The revised projections of

national GHG emissions

Low Carbon Ukraine - Policy Paper No. 4 (October 2013)


Final Report


Towards Ratification of the 2012 Doha Amendment by Ukraine:

The Revised Projections of National GHG Emissions


1

Towards ratification of the 2012

Doha Amendment to the Kyoto

Protocol by Ukraine:

The revised projections of national

GHG emissions

Low Carbon Ukraine - Policy Paper No. 4

(October 2013)

Project





2

Contact:

DIW econ GmbH

Dr. Lars Handrich

Mohrenstraße 58

10117 Berlin

Germany

Phone +49.30.20 60 972 - 0

Fax +49.30.20 60 972 - 99

[email protected]

www.diw-econ.de





3

1. The Challenge

The international climate negotiations in Doha at the end of 2012 adopted an amendment to

the Kyoto Protocol regulating the second commitment period (CP2) from 2013 to 2020. In

particular, emission allowances at the national level will be capped based on average

emissions from 2008 to 2010. For Ukraine, this corresponds to emission allowances of about

3.1 billion tons of CO2 equivalents or 0.39 billion tons per year (on average). The actual

GHG emissions in Ukraine and available assigned amount units (AAUs) for CP2 based on

the Doha Amendment are depicted in Figure 1.

Figure 2: GHG Emissions in Ukraine and available AAUs for CP2 based on Doha

Amendment

Source: UNFCCC (2013).

Policy makers in Ukraine worry that this cap on emissions will effectively limit the possibilities

for future growth of GDP. Thus, they currently consider not to ratify the Doha Amendment.

In July 2013, DIW econ put forward arguments in favour of ratification of the Doha

Amendment emphasising that it would be beneficial for Ukraine not to opt out (DIW econ,

2013). This paper provides additional evidence that with some political efforts, the CP2

0

100 000

200 000

300 000

400 000

500 000

600 000

700 000

800 000

900 000

1 000 000

19

90

19

92

19

94

19

96

19

98

20

00

20

02

20

04

20

06

20

08

20

10

20

12

20

14

20

16

20

18

20

20

GHG emissions (excl. LULUCF)

Yearly available AAUs 2013-2020 (if distributed uniformly)

Level of GHG emissions in 1990 (excl. LULUCF)

MtC

O2

e




4

emission target for Ukraine is feasible and economically reasonable. Thus, we recommend to

Ukrainian policy makers to ratify the CP2 Doha amendment.

The analysis of recent economic developments in Ukraine and of the latest GHG inventory

data shows that the emission cap as determined in the Doha Amendment does not impose a

barrier for future economic growth to Ukraine. On the contrary, it can be expected that even

under Status Quo developments – that is, in the absence of any further policy interventions –

national GHG emissions will exceed only the allowed amount of emissions induced by the

CP2-cap. More precisely, given the Status Quo, we estimate that the Ukrainian GHG

emissions on average will exceed the CP2-cap by just 1.3% per year during the commitment

period 2013-2020. However, if Ukraine manages to fully utilise its estimated abatement

potential at the cost level of up to 40 Euros per ton, Ukrainian GHG emissions will clearly

remain on average by 6.3% per year below the CP2-cap. The corresponding estimations are

illustrated in Figure 2 below.

Figure 2: Available AAUs for CP2 (Doha Amendment) and estimated GHG Emissions in

Ukraine

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2. Analysis

The analysis of future GHG emissions rests on two key assumptions:

The expected yearly levels of GDP growth until 2020; and

The intensity of GHG emissions per unit of GDP until 2020.

2.1 Expected yearly levels of GDP growth until 2020

Expectations on future economic growth in Ukraine until 2020 have been strongly revised

during the past two years. For example, as of April 2011, the IMF expected average growth

rates of at least 4% for Ukraine (IMF, 2011). Recently, however, this optimistic projection has

been substantially revised. In its most recent outlook as of October 2013, the IMF expects

growth rates of only 0.4% for 2013 and less than two percent until 2018 (IMF, 2013).

Assuming a rather high level of GDP growth of 3% for 2019 and 2020, the revised GDP

forecast implies that GDP grows from 2011 to 2020 by an annual average of only 1.7% (as

compared to 4.2% based on the previous forecast). The initial and revised outlooks are


Consequently, the significant drop in expected growth translates into lower expected

amounts of GHG emissions relative to the forecasts of previous years.

Figure 3: Expected yearly levels of GDP until 2020: Outlook of 2011 vs. outlook 2013.

(In constant 2007 national currency units.)

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Source: IMF, World Economic Outlook (WEO).

2.2 The intensity of GHG emissions per GPD until 2020

At present, Ukraine remains one of the most emission intensive countries of the world with

emissions per unit of GDP more than three times higher than average level in OECD Europe.

Hence, there is still a significant potential for further reductions of Ukraine‟s emission

intensity. Following the report by NERA (2012), the assumed development of GHG

emissions per unit of GDP would be as follows:

Under Status Quo (SQ) developments, NERA expects the ratio of GHG emissions

per unit of GDP to decrease by an average of -1.5% per year between 2011 and

2020.

In its Enhanced Policies (EP) scenario, which considers utilisation of all abatement

potential at costs of less than 40 Euros per ton, NERA expects the ratio of GHG

emissions per GDP to decrease by an average of -2.9% per year over 2011-2020.

2.3 Expected national GHG emissions: new adjusted estimations

Applying the expected development of emission intensity to the revised GDP forecast, the

expected total Ukrainian emissions are adjusted downward, as already presented in Figure 2

(page 2).

As a result, under Status Quo developments (when no additional policy efforts are made and

current institutions continue as they are now) national GHG emissions will be only slightly

higher than AAUs imposed by the CP2: on average, national emissions exceed the CP2-cap

by 1.3% per year during 2013-2020. Nonetheless, with some political efforts (i.e.

implementation of current plans to reform the wholesale electricity market) it would be easy

to get below the CP2-cap. Moreover, if Ukraine manages to fully utilise its estimated

abatement potential at costs of up to 40 Euros per ton, national emissions will clearly remain

below the CP2-cap between 2013 and 2020 (by 6.3% on average per year).

2.4 Costs of reaching the 2012 Doha Amendment

According to the adjusted emissions expectations under Status Quo scenario, the cumulated

GHG emissions (when summed up over 2014-2020), will exceed the 2012 Doha Amendment

allowances by total amount of 38 MtCO2e. These emissions are represented by the shaded

area in Figure 4 (which actually depicts an enlarged view of the Figure 2).




7

In order to reduce the national emissions by this amount, some additional political efforts and

investments, which depart from the Status Quo toward the Enhanced Policies scenario,

would be needed.

Multiplying the obtained emissions amount by the maximal price at 40 Euro per ton CO2e

(NERA, 2012), results in 1.53 billion Euro of total investments, which will be needed over the

next seven years in order to keep to the newly imposed emission cap. This implies that with

additional investments into technological modernisation of on average 219 million Euro (or

0.2% of GDP) per year until 2020 the requirements of the 2012 Doha Amendment could be

achieved by Ukraine.

Figure 4: Abatements needed to keep with requirements of the Doha Amendment

3. Conclusions

The presented analysis shows that the emission target imposed by 2012 Doha Amendment

for the second commitment period from 2013 to 2020 is achievable with some additional

political efforts and economically reasonable for Ukraine. Requiring yearly investments of

0.2% of GDP, the new target is achievable even under the current limitations in financial

markets or difficult situation in Ukraine‟s state budget. The target will not even trigger serious

structural changes within the economy. On the other side, the resulting improving overall

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energy efficiency of the economy and reducing emission intensity of GDP would promote

growth in targeted sectors and increase competitiveness of domestic products and services.

Additional benefits, listed by DIW econ (2013), emphasise the obtained conclusions and

strongly favour the ratification of the 2012 Doha Amendment by the Ukrainian side.

4. References

DIW econ. (2013). The 2012 Doha Amendment to the Kyoto Protocol: Implications and

recommendations for Ukraine. Project: Capacity Building for Low Carbon Growth in

Ukraine. Low carbon Ukraine – Policy Paper No.3. July 2013.

IMF. (2011). World Economic Outlook Database. April 2011.

IMF. (2013). World Economic Outlook Database. October 2013.

NERA. (2012). The demand for greenhouse gas emissions reduction investments: An

investor’s marginal abatement cost curve for Ukraine. Prepared for EBRD. January 2012.

London.

UNFCCC. (2013). Greenhouse gas inventory data – Detailed data by Party. Retrieved from

http://unfccc.int/di/DetailedByParty.do


Final Report


Appendix C-7

MRV and linking a potential ETS in

Ukraine with other systems

Low Carbon Ukraine - Policy Paper No. 5 (May 2014)


Final Report


MRV and linking a potential ETS

in Ukraine with other systems


(May 2014)

Project


Project

Version: 28. October 2015

MRV and linking a potential ETS in Ukraine

with other systems


iv

Contact:

DIW econ GmbH

Dr. Petra Opitz

Mohrenstraße 58

10117 Berlin

Germany

Phone +49.30.20 60 972 - 11

Fax +49.30.20 60 972 - 99

[email protected]

www.diw-econ.de

DIW econ GmbH

Dr. Ferdinand Pavel

Mohrenstraße 58

10117 Berlin




with other systems


v

Table of contents

Executive Summary .............................................................................................................. 1

1. Introduction ..................................................................................................................... 3

2. Fundamentals of linking ETS .......................................................................................... 4

2.1 Credibility of the system ............................................................................................ 5

2.2 Stringency of targets ................................................................................................. 5

2.3 Price regulation measures ........................................................................................ 7

3. The special importance of MRV ...................................................................................... 8

3.1 Challenges for MRV .................................................................................................. 9

3.2 Main demands on an MRV system ......................................................................... 10

4. Potential advantages and disadvantage of linking ETS .................................................11

5. Conclusions ...................................................................................................................12


with other systems


1

Executive Summary

Although the question of a future linking of a potential emission trading system (ETS) in

Ukraine with other ETS is currently more of hypothetical matter, some of the fundamentals

of an ETS, like for example Monitoring Reporting and Verification (MRV), are relevant

today for Ukraine anyway. That is because Ukraine takes part in international climate

change regulations and negotiations in upcoming new rules and instruments.O n the other

hand, Ukraine has adopted a revised Energy Strategy until 2030 which aims at increasing

energy efficiency in all sectors of the economy as well as supporting the use of renewable

energies.

Some of the fundamentals of linking an ETS outlined in this paper are therefore essential

for cooperation in international climate change framework as well as for the

implementation of national climate change and energy policies and strategies.

There are at least two main fundamentals for both linking and international cooperation to

ensure achieving the goals and targets of national strategies and policies:

Credibility, and

Stringency of targets.

The creation of a reliable system of monitoring, reporting and verification by the

government is essential for these fundamentals. MRV is key for:

Ensuring greater transparency, accuracy and compatibility of information with regard

to climate change, energy efficiency etc. in order to identify good practice, foster a

learning process, and allow for international benchmarking










The current MRV system in place in Ukraine needs to be substantially improved not only

for a potential ETS but also for monitoring implementation of other GHG reduction

policies and measures like the carbon tax or the Energy Strategy 2030.


with other systems


2

The MRV system should always be as robust and ambitious as feasible in order to be

most useful for domestic purposes of MRV, but also to address international

requirements at the same time. To establish two parallel systems for domestic and

international purposes would be highly inefficient.

Respective MRV guidelines and rules should be in accordance with guidelines and rules

of major potential emission trading partner countries.

As an MRV system is quite complex it needs strong coordination capacity between

national and subnational entities. Co-ordination and communication between regulators,

industry and verifiers through workshops or permanent working group proved to be very

helpful.

Due to the fact that a future ETS linking may generate advantages as well of

disadvantages both should be analysed in advance before making a decision on linking.


with other systems


3

1. Introduction

The implementation of the Kyoto Protocol in 2005 can be seen as a major driver having

created global carbon markets, which are shaped by different instruments. The trade in GHG

emissions allowances can take place among governments as well as among companies.

While the Kyoto Protocol defined precisely the emission trading between governments,

emissions trading on the company level evolved independently from it. This paper deals only

with the latter, i.e. systems allowing for trading of emissions on the company level only. The

term of “Linking” is treated as a full direct connection of existing emissions trading systems132

allowing non-restricted bi- or multilateral trading.

In 2003 the EU set up an emissions trading system (ETS) on the company level, which is

based on installations. The system is, in fact, a linked system as in 2007 the systems of

Norway, Liechtenstein and Iceland, non-members of the EU, had been linked to the EU ETS.

In the US and Canada regional and state-level emissions trading systems had been

launched on the East Cost (Regional GHG Initiative –RGGI), on the West Coast (The

Western Climate Initiative – WCI) and the Midwestern GHG Accord (MGGA).

During the last years a “mushrooming” of national, regional and sub-national ETS is being

observed. Switzerland, New Zealand as well as Australia implemented national trading

schemes. China and Japan are testing regional and local trading regimes. Among the FSU

countries, Kazakhstan is so far the only country which has set up an emissions trading

scheme which started operating in 2013. First trading actions very carried out in 2014. Rules

for this ETS are still being adjusted.

The International Carbon Action Partnership (ICAP) was set up in 2007 to provide a forum for

discussion and exchange of experiences on ETS and opportunities for linking.

(https://icapcarbonaction.com/)

For any linking with already existing systems, of course a well experienced ETS which has

proved its efficient functioning needs to be in place. As for Ukraine, currently no further steps

have been undertaken to implement an ETS. Instead, the actual political discussion is

focussing on implementation of economic incentive for GHG emission reductions by

introducing a CO2-Tax, or in fact, to raise the level of the currently very soft tax in place to

increase the real incentives for emission reduction measures. .

However, some of the fundamentals of an ETS, like for example the MRV are relevant for

Ukraine in any case. We outline below why the Government of Ukraine should implement

132 An indirect linking is achieved by approval of certificates from Kyoto flexible project mechanisms

(CDM, JI) for compliance within an existing ETS. For example, this has been the case in the EU ETS, as the EU Commission‟s „Linking Directive“ shows.

https://icapcarbonaction.com/


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today an MRV-System which today already takes into consideration the requirements for a

potential future linking of emission trading systems..

We outline, what would be the main fundamentals for an ETS in Ukraine to be developed

and implemented in the future and which would be the advantages and the disadvantages of

linking emission trading systems.





2. Fundamentals of linking ETS

For Ukraine are many basic principles which are crucial for linking an ETS of great

importance, even without an ETS in place yet. This is especially so, as Ukraine takes part in

international climate change regulations, negotiations and perhaps in upcoming new rules

and instruments. Furthermore, Ukraine has adopted a revised Energy Strategy until 2030

which aims at increasing energy efficiency in all sectors of the economy as well as

supporting the use of renewable energies.

There exists a wide range of different designs of ETS. The specific design of an ETS

depends on policy objectives and economic fundamentals of a given country. An ETS is a

quantity based instrument. Prices for carbon depend on shortages of emission allowances,

i.e. by setting a cap on emissions. But, in addition to achieving a certain target level of GHG

emissions an ETS is considered to be an efficient instrument to prevent climate change in

the long run. In case of the EU ETS, it is expected that shortages of allowances and trading

would lead to carbon prices high enough to stimulate long-term technological change and to

prevent technology lock-in effects. Thus, expectations towards emissions trading are

focussing both on static and dynamic efficiency of the instrument under climate change

aspects.

Systems which are planned to be linked do not necessarily need to be identical. However,

they should be compatible. The following criteria of system design are considered important.

Not taking them into account might create barriers for ETS linking.


with other systems


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2.1 Credibility of the system

The credibility of the system is crucial as it ensures that set reduction goals will be achieved

in reality. One ton of CO2equ under regulation in one system needs to be equal to one tone in

the other system. This holds also for national policies in order to achieve their goals and

targets.

MRV.

Each linked scheme must have credible MRV standards, which are robust and

guaranteeing the system‟s integrity. A credible emissions inventory should be the basis.

Existing MRV requirements under the Kyoto Protocol could provide respective guidance

and ease harmonization of MRV provisions.

Enforcement of compliance.

Confidence needs to be built concerning the rules implemented in the system in order to

achieve a high degree of compliance. Otherwise the ecological effectiveness of the

system with strong compliance enforcement would decrease. Therefore, existing

sanctions are a pre-condition for efficient linking.

Offset standards and types.

Offsets should be recorded by comparable standards in order to assure that reductions

from offsets are measured the same way. The common use of the Kyoto CDM and/or JI

standards would be helpful but standards could also be agreed bilaterally or multilaterally

respectively.

In case some credits are only eligible in one system (like f.ex. REDD credits in US

schemes) and not in the other (like f.ex. credits from land use are currently not

recognised in the EU ETS) that will affect the overall amount of units and therefore the

scarcity and price of carbon. In addition, in case offsets are considered non-eligible due

to low ecological credibility, the linking would harm integrity from this point of view. An

example is credits from HFC-23 which are banned in the EU trading system.

2.2 Stringency of targets

Stringency depends heavily on the prioritised policy objectives under which an ETS has been

set up. It influences scarcity and prices as well as ambitions and efforts. Comparability of

stringency is therefore crucial as well.

In order to create real shortages a cap or an emission reduction target should be set in order

to lead to real emission reductions compared to business as usual.. That does not mean that

caps need to be identical, but instead, they need to be adequate. Differences in types of

caps - absolute caps versus relative (carbon intensity based) caps do not, in principle, forbid


with other systems


6

linking but make it politically very difficult. The issue might be managed by implementing a

“gateway” that avoids net transfers from schemes with relative targets to the other system.

But such an approach would cause considerable transaction costs and therefore seems not

very realistic.

Setting an appropriate cap on emissions

In order to assess whether a cap is adequate the level of overall economic development

of a country as well as economic growth patterns, population growth and available

abatement potential needs to be taken into account. With this regard it might be easier to

estimate the appropriate cap for linking the ETS with countries in transition – FSU.

Burden sharing.

Different caps might be accepted f a burden sharing is agreed, as it is the case with the

EU-ETS. However, the respective caps should lead in the end to a shortage of

allowances.

Offsets.

A link between different ETS will indirectly extend the availability of offsets to all linked

schemes. The amount of offsets allowed for compliance in each of the linked systems

should not vary to a large extend, as offsets lower the burden for internal emission

reductions within the industries participating in a national system and therefore soften the

cap and lower the ambitiousness of the whole system. In addition, some sectors for

offsets may need to be considered. In some countries, for example, forestry and

agriculture provide huge offset potential which may not be accepted by other systems.

Banking and borrowing.

Linking effectively extends the most generous banking/borrowing rules to all other

schemes. Thus, unused allowances in a certain period from a scheme not allowed for

banking could be used for compliance in a system which allows for banking and hence

create a surplus in the following period also for the system without banking. That may

lead to reduced incentives for investment into new technologies. Borrowing may lead to

deferring and perhaps later abandoning of mitigation measures and could raise future

compliance cost and that would as well affect the system which does not allow for

borrowing.

Trading periods.

Systems may have defined different trading periods and thus caps may be set in different

times and for different periods of time. For example the third trading period of the EU

ETS lasts 7 years while in Australia the cap is defined for each separate year five years

in advance. It is feared that the cap in one system would be relaxed other system due to


with other systems


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economic growth or other measures so that the demand for certificates would increase

and so would the price.

Treatment of new entrants and installation closure.

Different allocation schemes.

Both, the free allocation or auctioning do not create barriers for the environmental

integrity of the linked systems. However, in linked systems changes in allowance prices

of one ETS could have distributive effects on the other depending on the allocation

method.133

Different points of regulation.

Upstream (producer and importer of fossil fuels) versus downstream (emission producing

facilities) coverage and direct (emission producing facilities are liable) versus indirect

emissions (entities trading goods with embedded emissions are liable). Linking is

possible in principle but efforts need be undertaken to avoid double counting in case two

systems with different points of regulation should be linked.

2.3 Price regulation measures

If a minimum price is established in one of the linked system systems, arbitrage trader will

buy or sell certificates in the other, non-regulated system, until prices in both systems level.

However, cost containment measures aimed to limit compliance costs, would be an

important obstacle if existent in only one of the systems. Under non-limited trade between

both systems a maximum price implemented in one system will also be valid for the other

system as permit holders in the system without the price cap would be able to buy unlimited

credits from the system with the cap. Special provisions would be needed between such

systems to ensure that the environmental effectiveness of the system without a cap is not

unduly affected.

Effects depend on level of price at the “price maker” market, the larger market. If the price in

that market is lower than in the “price taker” market with a price cap, the cap would not be

reached. If the price in the “price maker” market is higher than the price cap in the other

market with a price cap, that might create an incentive for the regulators of the capped

smaller market to lower the overall cap on allowances. That would lead to less stringent

targets and thus decrease the environmental effectiveness of the system and damaging

credibility.

133 In case grandfathering or benchmarking, sellers in a high-price ETS and buyers in a low-price ETS

lose, while buyers in a high-price ETS and sellers in a low-price ETS win. See: Ch. Flachsland et. al. (2008). Developing the international carbon market. Linking options for the EU ETS, Potsdam Institute for Climate Impact Research, p.19


with other systems


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3. The special importance of MRV

Monitoring, reporting and verification are crucial for the credibility of an ETS in order to create

mutual trust. It needs to ensure that emissions are in fact comparable and “a ton is really a

ton”. But also for a carbon tax or any other policy aiming at quantitative results a monitoring

and reporting system needs to be in place.

Monitoring, reporting and verification are key elements for:

Ensuring greater transparency, accuracy and compatibility of information with regard to

climate change, energy efficiency etc. in order to identify good practice, foster a learning

process, and allow international benchmarking






It is worth noting that a national MRV system should always be as robust and ambitious as

feasible in order to be most useful for domestic purposes of MRV and to address

international requirements at the same time. To establish two parallel systems for domestic

and international purposes would be highly inefficient.

Ukraine has already gained experiences with MRV by implementing and verifying Joint

Implementation projects within the frame of the first phase of the Kyoto Protocol. These MRV

requirements under the Kyoto Protocol could provide respective guidance for setting up a

comprehensive national MRV system. In addition, under the UNFCCC Ukraine is reporting

on overall GHG emissions levels and submits annual GHG emissions inventory data

consisting of the national inventory report (NIR) and common reporting format (CRF) of all

Parties included in Annex I to the Convention. However, greenhouse gas (GHG) inventories

are an essential part of a national MRV system, but not a substitute because information

provided by an MRV system is supposed to serve as the basis for planning and

implementing policies and measures at national level and tracking impacts of such activities.

Therefore, for an ETS as well as for the implementation of a CO2-tax the measurement and

for monitoring of the implementation of the Ukrainian Energy Strategy until 2030, reporting

and verification of greenhouse gas emissions in Ukraine needs to be substantially improved.

Also in the EU-ETS it became evident that the MRV system set up in 2004 for the first trading

period of the EU-ETS had to be improved over time. EU-ETS MRV guidelines were revised


with other systems


9

in 2007 and in 2012 updated rules for monitoring, reporting and verification have been laid

down in a new Monitoring and Reporting Regulation (MRR) and in the Accreditation and

verification Regulation (AVR).134 The EU-Commission is now developing and publishing new

guidance and templates in support of the regulations for Phase III aiming at improving

harmonization and cost-effectiveness of application of the regulations in all Member States.

3.1 Challenges for MRV

In many cases data availability is a major challenge for MRV. That is not only due to little

interest on detailed GHG data in the past when such a requirement was not an issue of

accountancy and company reporting; but also due to lacking determination on which

emission sources are considered and which types of entities are regulated. Different

emission trading systems may vary concerning the entities regulated by the system. The EU

ETS is based on the regulation of installations. However, within the Kazakh ETS for example,

companies are subject of regulation.

The availability of reliable and consistent data is not only an essential basis for MRV but also

for the cap-setting process.

In addition, conformity is also a challenge, mainly as an aspect of reporting and verification.

Conformity assessment demonstrates that products, services and processes fulfil

requirements of relevant norms, standards, legislation or technical specifications and that

they are reliable according to their quality and safety.

As the complexity of an MRV system is huge it needs strong coordination capacity between

national and subnational entities and institutional gaps and insufficiencies need to be

overcome. This is a lesson which has been learned from implementation of the Kazakh

national ETS. Co-ordination and communication between regulators, industries and verifiers

through workshops or permanent working groups are very helpful.

If prior to ETS a carbon tax system exists conflicts may arise from different behaviour of

operators. In a tax system operators tend to under-report emissions as that would potentially

lower the tax burden. In contrast, the allocation via grandfathering (based on historical

emissions) provides an incentive to over-reporting as higher amounts of allowances at the

very beginning of an ETS would lower the burden.

Experiences in Kazakhstan show that in addition to the above mentioned challenges also

coherent rules and templates for verification and rules for accreditation of verifiers are

necessary. While under UNFCCC reporting rules no verification of inventories and emission

reports is necessary, and the number of verifications for offset projects (JI projects in

134 http://ec.europa.eu/clima/policies/ets/monitoring/index_en.htm


with other systems


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Ukraine) was limited, verification of emission reports of all entities participating in an

emission trading scheme needs a substantial number of available accredited verifiers. That

implies the creation of verifier competences also at the national level and setting up

respective training schemes and incentives.

3.2 Main demands on an MRV system

Monitoring, reporting and verification needs to be based on sound, clear and approved rules.

Respective guidelines need to be elaborated and approved as well. Monitoring and reporting

needs to be split from verification in order to avoid vested interests.

Robustness, transparency, consistency and accuracy are main requirements for an effective

monitoring and reporting of greenhouse gas emissions. For linking of ETS the harmonisation

of existing MRV systems is required in order to create mutual trust.

In the report on “Data needs for the planning and modelling of low carbon policies”, prepared

by Thomson Reuters in December 2013 for the project “Capacity Building for Low Carbon

Growth in Ukraine”, the evolution and adjustment over time of the MRV system in the EU

ETS was described in detail and recommendations have been provided for implementation of

an MRV system in Ukraine.

The Partnership for Market Readiness (PMR) as well has outlined the main requirements for

monitoring of GHG emissions which are considered well defined and do not need any

amendment. Therefore, these outlines will not be repeated in this paper.

However, some more general requirements need to be considered from the very beginning:

Capacity thresholds for monitoring and reporting need to correspond to capacity

thresholds of entities under regulation. It is recommended to regulate large point sources

with low data uncertainties.

The coverage of activities of an MRV system should correlate with the activities

regulated under a certain policy, be it an ETS or any other policy or measure.

The robustness of a MRV system is crucial as otherwise there might be an incentive to

underreport annual emissions. Underreporting operators would benefit because they

would have to surrender less allowances. The necessity for ex-post corrections of

emission data will lead to price volatility and therefore to less confidence of market

participants.

Monitoring plans and emission reports are key instruments of an MRV system.

As the harmonisation of MRV standards based on best practice is desirable in order to

ensure the environmental effectiveness of the linked systems as well as market


with other systems


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confidence and efficiency it is recommended to set up the MRV system from the very

beginning in line with MRV systems of other ETS most likely to be linked to in the future.

In order to meet the requirements coherent and appropriate regulations for monitoring,

reporting and verifications need to be in place.

To overcome institutional gaps a coordination mechanism between governmental

departments needs to be established which coordinates the involvement of the needed range

of organisations needs to be involved in the measurement process, e.g. companies,

industrial operators, government departments and research institutions and reporting and

verification procedures.

4. Potential advantages and disadvantage of

linking ETS

With a proper framework set up by the government private companies will substantially

benefit form linking the ETS and international cooperation.

There is common sense in scientific literature and also empirical evidence is that an

appropriate linking of ETS may create the following basic advantages:

Increase of cost efficiency by enlarging the market size and thus the abatement

opportunities. Allowance prices will be equalised trough trade. Thus, price convergence

over time and reduction of competitive distortions will be achieved.

Some modelling results for emission trading under conditions without market

imperfections have shown that cost savings for trading between asymmetric countries

(i.e. developed and less-developed economies) are higher than in case of trade between

more similar countries. Cost savings might be up to 50-75%.

Increase of market liquidity und decreasing volatility of the market.

Unification of the level playing field for companies under carbon restrictions and avoiding

competitive distortions and carbon leakages between the companies and countries

covered by linked systems.

Lowering the lure of discretionary policy compared to closed systems due to mutual

pressure among linking partners. As result, price signals in linked systems can be more

credible.

Providing opportunities for development of a global carbon market.


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Strengthening international cooperation and building mutual trust, which may support

reaching global emission reduction goals and potential facilitation of the international

negotiation process on climate change mitigation.

However, linking may also entail economic, political and environmental challenges. Price

containment measures, such as price caps and unconstrained borrowing, as well as relative

commitments and ex-post adjustments of allowances are the most challenging to overcome.

They can decrease environmental effectiveness of the trading system and cause negative

economic or distributional impacts.

Linking may also lead to an import of volatility from partner systems and to leakage as the

sensitivity to changes in carbon prices in each economy linked may vary. Thus, a region with

increasing carbon prices as result of linking may be exposed to increasing leakage.

Further, linking educes the national control over the domestic market and may hinder attain

prioritized policy objectives.

In order to avoid potential challenges

An analysis has to be carried out about differences of systems to be linked with,

The advantages and disadvantages of linking have to be clearly estimated and,

Several basic criteria need to be agreed on between different ETS before linking.

5. Conclusions

The outlined benefits and challenges of linking as well as the fundamental requirements are

valid for all types of direct linking of ETS. This is true also for linking with the Kazakh ETS or

potentially developing ETS in other FSU.

Although Ukraine currently does not prepare for the implementation of a national ETS at

least two main fundamentals of linking and of international cooperation in similar systems

need to be considered which are crucial as well for achieving the goals and targets of

national strategies and policies:

Credibility

Stringency of targets

Also some rules to be implemented for linking are worth to be considered in any case as

they are relevant for other instruments of GHG emissions reduction. This is especially

true for:

Defining monitoring guidelines

Setting up monitoring and reporting schemes for GHG emissions

Implementing guidelines for verifiers as well as rules for accreditation of verifiers


with other systems


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Although Ukraine has already some experiences with MRV reporting and verification of

greenhouse gas emissions the current MRV system needs to be substantially improved

not only for a potential ETS but also for monitoring implementation of other GHG

reduction policies and measures like a carbon tax or implementation of the Energy

Strategy 2030.

MRV system should always be as robust and ambitious as feasible in order to be most

useful for domestic purposes of MRV and to address international requirements at the

same time. To establish two parallel systems for domestic and international purposes

would be highly inefficient.

Respective MRV guidelines and rules should be in line with guidelines and rules of major

potential emission trading partner countries.

As the complexity of an MRV system is huge it needs strong coordination capacity

between national and subnational entities. Co-ordination and communication between

regulators, industries and verifiers through workshops or permanent working group are

very helpful.

Due to the fact that linking may generate advantages as well of disadvantages both

should be analysed in advance before making a decision o on linking.


Final Report


Appendix C-8

From Stabilisation to Sustainable

Economic Growth

Low Carbon Ukraine - Policy Paper No. 6 (June 2014)


Final Report


From Stabilisation to Sustainable

Economic Growth


(June 2014)

From Stabilisation to



ii

DIW econ GmbH

Dr. Lars Handrich

Mohrenstraße 58

10117 Berlin

Germany

Phone +49.30.20 60 972 - 0

Fax +49.30.20 60 972 - 99

[email protected]

www.diw-econ.de

DIW econ GmbH

Dr. Ferdinand Pavel

Mohrenstraße 58

10117 Berlin






iii

Table of Contents


1. Introduction ..................................................................................................................... 1

2. Energy Market Reform and Economic Growth ................................................................ 1

2.1 Contemporary technology and energy efficiency level .............................................. 2

2.2 Capital stock regeneration and economic growth ...................................................... 5

3. Spurring capital stock modernisation and diversification ................................................. 7

4. Policy Recommendations ............................................................................................... 8

5. References ..................................................................................................................... 9




iv

Executive Summary


stability in Ukraine. However, the fundamental structure of the Ukrainian economy remains

flawed. A strong reliance on industry exports coupled with a pronounced dependence on

energy imports jeopardizes Ukrainian long-term growth prospects and makes it vulnerable to

external shocks. Thus, structural policies ought to prioritise economic diversification to

achieve sustainable economic growth.

Abolishing energy subsidies and liberalising energy markets are key conditions adherent to

the IMF loans. However, they are also expected to incur a wave of energy price shocks and

thus, economic losses. Hence, the economy risks being locked in a viscous cycle where

stabilization requires price shocks which in turn undermine economic growth and –

eventually – stabilisation. The focus of this paper is to demonstrate how this cycle can be

broken. In the medium-term, energy prices shocks can initiate technological adjustment,

yielding productivity gains and energy efficiency. Under favourable circumstances, incipient

losses are not only set off but also allow for economic growth. In Ukraine, however,

conditions for such a technological adjustment process towards lower energy intensity have

not been established yet. Rather, a technological frontier gap and pronounced capital

depreciation prevail. Moreover, protectionist government measures in different manufacturing

industries invalidated the market pressure to invest in energy efficiency and capital stock

modernization. Accordingly, reversing the trends of capital depreciation and high energy

intensity in manufacturing, improving market structures in the energy sector and ameliorating

the economy-wide business environment can provide Ukraine with vast potential for

economic growth. This is the focus of this paper.

Above all, initiating capital stock modernisation as well as diversification requires

investments. In turn, kick-starting investments requires the government to act along two lines

of action:


reforms in areas such as strengthening of property rights and fighting corruption and red-tape

is well understood, and the key measures have been widely discussed already. However, we

acknowledge that even if the government succeeds in improving the country‟s investment

climate, quick acceleration of investment activities is highly unlikely since trust and

confidence of investors can only be build up over a considerable period of time. However,

neither the economic nor the political situation in Ukraine allow to wait.




v

Accordingly, the second task is initiating public support to private investment in all relevant

areas including modernisation of capital stock in manufacturing, infrastructure or buildings.

As public budgets will not be able to provide the necessary funds, the government needs to

secure funding through international donors willing to support economic reconstruction in

Ukraine. In fact, by establishing improvements in energy efficiency as key condition for such

loans, the government can achieve a win-win situation:

As argued before, reducing energy intensity is key to re-vitalise the national economy

during times of rising energy prices. Hence, a benefit to Ukraine.

Reducing primary energy consumption as well as carbon emissions is a common

objective of international donors such as World Bank, EBRD, European Investment Bank

etc. Hence, using donors‟ funds to reduce energy intensity is a clear benefit to those

organizations as well.




1

1. Introduction


stability. However, the fundamental structure of the Ukrainian economy remains flawed. A

strong reliance on industry exports of just a few sectors such as metallurgy coupled with a

pronounced dependence on energy imports jeopardizes Ukrainian long-term growth

prospects and makes it vulnerable to external shocks. Thus, structural policies ought to

prioritise economic diversification to achieve sustainable economic growth.

Phasing out energy price subsidies, improving energy efficiency, and liberalising the energy

market, are among the key conditions adherent to the IMF loans. However, these measures

are expected to entail a wave of energy price shocks and thus, economic losses. Hence, the

economy risks being locked in a vicious circle where stabilisation triggers price shocks which

in turn undermine economic growth and – eventually – stabilisation.

The focus of this paper is to demonstrate how this cycle can be broken. In the medium-term,

energy prices shocks can initiate technological adjustment, yielding productivity gains and

energy efficiency. Under favourable circumstances, incipient losses are not only set off but

also allow for economic growth. Thus, a key challenge for policy-makers is to create

conditions to link energy subsidy removals with economic growth.

2. Energy Market Reform and Economic Growth

With an estimated general government deficit of 4.8 percent of GDP in 2013 (IMF 2014) and

gas price subsidies representing about 1.6 percent of GDP in 2011 (IEA/OECD 2012), the

IMF loan conditions focussing on budget consolidation and strengthening of market

structures in the energy sector, including the implementation of cost-covering energy prices,

are without alternative. The energy sector drains public finances and provides false price

signals to suppliers, distributors and consumers. This stimulates excessive use of energy,

fails to provide incentives for energy efficiency improvements and – in particular – leaves the

economy highly vulnerable to future energy price shocks.

Accordingly, the required abolishment of energy price subsidisation poses a threat to

economic growth prospects. In the medium-term though, cost-covering energy prices can

spur economic benefits as they make investments into new technologies profitable and




2

thereby stimulate productivity gains. The key challenge for Ukrainian policy-makers is thus to

initiate a rapid transition from short-term economic contractions evoked by energy price

shocks to economic growth through investments into capital stock modernisation and

economic diversification.

2.1 Contemporary technology and energy efficiency level

The comparison of economic development and energy efficiency by different countries

asserts country-specific learning curves (Figure 1). Specifically, higher levels of GDP per

capita appear to correlate negatively with energy use per GDP. In other words, economic

growth seems to be (positively) linked with higher levels of energy efficiency. Countries such

as the United States or Germany that already employ state-of-the-art technologies invest

financial and human resources in research and development to shift technological and

energy efficiency boundaries. Other countries that lack behind, can cost-efficiently adopt

these innovations by providing investment-friendly conditions and competitive markets for

new technologies. This can be further supported through appropriate technology standards,

stimulation of public investment demand and programmes for energy efficient refurbishment

of the building stock. In fact, energy price shocks can be an important driver for such

investments and modernisation of capital stock.

Figure 49 Country-specific learning curves of energy efficiency




3

Source: World Bank, World Development Indicators (2013)

For Ukraine, the relation between GDP per capita and energy efficiency is not as clear-cut as

in similar countries such as Poland or Russia. The economic crisis in 2008/2009 led to a

contraction of GDP which eventually caused an energy intensity to even increase in 2010.

However, the development of energy efficiency in Ukraine as shown in Figure 1 is not only

specific due to recent economic developments. Rather, it exhibits much higher levels of

energy intensity than in other countries. However, whereas Ukraine‟s economy made strong

advancements in energy efficiency until 2007, this trend has recently dissolved.

Figure 50 Impact of gas prices on demand

0

0,25

0,5

0,75

1

1,25

1,5

1,75

2

500 5000 50000

Energ

y u

se (

kg o

f oil

equiv

ale

nt)

per

GD

P (

consta

nt

2005

US

D)

GDP per capita (constant 2005 USD)

Germany

United States

Poland

Russian Federation

China

Ukraine

2002

2011

2003

2004

2005

2006

2007

2010

20082009




4

Source: International Energy Agency (2001 ff.)

Ukraine‟s economy has already been exposed to energy price shocks. In particular, prices

for imported gas from Russia have been increasing since 2005. However, Figure 2 illustrates

that until today, domestic demand has only slightly responded to higher gas prices. In

particular, industrial gas consumption has dropped significantly between 2007 and 2009 but

– despite further increases of import prices – has increased again after 2009. Similarly, also

industrial consumption of coal has increased since 2009 while residential gas consumption

has remained almost flat since 2001. In fact, this pattern characterises Ukraine‟s energy

policy until very recently where households were shielded from market developments

through populist regulation and industries where supported though additional measures. For

example, the chemical industry, Ukraine‟s largest natural gas consumer, served to quasi-

subsidize natural gas consumption (IEA/OECD 2012) has been exempted from value-added

taxes (VAT) on gas consumption (Cabinet Decree No. 880, 2009). In January 2014, the

Verkhovna Rada even prolonged such measures when allowing for the cancellation of VAT

for natural gas importers, resulting in a gap of 59.5 billion Hryvnia in the government budget

in 2014 alone. Along coal substitution, such protectionist measures are another factor that

cushions market pressures to invest in energy efficiency.

Rather than investing in capital stock modernisation and benefiting lower energy intensity,

the Ukrainian capital stock remains out-dated and energy-inefficient (Figure 3), leaving the

economy subject to energy price shocks. Noteworthy is the surge in capital stock

0

50

100

150

200

250

300

350

0

2000

4000

6000

8000

10000

12000

14000

16000

18000

20000T

housa

nd tonnes

of

oil

evquiv

ale

nt

Industrial gas consumption Industrial coal consumption

Residential gas consumption Gas import prices

US

D/1

000m

³




5

depreciation from 2009 to 2010 depicted in Figure 3 and the analogue jump in energy use

per US-Dollar GDP from 2009 to 2010 as shown in Figure 1. Capital stock depreciation

seems to have directly translated into an increase in energy intensity. More generally,

pronounced capital stock depreciation starting in 2007 coincides with the vanishing learning

curve on energy efficiency in the same year.

Figure 51 Capital stock depreciation in Ukraine

Source: UkrStat, Fixed Assets (2001 ff.)

In addition to the vulnerability to energy price shocks, considerations of resource productivity,

energy import dependency, as well as climate change mitigation increase the importance of

energy-efficiency improvement vis-à-vis an ageing capital stock. Continuing capital stock

depreciation would increase the distance to the technological and productivity frontier further

and hinder economic progress.

2.2 Capital stock regeneration and economic growth

Upgrading technology and improving productivity to the levels of a moderately contemporary

capital stock provides Ukraine with a large potential for economic growth and improvements

of energy efficiency (Box 1 exemplifies these potentials for the Metal Industry). Not only

would a closure of the technology gap result in lower energy intensity and operating costs but

would furthermore lead to a lower vulnerability to energy and production price shocks,

positively contributing to economic growth and a relief on climate change pressures. Despite

such expectations of economic gains from capital stock modernisation, necessary

40%

45%

50%

55%

60%

65%

70%

75%

80%

Deg

ree o

f cap

ital s

tock d

ep

recia

tio

n




6

investments did not take place thus far. Erosion of – rather than investment in – the capital

stock was the basis of the past unsustainable, economic growth in Ukraine.

Box 1: Energy Efficiency Potential of the Metal Industry in Ukraine

In a previous paper (Benchmarking for sustainable and economically viable technology

options, Low Carbon Ukraine - Technical Paper No. 2, August 2013), DIW Econ analyzed

the economic viability and environmental sustainability of the basic and fabricated metal

industry in Ukraine against an international benchmark. The focus of this analysis is the

concept of technical efficiency, which describes the ability to produce high levels of output

with low levels of greenhouse gas (GHG) emissions from a given set of inputs (labour,

capital and energy). The sectoral analysis showed, that within a sample of 27 countries,

only Brazil, the Czech Republic and India have a lower technical efficiency level in the

metal industry than Ukraine. Even after taking into account the given production structure

of Ukraine, i.e. its focus on highly energy intensive products, Ukraine ranks among the

countries with poor performance in terms of technical efficiency and thus exhibits

significant potentials for GHG emissions.

Underlying causes for the lack of investments and the resulting capital stock depreciation can

be found in Ukraine‟s adverse business climate as well as a weak rule of law. Referring to

the energy market, the persistency of artificially low levels of energy prices reduced and at a

certain point diminished the incentives to invest in a modernised and energy-efficient capital

stock. Interference in the mechanisms of the energy market thus not only proved to be

unsustainable but furthermore inefficient.

The absence of market mechanisms in the energy market characterizes much of the

Ukrainian economy. Generally, interference in market institutions results in an economy-wide

low degree of competition and limited market development across sectors. Despite being

among the economies improving the most in 2012/2013, Ukraine still ranks 112th out of 189

evaluated economies in the 2014 World Bank‟s Doing Business Report. Within Transparency

International‟s Corruption Perception Index (2013), Ukraine ranks 144th out of 175 countries.

Neither the absence of market mechanisms, nor the weak rule of law stimulates national or

international investors‟ trust in the Ukrainian business environment and the Ukrainian

economy in itself. Restoring investor‟s trust is necessary to reverse the trend of capital

depreciation and bridge the technology gap to exploit the available growth and energy

efficiency potential.




7

3. Spurring capital stock modernisation and

diversification

Initiating capital stock modernisation as well as diversification requires investments. Although

private capital is potentially available in Ukraine as well as from abroad, the prevailing

insufficient investment climate and lack of trust prevent the immediate activation of such

funds. Kick-starting investments therefore requires the government to act along two lines of

action:


reforms in areas such as property rights, corruption and red-tape is well understood, and

the key measures have been widely discussed already. However, we acknowledge that

even when the government succeeds in improving the country‟s investment climate, the

quick acceleration of investment activities is highly unlikely as trust and confidence of

investors can only be build over a considerable period of time. However, neither the

economic nor the political situation in Ukraine allow to wait.

Accordingly, the second task is initiating public support to private investment in all

relevant areas including the modernization of capital stock in manufacturing,

infrastructure and buildings. As public budgets will not be able to provide the necessary

funds, the government needs to secure funding through international donors willing to

support economic reconstruction in Ukraine.

In order to direct the commitment of international donors and international financing

institutions (IFIs) to support sustainable economic development the Ukrainian government

should, first of all, improve the conditions for investment into energy efficiency by introducing

cost-covering prices. In addition, the Government of Ukraine should together with

international donors set-up special public program aimed at improvements in energy

efficiency.

An adequate example of such program is the appointment of a public loan program for

energy efficient refurbishment of the existing building stock. This program could

create demand for energy efficient technologies in the building sector;

spur investments in the production of such technologies in Ukraine; and

create new jobs during the implementation of refurbishment and future maintenance.




8

Public support for investments in infrastructure and manufacturing could be utilized to lower

prevailing uncertainties resulting from lack of trust to economic governance by strengthening

property rights and engaging in anti-corruption measures to name a few. Public support via

international donors and IFIs could help to establish needed trust and thus work as a motor

for capital stock modernization and productivity advancements as well.

4. Policy Recommendations

In addition to reinforced economic stability aided by the IMF rescue program, structural

policies are necessary in order to prioritize economic diversification and kick-start capital

stock modernization.

Abolishing energy subsidies and strengthening market forces in the energy sector are

key preconditions but not sufficient to initiate technological adjustment yielding

productivity gains.

In order to kick-start modernization and diversification, the following governmental

measures will be beneficial:

Improve the country‟s investment climate;

Improve trust in governmental reforms with the support of public financing offered by

international donors and IFIs;

Utilize public financial support to create markets for energy efficient technologies by

setting up infrastructure programmes, programmes for energy efficient refurbishment

of the building stock and programmes of co-financing capital stock modernization

and diversification through small and medium enterprises.

Public co-financing should remain within the boundaries of “support”, i.e. with a

distinct temporary character and the aim to address available private capital,

specifically financial means from current operations of firms within the

manufacturing industry.

As capital stock modernisation and diversification entail energy efficiency improvements and

thereby an element of climate change mitigation, cooperation between the Ukrainian

government and the international donor community can not only ignite sustainable economic

growth but, on an international level, provide a stimulus for international cooperation to fulfil

the common but differentiated responsibility of countries in climate change abatement.




9

5. References

DIW Econ (2013). Benchmarking for sustainable and economically viable technology options

Selected industries in Ukraine, Low Carbon Ukraine - Technical Paper No. 2 (August

2013)

IEA (2001 ff.). Energy Balances of Non-OECD Countries. Paris: International Energy Agency

IEA / OECD (2012). Ukraine 2012: Energy Policies Beyond IEA Countries. Paris:

International Energy Agency

IMF (2014). Request for a Stand-By Arrangement: IMF Country Report Ukraine No. 14/10.

Washington, D.C.: International Monetary Fund

Documents

Final Report - UNDP v 1.… · Low Carbon Growth in Ukraine Final Report iv 3. Impact assessment of identified policies and measures and development of BAU scenarios until 2020 and