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"Prioritizing agricultural subsector growth and investments at the country level: Methodology to assess economy-wide impacts", presentation by James Thurlow and Paul Dorosh at the USAID, IFPRI Financial Gap Analysis Workshop held at the World Bank, January 7, 2010.
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IFPRI
INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE
Prioritizing agricultural subsector growth and
investments at the country level:
Methodology to assess economy-wide impacts
James Thurlow and Paul Dorosh
International Food Policy Research Institute
USAID/World Bank Workshop on
“Agricultural investment priorities and financing gaps for achieving growth and
poverty reduction targets: Review of evidence and methodology”
January 7, 2010
IFPRI
Broad Strategic Questions
Is a 6% agricultural growth rate enough to reach national poverty targets? If not what is the required agricultural growth rate?
How can different agricultural sectors contribute to accelerating growth?
How do outcomes vary across sub-national regions?
How will different types of farmers be affected, and what is the impact on rural employment and the non-farm economy?
What are the potential product market constraints caused by expanding agricultural productivity?
IFPRI
Overview
1. Economywide growth and poverty analysis Overview and key features of the methodology
2. Modeling future growth scenarios Results from the Uganda case study
3. Prioritizing sectors for investment Criteria for ranking crops and sub-sectors
Results from selected country studies
IFPRI
IFPRI Estimates of Impacts of Agricultural Investments:
Two Analytical Approaches
1. Costing of MDG and Development Objectives using a reduced
form approach (“spreadsheet” calculations of growth and poverty
reduction effects)
» Fan, Johnson, Saurkar and Makobe (2009), “Investing in African
Agriculture to Halve Poverty by 2015”, ReSAKSS Working Paper
No. 25 (February).
» Costing studies for Ghana and Uganda
2. Individual country studies for CAADP using economy-wide
models
» Ghana, Kenya, Nigeria, Rwanda, Uganda, Zambia
» Ethiopia, Mozambique, Tanzania (CGE analysis not including
investment costs)
IFPRI
Approach 2: Impacts of Agricultural Investments
using Economy-Wide Models (CAADP analysis)
Individual country studies for CAADP using
economy-wide models
» Output-investment elasticities for individual agricultural
sub-sectors (derived from econometric analysis)
» CGE model simulations of the agricultural productivity
shocks showing
Changes in real prices
Sectoral and total GDP growth
Household income and consumption
Poverty rates
IFPRI
1. Growth and poverty analysisEconomywide (“CGE”) modeling framework
Factor markets
Commodity markets
Foreign markets/
countries
Public sector/
government
Human/physical capital
Productivity/technology
Urban/Rural
Farm/
Nonfarm
Agriculture
Industry
Services
Economic production Incomes and poverty
Production Consumption
Wages, rents,
profits
Foreign trade
Foreign aid
TaxesSpending
and market
policies
Foreign
investment
Taxes and
social policies
Public investment
and macro
policiesPrivate
investment
IFPRI
1. Growth and poverty analysis: Agriculture-nonagriculture linkages
Models include detailed agricultural and nonagricultural sectors
Capture upstream and downstream linkages (e.g., maize cultivation and
grain milling)
Considers all different income sources (e.g., off-farm, remittances)
Captures labor mobility and rural-urban migration
Includes the government (e.g., public spending, transfers, taxes)
Zambia Kenya Mozam-bique
Tanzania Malawi Ethiopia
Whole economy 100.0 100.0 100.0 100.0 100.0 100.0
Agriculture 20.5 25.7 25.9 31.8 40.1 44.9Cereals 5.5 4.4 5.3 8.3 11.9 13.5Exports 3.5 4.6 1.1 2.8 10.2 4.5
Livestock 3.1 5.4 1.7 5.5 2.5 12.9Manufacturing 13.0 11.0 13.7 8.8 10.8 5.2
Agro-processing 11.5 3.1 2.0 6.7 6.3 2.4Other non-mining industry 10.4 7.1 9.5 10.4 5.7 1.9
Sector contributions to national gross domestic product (GDP) (%)
IFPRI
1. Growth and poverty analysis: Domestic and foreign markets and prices
Models consider demand and supply interactions in both domestic and
international markets
Includes transaction costs separating home/marketed production
Considers macroeconomic conditions (e.g., balance of payments
constraints and exchange rates)
Share (%) Intensity (%)
Export Import Export ImportWhole economy 100.0 100.0 9.4 22.0
Agriculture 34.9 6.1 13.2 7.3Cereals 0.0 5.5 0.0 18.2Exports 21.5 0.3 63.5 7.1
Livestock 1.6 0.0 3.6 0.0Manufacturing 12.8 87.9 8.3 61.4
Agro-processing 2.1 10.0 2.0 20.8Other non-mining industry 0.0 0.0 0.0 0.0
Sector contributions to trade in Tanzania (%)
“Intensity” is the share of exports in output, and share of imports in demand
IFPRI
1. Growth and poverty analysis:
Spatial variation in production patterns
Models capture differences in
production patterns across sub-
national regions
Reflects differences in agro-
ecological conditions and
potential
Malawi North Center South Urban
Maize 49.9 43.9 51.1 47.2 72.3
Other cereals 4.7 4.3 2.1 8.0 0.6
Root crops 11.0 20.4 9.7 10.4 4.2
Pulses & oils 23.2 18.4 24.2 24.5 16.5
Horticulture 3.1 4.0 3.3 2.7 2.2
Tobacco 4.4 7.6 6.6 1.5 2.6
Other export crops 3.8 1.3 3.1 5.6 1.7
All crops 100.0 100.0 100.0 100.0 100.0
Land allocated to crops by region in Malawi (%)
IFPRI
1. Growth and poverty analysis:
Farm-level variations in cropping patterns
Models capture differences in production patterns across farmers with
different characteristics or endowments (e.g., land holding size)
Reflects differences in farmers’ opportunities and constraints (i.e.,
structure of production/crop mix, scale of production, access to
irrigation, etc)
Malawi Large
(>3ha)
Medium
(0.75-3ha)
Small
(<0.75ha)
Urban
Maize 49.9 45.4 47.8 52.4 72.3
Other cereals 4.7 1.2 5.5 6.2 0.6
Root crops 11.0 4.6 12.6 12.8 4.2
Pulses & oils 23.2 14.6 25.5 24.3 16.5
Horticulture 3.1 1.7 3.4 3.3 2.2
Tobacco 4.4 22.5 1.8 0.0 2.6
Other export crops 3.8 10.0 3.5 1.0 1.7
All crops 100.0 100.0 100.0 100.0 100.0
Land allocated to crops by scale of production in Malawi (%)
IFPRI
The Data Base
EDRI 2004/05 Social Accounting Matrix (SAM)
Constructed as part of a project with the University of
Sussex (w/support of IFPRI-ESSP2)
65 production sectors (24 agricultural, 10 agricultural
processing, 20 other industry, 11 services)
Regional SAM based on the “3 Ethiopias”
• Rainfall sufficient, drought prone, pastoralist
• Rainfall sufficient AEZ disaggregated to humid lowlands,
enset-based systems, and other (highland) rainfall
sufficient areas
Poor household groups defined as poorest 40% of rural and
urban households according to HICES 2004/05 per capita
expenditure data
IFPRI
Agro-ecological Zones (AEZ’s):
“3 Ethiopias” split into 5 AEZs
Source: 2005/06 EDRI Social Accounting Matrix.
IFPRI
1. Growth and poverty analysis: Household income distribution and poverty
Models identify representative household groups based on location,
income sources, endowments, etc
Households in the model are linked to a survey-based micro-
simulation module in order to measure poverty impacts
Farm typology
Agriculture Non-agriculture
Rural Urban
Micro-simulation poverty module
Economywide modelLabor income Land
& live-
stock
Capital
profits
Other
income
All
sourcesLow
skilled
High
skilled
RuralPoor 24.9 7.2 27.5 34.9 5.5 100.0
Non-poor 14.1 6.1 41.7 34.4 3.7 100.0
Small
urban
Poor 0.7 37.8 0.0 49.1 12.5 100.0
Non-poor 0.2 20.9 0.0 69.3 9.6 100.0
Large
urban
Poor 0.6 41.4 0.0 20.1 38.0 100.0
Non-poor 0.1 15.9 0.0 48.9 35.1 100.0
All households 13.2 10.5 27.7 39.8 8.7 100.0
Household income shares in Ethiopia (%)
IFPRI
1. Growth and poverty analysis: Summary of key features of the models
Economywide (agriculture and non-agriculture)
Detailed crop and livestock production technologies
Sub-national agricultural production patterns
Farm typologies (e.g., land endowments, technologies)
Domestic and foreign markets and prices
Representative households captures distributional change
Households linked to survey-based micro-simulation module to capture poverty outcomes
IFPRI
2. Modeling alternative growth scenarios:
Business-as-usual versus accelerated growth
Dynamic models: considers growth paths for next
10 – 15 years
Three growth scenarios commonly considered:
1. Business-as-usual growth path as a baseline
2. Accelerated agricultural growth scenario to meet
CAADP target
3. Accelerated agricultural and nonagricultural growth to
achieve MDG1
Accelerated growth in both agricultural and
nonagricultural sectors are driven by productivity
improvements
IFPRI
2. Modeling alternative growth scenarios:Accelerated growth by closing yield gaps in Uganda
Yield gaps are drawn from the country, and in most cases
obtained from Ministry of Agriculture
Yields for selected crops in Uganda (current and targeted)
IFPRI
2. Modeling alternative growth scenarios:Economy-wide impact assessment, Uganda
Average GDP growth rates (%)
Total GDP growth increases from
5.1% to 6.1%
Agricultural GDP growth
increases from 2.7% to 6.0%
(i.e., CAADP target)
Agricultural processing GDP growth
rises from 4.4% to 5.8%
(linkage-effects for the
nonagriculture sector)
Export crops have higher growth
potential
IFPRI
2. Modeling alternative growth scenarios:
Impact on poverty reduction, Uganda
Faster agricultural growth greatly accelerates poverty reduction…
Base scenario: achieves MDG1 (i.e., half 1991 poverty by 2015)
CAADP: additional 7.6% poverty reduction (2.9 million people by 2015)
IFPRI
2. Modeling alternative growth scenarios:Market constraints and price effect, Uganda
Some crops face serious
market constraints
Prices fall more if income
elasticity is low and
production increases too
rapidly (e.g. matoke)
Export opportunities are
small for domestic staple
crops even after prices fall
More domestic-focused food
crops are affected most
(e.g. maize, matoke)
Assuming exported crops are not
constrained by world market demand
(e.g. coffee)
0.65
0.70
0.75
0.80
0.85
0.90
0.95
1.00
1.05
1.10
2005 07 09 11 13 15
Price
in
de
x (
20
05
=1
)
Coffee
Vege.
Maize
Fish
Potatoes
Matoke
IFPRI
3. Growth options and investment prioritization
Four criteria for agricultural sub-sector prioritization
1. Growth potential and size-effect: Larger sectors can contribute more to national growth
Some sectors may be small but can grow fast
2. Poverty-effect: Some sectors are better at reducing poverty (stronger
income generation for poorer households)
3. Linkage-effect: Some sectors generate more growth outside of agriculture
4. Price-effect: Some sector face greater demand or market constraints
IFPRI
3. Growth options and investment prioritization
Results from Uganda
Best growth potential & largest subsectors
Strongest poverty reducing effectsStrongest growth
spillovers to rest of economy
Roots
CerealsForestry
Coffee & export crops
Matoke
Pulses
Livestock
IFPRI
3. Growth options and investment prioritization:Summary of sector ranking for selected countries
Criteria 1:Growth potential
and size-effect
Criteria 2:Poverty-
effect
Criteria 3:Linkage-
effect
Criteria 4:Price-
effect
KenyaMaize,
export crops
Rice,
export crops
Livestock,
roots
Livestock,
sorghum
MalawiMaize,
tobacco
Vegetables,
pulses
Rice,
roots
Tobacco,
vegetables
MozambiquePlanned biofuels,
maize
Maize,
other cereals
Roots,
livestock
Cashews,
export crops
NigeriaCassava,
riceRice,
millet/sorghumPulses,cereals
Wheat, maize
RwandaPotatoes,livestock
Pulses, maize
-Maize,
rice
TanzaniaMaize,
livestock
Maize,
roots
Livestock,
pulses
Rice,
tobacco
UgandaRoots,
matoke
Vegetables,
roots
Vegetables,
forestryCoffee, fisheries
ZambiaExport crops,
maize
Roots,
maize
Roots,
livestock
Export crops,
livestock
IFPRI
3. Growth options and investment prioritization:
Completed country-level studies
IFPRI has provided technical
support to COMESA and
ECOWAS to prepare for the
CAADP roundtables
IFPRI has also provided technical
support to three regional
organizations (CORAF,
ASARECA, CARDESA) for
regional level strategic analysis
Detailed country study
Covered by regional studies
IFPRI
Summary
1. The evaluation of alternative investments depends on:
The output-investment ratio (which is exogenous to the models)
Economy-wide effects of the increase in crop or sub-sector productivity
2. Economy-wide growth and poverty analysis
Models are based on detailed data on crop production patterns, sectoral output,
factor earnings, and household incomes and expenditures captured in Social
Accounting Matrices (SAMs) for individual countries
The CGE models used use conservative estimates of parameters for supply and
demand response to changes in price incentives
3. Modeling future growth scenarios
Base-line simulations are derived from historical growth rates
Alternative investment patterns are modeled as exogenous increases in
productivity
The simulations show the economy-wide impact of these productivity increases on
production, incomes, prices and poverty in consistent economy-wide framework
4. Prioritizing sectors for investment
Various criteria are used for ranking investments in crops and sub-sectors