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Poverty & Equity Global Practice Working Paper 164 INFRASTRUCTURE, VALUE CHAINS, AND ECONOMIC UPGRADES Xubei Luo Xuejiao Xu August 2018 Public Disclosure Authorized Public Disclosure Authorized Public Disclosure Authorized Public Disclosure Authorized

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Page 1: INFRASTRUCTURE, VALU E CHAINS, AND ECONOMIC UPGRADES

Poverty & Equity Global Practice Working Paper 164

INFRASTRUCTURE, VALUE CHAINS,

AND ECONOMIC UPGRADES

Xubei Luo Xuejiao Xu

August 2018

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Page 2: INFRASTRUCTURE, VALU E CHAINS, AND ECONOMIC UPGRADES

Poverty & Equity Global Practice Working Paper 164

ABSTRACT Infrastructure development is critical to delivering growth, reducing poverty, and addressing broader development goals. This paper surveys the literature on the linkages between infrastructure investment and economic growth, discusses the role of infrastructure in participation in global value chains and supporting economic upgrades, highlights the challenges that the least developed countries face, and provides policy recommendations. It suggests that addressing the bottlenecks in infrastructure is a necessary condition to provide a window of opportunity for an economy to develop following its comparative advantage. With the right conditions, good infrastructure can support an economy, particularly a less developed economy, to reap the benefits of participation in global value chains to upgrade the economic structure.

This paper is a product of the Poverty and Equity Global Practice Group. It is part of a larger effort by the World Bank to provide open access to its research and contribute to development policy discussions around the world. The authors may be contacted at [email protected].

This paper is co-published with the World Bank Policy Research Working Papers.

The Poverty & Equity Global Practice Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.

‒ Poverty & Equity Global Practice Knowledge Management & Learning Team

Page 3: INFRASTRUCTURE, VALU E CHAINS, AND ECONOMIC UPGRADES

Infrastructure, Value Chains, and Economic Upgrades

Xubei Luo1, Xuejiao Xu2

1. Poverty Global Practices, The World Bank, Washington D.C., USA, [email protected]

2. Columbian College of Arts & Sciences, The George Washington University, Washington D.C.,USA, [email protected]

JEL classification: H54; O40, F14, F60

Keywords

Infrastructure gap; economic growth; structural upgrades; least developed countries; global value chains

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Infrastructure, Value Chains, and Economic Upgrades 

Xubei Luo and Xuejiao Xu* 

.

An  accessible,  affordable,  and  reliable  infrastructure  network  is  crucial  for  development.  It  is 

necessitous  for powering business,  lowering  transactions  costs,  improving market  access,  and 

improving the efficiency of other productive factors; and it is prerequisite for providing people 

with access to important services like education and health care, connecting workers to their jobs, 

and  sharing  the  fruits of growth  in an equitable manner.  In  the global arena,  infrastructure  is 

essential for participation in value chains to upgrade economic structure.  As argued in the World 

Bank Report Transformation through Infrastructure (2012a), infrastructure development is critical 

to delivering growth, reducing poverty, and addressing broader development goals.1  

This paper surveys the literature of the linkages between infrastructure investment and economic 

growth, discusses the role of infrastructure in participation in global value chains and supporting 

economic  upgrades,  highlights  the  challenges  faced  by  the  least  developed  countries,  and 

provides  policy  suggestions.  It  suggests  that  addressing  the  bottlenecks  in  infrastructure  is  a 

necessary condition to provide a window of opportunity for an economy to develop following its 

comparative advantage. With the right conditions, good infrastructure can support an economy, 

particularly a less developed economy, to reap the benefit through participation in global value 

chains to upgrade the economic structure.  

Infrastructure investment and economic growth 

Infrastructure  includes  hard  (tangible)  infrastructure  and  soft  (intangible)  infrastructure.  Hard 

infrastructure often refers to the transport system (such as roads, airports, port facilities, and rail), 

public utilities (such as energy, water supply and sewer, and irrigation), communication network 

(such  as  telecommunication  and  broadband),  and  social  infrastructure  (such  as  schools  and 

hospitals). Soft infrastructure often refers to matters related to efficiency, such as institutions and 

regulations.2  

There  is  a  vast  literature on  the  contribution of  infrastructure and public  capital  to aggregate 

productivity  and  growth.  Arrow  and  Kurz  (1970)  examined  the  relationship  between 

infrastructure investment and productivity using the Ramsey type exogenous growth model and 

* Xubei Luo is an economist at the World Bank, Xuejiao Xu is a graduate from George WashingtonUniversity. The authors would like to thank participants at the 4th New Structural Economics InternationalConference at Peking University for comments. Special thanks go to  Justin Lin, Yong Wang, Shang‐Jin Wei,Yanrui Wu, Jianye Yan, and Juzhong Zhuang, for useful discussions and suggestions. The findings,interpretations, and conclusions expressed in this paper are entirely those of the authors. They do notnecessarily represent the views of the International Bank for Reconstruction and Development/WorldBank and its affiliated organizations, or those of the Executive Directors of the World Bank or thegovernments they represent.1 See World Bank (2012a).2 See more from Lin (2011), Bottini, Coelho, and Kao (2012), and Ismail and Mahyideen (2015).

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found  that  the  volume  of  public  investment  conditions  marginal  productivity.  Barro  (1990) 

included pubic capital in the framework of the endogenous growth model and concluded that the 

growth and savings rate increase initially with productive services, but subsequently decline, while 

the  two  rates  were  negatively  associated  with  consumption  services.  Futagami  et  al.  (1993) 

extended Barro’s method, by adding private capital stock into the endogenous growth model, and 

showed that long‐run economic growth is maximized when the income tax rate equals the output 

elasticity of public capital.  World Bank (2012a) showed a positive correlation between estimated 

infrastructure investments (per capita) and the level of development (proxied by GDP per capita) 

using data from 104 countries (Figure 1). WEF (2013) suggested that, if every country improved 

border  administration,  transport  and  communications  infrastructure,  and  related  services 

halfway  to  the world’s best practices,  global GDP could  increase by US$2.6  trillion  (4.7%) and 

exports by US$1.6 trillion (14.5%). 

Figure: 1 Infrastructure investment and economic development 

 Cited from World Bank (2012a), Transformation through infrastructure.  

Note: Total investments in infrastructure consist of: (a) new investment resulting from the variation in infrastructure stocks between 2000 and 2005, valued at unit costs; and (b) requirements for maintenance, resulting from multiplying stocks of 200 by a depreciation rate. Infrastructure sectors include paved and unpaved roads, rails, ports, electricity generation and electrification, fixed and mobile communications, and water supply and sanitation. The curve is obtained by a three‐degree polynomial trend 

 

There is an indication that infrastructure is closely associated with economic development, while the empirical evidence of the causality between infrastructure and productivity growth remains inconclusive and the marginal productivity of infrastructure varies across countries. De la Fuente (2010) provided a survey of the literature with a thorough discussion of the econometric complications. Aschauer (1989) found that the slowdown of the investment rate in public infrastructure leads to the deceleration of private‐sector total factor productivity in the U.S. since the early 1970s. Wylie (1996) used a similar approach as Aschauer's analysis and found high returns of infrastructure investment to productivity in Canada’s goods‐sector, and complementarity of infrastructure with goods‐sector capital and labor inputs during 1964‐1991. Fernald (1999) accessed the links between road services and productivity and found that industries that intensively used roads often witnessed a faster productivity growth increase when the stock of roads increased, using industry data in the U.S. between 1953‐1989. Canning and Bennathan (2000), using an aggregate production function, found that infrastructure, as complementary to physical and human capital, enhances production capacity.  Röller and Waverman (2001) found a positive causal link between telecommunication infrastructure and economic development using data from 21 OECD countries spanning the years 1970‐1990 with a micro‐model endogenizing telecommunication investment and a macro‐growth equation, after 

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controlling for country‐specific fixed effects and nonlinear effects caused by network externalities. Albiman and Sulong (2016) showed that mobile phone and internet were main economic growth drivers in the long run using data in 45 Sub‐Saharan African countries from 1990 to 2014. 

Infrastructure can contribute to productivity and economic growth through several channels: 

Infrastructure  can  lower  production  costs.  Seethepalli  et  al.  (2008)  found  that telecommunications,  electricity,  roads,  water,  and  sanitation  have  significant  positive impact  on  economic  growth  in  East  Asia,  after  controlling  human  capital  and  total investment.  Similarly,  Straub  and  Terada‐Hagiwara’s  study  (2010)  showed  the  growth rate of these infrastructure stocks promotes economic growth in most countries in East Asia and South Asia. For production, electricity is often a major constraint in developing countries.  Dollar  et  al.  (2005)  showed  that  the  inconsistent  power  supply  has  strong negative impacts on productivity using firm level survey data. Firms often have to rely on their own generators to supplement the unreliable public electricity supply. However, the cost of maintaining a power generator is often high and burdensome, especially for small and medium firms, where a large share of the poor and vulnerable are employed. Hallaert et al. (2011) found electricity supply is a major constraint to trade expansion in developing countries.   

Infrastructure  can  lower  transactions  costs.  Limao  and  Venables  (2001)  showed  poor infrastructure accounts for more than 40 percent of transport costs. Radelet and Sachs (1998) found that a doubling of the shipping cost is associated with slower annual growth of slightly more than half of one percentage point. Cordella and Simon (1997) found that infrastructure can reduce transaction costs (including the costs for gathering information, evaluating alternative options, negotiating, and contracting) by reducing time and cost in communication and information exchange and by flattening the organizational structure to reduce information flux and coordination needs.  Lakshmanan (2011) suggested that time  and  cost  savings  due  to  transport  infrastructure  improvement  can  better  link product  and  factor markets,  promote  inter‐regional  trade  and  specialization,  increase returns to scale, and reallocate economic activities.  

Infrastructure can increase total factor productivity. Good infrastructure can increase 

efficiency of conventional inputs (Duggal et al., 1999). Interconnections and 

complementarities between infrastructures help improve service efficiency and support 

innovative technologies adoption (Bottini et al., 2012). Based on a large‐scale firm‐level 

survey data from China, Wan and Zhang (2017) explored the causality between 

infrastructure and firm total factor productivity, and concluded that roads, 

telecommunication servers, and cable promote firm productivity. In addition to the 

conventional productivity effect, Fay et al. (2011) found that infrastructure is likely to 

condition the efficiency of many key areas of productive factors, such as the costs of 

investment adjustment, the durability of private capital, and both demand for and 

supply of health and education services. Dam (2007) showed that the rule of law is 

important to unlocking the developing world's full growth potential. 

 

Infrastructure services can “crowd in” other productive inputs. Calderón and Servén 

(2014) suggested an increase in infrastructure stock or improvement in infrastructure 

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can indirectly crowd in other inputs owing to the accompanying rise in their marginal 

productivity, and this indirect effect may take place instantaneously (for variable inputs 

in elastic supply) or over time (for fixed inputs such as human and non‐infrastructure 

physical capital). Infrastructure, being a key element of the business environment, 

conditions individual firms’ transaction and marginal return on investment.3  Wheeler 

and Mody (1992) and Richaud et al. (1999) provided evidence that infrastructure can 

crowd in foreign direct investment, an important element for growth in less developed 

countries. Eden and Kraay (2014) found that an extra dollar of public investment can 

raise private investment by roughly two dollars, and output by 1.5 dollars, based on data 

from 39 low‐income countries. 

The magnitude of contribution of infrastructure to productivity and output varies. Various 

factors are at play. Calderón et al. (2015) found that the long‐run output elasticity of 

infrastructure ranges from 0.07 to 0.1, using a synthetic index combining power, transport and 

telecommunications infrastructure as one of the inputs in a production function, based on a 

large data set covering 88 countries spanning the years 1960–2000. Their results suggest that 

the marginal productivity of infrastructure is associated with the ratio of aggregate 

infrastructure to output. Calderón and Servén (2008), drawing from data of 100 countries over 

1960‐2005, found that infrastructure development makes, on average, a smaller contribution to 

growth in Sub‐Saharan Africa than in other regions – just 0.7 percent per annum. This is related 

to the severe deterioration of the quality of infrastructure services in the region ‐ while the 

expansion in infrastructure stocks raises the growth rate by 1.2 percent per annum, the 

deterioration of the quality of infrastructure services reduces the growth rate by 0.5 percent per 

annum. Bottini et al. (2012) suggested that enhancing service efficiency and supporting 

innovative technologies adoption can improve the contribution of infrastructure to total factor 

productivity through better interconnection and stronger complementarities.  

The relationship between infrastructure and economic growth is not linear. Hurlin (2006) found that returns to infrastructure exhibit threshold effects and that the highest marginal productivity of investment is found when a network is sufficiently developed but not completely saturated. For example, road construction may have limited effects until it links several locations. After the establishment of a minimum road network, the marginal productivity is high for the new road construction extending the network before congestions kick in (Fernald, 1999). Henckel and McKibbin (2017) pointed out that the economic benefit from transport infrastructure is nonlinear because of network externalities, reflecting the decreasing benefits from additional highway construction to an existing efficient transport network. Telecommunications investment has strong externality. A subscriber’s welfare increases with the increase of the number of people who have access to the network, until reaching the saturation point. Röller and Waverman (2001) found that the impact of telecommunications infrastructure on output is substantially higher in countries where penetration approaches universal coverage. 

 

Infrastructure and global value chains 

                                                            3 See Lin, J. Y. (2011). 

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Infrastructure development includes two main stages. The first stage is the development of 

transport infrastructure. It significantly lowers transport costs and made it feasible to spatially 

separate production and consumption. Production becomes specialized and clustered in large 

scale (Florida, 2005). The second stage is the development of communication infrastructure. It 

significantly lowers coordination costs and makes it feasible for firm specific knowledge and 

know‐how to be shared across national borders (Baldwin, 2011).  

In today’s world, with the drastic decline of transport costs and communication costs, the 

potential contribution of infrastructure to productivity and growth is magnified. The 

infrastructure improvement can not only contribute to growth through lowering production 

costs and transaction costs, increasing total factor productivity, and crowding in other 

productive factors, but also change the boundary of production and reshape the economy 

(Lewis and Bloch, 1998; McCann and Shefer, 2004). Yu (2017) found that infrastructure 

improvement plays a crucial role in the increasing economic cooperation and integration 

between East Asian countries. The transportation and communication technology revolution has 

redefined the function of time and distance.  The interconnectedness across firms or sectors 

multiplies and intensifies. 4  

The separation of stages of production, or tasks instead of the full products, which is profitable 

due to the large differences of wages, land prices, and advantageous policies between 

developed and developing countries, opens new doors for developing countries to specialize in 

specific niches of the global value chains. It enables an economy to develop its comparative 

advantages, including latent comparative advantages, potentially at an earlier stage through 

focusing on a special niche in the global value chains.5 Countries become increasingly 

interdependent through supply chain trade, as they specialize in tasks and business functions 

rather than products. Products at different stages of value added may be imported, exported, 

and re‐exported multiple times. In 2009, world exports of intermediate goods exceeded the 

combined export values of final and capital goods for the first time, representing 51% of non‐

fuel merchandise exports (WTO and IDE‐JETRO, 2011). 

Global value chain integration can increase domestic value added. As indicated by Kowalski et al. 

(2015), global value chain participation can increase domestic value added embodied in a 

country’s exports, enhance the sophistication of the export bundle, and improve diversification 

of export products. Weinberger and Lumpkin (2007) stated that integrating into the horticulture 

global value chain offers opportunities for the least developed countries to alleviate poverty by 

increasing income and creating employment. Kummritz et al. (2017) found both backward and 

forward global value chain participation can lead to growth of domestic value added, based on a 

data set covering 61 countries and 34 industries between 1995 and 2011. Gonzalez (2016) found 

that using foreign value added is one of the most important factors that contribute to growth in 

domestic value added in exports. In ASEAN countries, the total domestic value added in exports 

increased nearly four times during the period of 1995‐2011. According to the Global Value 

Chains Development Report (World Bank et al., 2017), the information and communication 

                                                            4 See Gereffi and Luo (2015) for more discussion. 5 See Lin and Monga (2010) and Lin (2012b) for a thorough discussion on the identification of comparative advantages.

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technology industry in the U.S. and China has experienced an increased rate of return in labor or 

capital by participating in the global value chains.  

The participation in global value chains can be a window of opportunities for developing 

countries to move up the ladder in the production structure by specializing in the niches where 

they have comparative advantage. Following the metaphor of “ladder” instead of a “chain” used 

in a recent joint report by OECD, WTO and World Bank Group, “the disaggregation of production 

into separate stages allows their firms not only to find their place on the ladder, but to move up 

the rungs as their capabilities improve”.6 Entering global value chains is a way to "denationalize 

comparative advantages", and it has the potential to enhance developing countries’ export 

opportunities and their competitiveness (Del Prete et al., 2017). It allows developing countries 

to specialize in narrow niches without the need of first building an entire value chain from 

scratch, as other countries, such as Japan and the Republic of Korea, experienced in the last 

century. A small developing country with abundant unskilled labor can join the value chain of 

garment manufacturing, specializing in only one small niche such as producing buttons before 

they can have the entire assembly line.  

Participation in global value chains can therefore encourage upward movement by providing the 

platform to reward skills, learning, and innovation.  Gereffi and Fernandez‐Stark (2016) drew an 

upgrading trajectory in a global value chain, in which countries follow the steps of entering the 

value chain first by offering the most basic products or services, then providing more 

sophisticated business, subsequently to knowledge activities, offering a large spectrum of 

products or services, and finally specializing in vertical industries. Costa Rica has experienced 

product upgrading in medical devices value chains, as shown by Bamber and Gereffi (2013), with 

its higher tech medical devices accounting for more than half of total medical device exports in 

2011, compared with 90% shared by low‐tech disposable devices in 2002. Simultaneously, the 

country also witnessed significant growth of FDI in higher‐level technology medical devices 

sectors.  

The potential benefit of tapping in the benefit of structural upgrading through the participation 

in the value chains is large.  Development is path dependent. Several economies, including 

China, are moving up the value chain and releasing millions of labor intensive jobs (Lin, 2012a). 

Seizing this opportunity to specialize in the niches following the latent comparative advantages 

can set an economy on a right path of structural upgrades. Successful cases can be found in 

countries such as Chile in exporting engineering services related to mining, India in exporting 

pharmaceutical R&D, and Uruguay in exporting sophisticated expertise on cattle traceability 

(Gereffi and Fernandez‐Stark, 2016).  

Improving infrastructure, including hard infrastructure and soft infrastructure, is a necessary 

condition for reaping the benefit of the participation in the global value chains to upgrade the 

economic structure. Reliable infrastructure to connect supply, efficient movement of goods and 

services across borders, fast and reliable information transfer, and sufficiently low coordination 

costs are prerequisites for participating in global value chains.  Yi (2003) indicated that tariffs 

have large and nonlinear impact on global trade, especially for semi‐finished goods in the value 

                                                            6 See OECD, WTO, & World Bank Group. (2014). 

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chains as they need to cross borders several times. A recent Brookings report (World Bank et al., 

2017) showed a clear relationship between better logistics performance and deeper 

involvement in global value chains using the World Bank’s Logistics Performance Indicator. 

While not all countries with good logistics are deeply involved in global value chains, no 

countries with poor logistics performance are central to global value chains (figure 2). According 

to World Economic Forum (2014), well‐developed infrastructure not only reduces the distance 

between regions but also integrates national markets and connects them to other economies. 

The proximity of industries and businesses favors cost reduction and productivity improvement, 

allowing firms in the region to share a similar labor pool and enjoy knowledge spillovers, and 

enables further clustering and agglomeration (Fujita et al., 1999; Fujita and Thisse, 2013). 

Figure 2: Relationship between the Logistics Performance Index and a centrality measure of country involvement in global value chains 

 

Cited from World Bank et al. (2017), and Diakantoni et al. (2017).  Based on COMTRADE and World Bank data. 

Note: The centrality indicator ranks a country’s centrality to global value chains, taking into account direct and indirect trade flows to and from trading partners in the global production network. 

 

Challenges for the least developed countries 

Participating and competing in global value chains have become largely inevitable. Local firms 

are collaborating directly or indirectly with foreign firms in the same industry or with their 

upstream or downstream partners; at the same time, local firms are competing with a growing 

number of foreign firms in the local as well as international markets.  As the natural barriers of 

distance to trade are diminished, countries may benefit or lose in the new global arena. To 

survive, they need to improve product quality and efficiency of operations. Infrastructure 

required for firms in least developed countries, which mainly target local markets with small 

amount of transactions, used to be rudimentary. However, when they attempt to join the global 

value chains, where business transactions are often long distance and large in quantity and 

value, more sophisticated and various types of infrastructures become necessary (Lin, 2011). 

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Countries with poor infrastructure and distant to the economic centers can be marginalized and 

locked from the opportunity of participating in the global value chains and, consequently, the 

opportunity of upgrading the economic structure.  

Developing countries face daunting challenges, ranging from the accessibility and quality of 

transportation, telecommunication, and water supply, to institutions and regulations to 

facilitate trade. The large infrastructure gaps, particularly for the least developed countries, 

might deprive them of the opportunity to upgrade their economic structure through 

participation in global value chains. World Bank (2017) indicated that the performance of Sub‐

Sahara Africa’s infrastructure currently ranks below all other developing regions: road density 

has declined over the past 20 years in Africa, and only 35% of the population has access to 

electricity, with rural access rates less than one‐third urban ones. The report estimated that 

closing the infrastructure quantity and quality gap in Sub‐Sahara Africa relative to the best 

performers in the world could increase the growth of GDP per capita in the region by 2.6 

percent per year, or 1.7 percent per year if it were to close the gap with the median of the rest 

of the developing world.  

Transport costs can be prohibitively high. Transport costs, according to developing‐country 

suppliers, remain the main obstacle to entering, establishing, or moving up in global value 

chains (OECD and WTO, 2013).  Transport prices for most African landlocked countries range 

from 15 to 20 percent of import costs, approximately two to three times more than in most 

developed countries (Teravaninthorn and Raballand, 2009). According to a recent IMF report 

(IMF, 2015), the quality of infrastructure in Africa is about half that found elsewhere in the 

world, credit‐to‐GDP ratios about a third of ratios elsewhere, and tariffs on average four times 

higher than elsewhere. The slow and unpredictable land transport keeps most of Sub‐Saharan 

Africa out of the higher value added segments of the value chains, including electronics (Christ 

and Ferrantino, 2011).  

Firms in the least developed countries are more likely to suffer from the burden of high 

transaction costs. Besides conducive business environment and strong human capital, efficient 

and reliable infrastructure services (including telecoms, internet, express service delivery, and 

customs clearances) for coordinating the dispersed production become the essential condition 

of the location choice in the production supply chain. With below‐average infrastructure quality 

in most countries and the lack of regional co‐ordination of trade facilitation effort, South Asia 

has the highest intra‐regional trade costs after the African regions (Kowalski et al., 2015). 

Ahmed et al. (2010) noted high transaction costs are bottlenecks for South Asian countries to 

promote regional or international trade, with 140 to 200 signatures required for trading 

between India and Nepal, and over four days of waiting time for trucks to cross the border 

between Bangladesh and India. Facilitating trade by focusing on publication of customs 

information, notifications, advance rulings, documentation requirements, and international 

standards can reduce trade costs mostly in less developed counties (Moïsé and Sorescu, 2013).  

High logistic costs due to weak supply chains are often another barrier for the least developed 

countries. Lacking reliable supply chains, firms in less developed countries encounter much higher 

logistic costs and are virtually eliminated from just‐in‐time production. High inventory costs post 

a double penalty for firms participating in global manufacturing value chains with extra logistics 

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costs on both inputs and exports. The inefficient and unreliable clearance processes could even 

render  the  participation  in  global  value  chains  impossible.  As  a  result,  the  off‐shoring  and 

industrialization after  the  ICT  revolution  tend  to concentrate  in  select parts of  the developing 

world, of which a significant share is in East Asia, followed by select countries in Latin America 

and East and Central Europe.   

Small and medium enterprises (SMEs) stand for the majority of firms in least development 

countries. According to Gereffi and Fernandez‐Stark (2016), market access, training, and 

collaboration and cooperation are major constraints for SMEs to sustainably enter value chains. 

Infrastructure such as transportation and ICT conditions the linkages between producers and 

buyers in value chains and affects the adoption of new technologies to meet the international 

market requirements. Collaboration and cooperation refer to both horizontal coordination 

between producers and vertical interaction between segments of the value chains, with the 

former facilitating economies of scale and providing opportunities for more value added, and 

the latter helping sharing knowledge along the chain and upgrading.  

SMEs are even more vulnerable to supply chain inefficiencies compared with large firms. For 

SMEs, related to their small scale, logistics costs are disproportionately higher—industrial firms 

with fewer than 250 workers on average having logistics cost of some 15% of overall revenue for 

the business unit, more than twice that of firms with over 250 workers (Straube et al., 2013). 

Small exporters and importers tend to be more affected by a lack of transparency in clearance 

processes. They have lower economies of scale, therefore higher inventory costs, which can be 

punitively high in countries with poor logistics performance. Many of them are often forced to 

confine their business activities to the geographical area close to their production site. For the 

SMEs in remote areas, the lack of continuity of logistics services beyond the main gateway could 

make access to global value chains prohibitive.  

Evidence shows that insufficient infrastructure has put obstacles for less developed countries to 

integrate into global value chains and upgrade to higher segments on the chains. According to 

Gereffi (2015), in some Central American countries, inadequate infrastructure investment in wet 

processing  plants  limited  the  abilities  of  small  producers  to  produce  premium  coffee, 

consequently losing the opportunity to capture the price premiums in the global value chain. A 

report  from AfDB et  al.  (2014)  suggested  that many African  countries  suffer  from  insufficient 

infrastructure.  Lack  of  infrastructure  and  burdensome  border  procedures,  accompanied  with 

geographical remoteness, mean that in countries in Sub‐Saharan African, on average it takes 38 

days to import and 32 days for exporting across borders. As a result, firms face high costs and 

uncertainty of supply (World Bank, 2012b; Kowalski et al., 2015). Poor infrastructure, especially 

lack of access to energy, and inadequate skilled workforce are the main barriers for Burkina Faso 

to participate in the global value chains.  In the Republic of Congo, the economy has not been able 

to build on the comparative advantages in natural resources and move up the value chains due 

to  the  lack  of  decent  infrastructure,  such  as  transport  and  energy,  as  well  as  the  lagging 

technology,  less  qualified  labor,  and  uncongenial  business  environment.  In  Tunisia,  while  the 

manufacturing sector has benefited from participation in the global value chain particularly, its 

further  development  and  structural  upgrades  are  still  handicapped  by  logistics,  transport, 

unbalanced  distribution  of  information  and  communication  technologies,  and  technology 

transfers.  

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The less developed countries with underdeveloped infrastructure, low investment rates, and 

low per‐capita incomes can experience a boost in trade flows and benefit from infrastructure 

development. The development experiences in Africa and Asia, such as light‐manufacturing in 

Ethiopia, horticulture in Kenya, readymade garments in Cambodia, and textiles in Pakistan have 

already highlighted these countries’ tremendous potential for productive job creation, providing 

they tackle the “hard” and “soft” infrastructure constraints to help realize this latent 

comparative advantage. 

 

Conclusions 

Improving  infrastructure  to meet  the demand  in  today’s  economy  is  a must.  The demand  for 

infrastructure includes not only the traditional facilities but also the new ones that better respond 

to  the  rapidly  evolving  needs  and  provide  quicker  and  more  reliable  services.  While  the 

“traditional”  infrastructure,  such  as  roads,  railways,  electricity,  water  and  sanitation,  is  still 

fundamental, “new” infrastructure, such as highways, high‐speed trains, and broad‐band internet 

has become necessary for an economy to fully participate in the global value chains and to move 

up the ladder of the economic structure.  

Infrastructure is not everything, but without good infrastructure, most potential will be limited. 

Improving infrastructure is not only important for growth by boosting firm performance, but also 

facilitating public services delivery and contributing to inclusiveness and long‐term development. 

The lack of access to basic services undermines living standards for poor people and limits their 

ability to materialize their full potentials. The inequality of opportunity and inequality of outcomes 

intertwine  and  perpetuate  and  prevent  poor  people  from  accessing  infrastructure  services. 

Alesina et al.  (1999) argued that more unequal societies devote  less effort  to  the provision of 

public  goods,  including  infrastructure.  Estache  et  al.  (2002)  showed  that  income  inequality 

adversely  affects  access  to  the  internet,  which  aggravates  the  information  asymmetry  and 

deprives  the  poor  from  equal  opportunities.  Some  studies,  for  example  Gonzalvez  (2016), 

suggested that participation in global value chains can be an engine of job creation: forward global 

value chain jobs—domestic jobs linked to the production of intermediate products traded within 

value chains—have grown over six times faster than total jobs in 1996‐2011. 

Infrastructure is a necessary but not sufficient condition for growth. The extent to which 

infrastructure improvement contributes to growth of a specific industry or location depends on 

their specific characteristics and the business environment that they are in. To the extent that 

suboptimal infrastructure investment constrains other investment, it constrains growth 

(Newbery, 2012). More infrastructure may not necessarily cause more growth if the binding 

constraints lie elsewhere or the type or quality of infrastructure investment does not match the 

demand.7 Building a bridge to nowhere will not add any value.  

The constraints of infrastructure, or the benefit from the improvement of a specific type of 

infrastructure, vary across industries and firms as well as across regions in the same country. For 

example, a new expressway linking two locations might benefit one more than the other 

                                                            7 See more discussions in Canning, D., & Pedroni, P. (2008).  

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depending on their production and geo‐economic structures. Improvement in connectivity and 

market accessibility might lead to stronger clustering and agglomeration, which tends to favor 

the economic centers more than the periphery. Similarly, simplification of the customs 

clearance might benefit firms specializing in foreign trade or the economy in general, but at the 

same time raise the competition for those engaging in import substitution industries or focusing 

on the domestic market.  

Infrastructure  is not a sufficient condition  for benefiting  from participation  in  the global value 

chains,  and  participation  in  the  global  value  chain  is  not  a  sufficient  condition  for  structural 

upgrades. The “smile curve” is deep as value added is high at the pre‐ and post‐manufacturing 

stages.  Based  on  a  sample  of more  than  2 million  firms  in  the  European Union  in  2015,  the 

empirical results from Rungi and Del Prete (2017) confirmed a nonlinear U‐shaped relationship at 

firm‐level between the value added generated and position on a productive sequence. Developing 

countries, given the mix of their factor endowment, often enter global value chains first at the 

low value‐added stage (assembly or production stage) and subsequently seek to move towards 

higher value‐adding activities. To what extent they can increase their domestic value‐added and 

move up the ladder depends on a variety of factors. With good infrastructure, opportunity is there 

but success is not guaranteed; however, without good infrastructure, the economy will certainly 

be deprived of the opportunity to materialize its latent advantage at the global scale early on.  

The public‐good nature of infrastructure calls for support from the governments, and partnership 

between  the  public  and  private  sectors  in  many  areas  is  essential.  When  the  infrastructure 

investment crosses national borders, regional and global collaborations are essential. Concerted 

efforts between national governments and regional or international development agencies can 

play a crucial role. With the right conditions, infrastructure investment and economic growth can 

reinforce each other: good infrastructure investments can accelerate growth, while growth itself 

can generate greater demand for, and usually supply of, infrastructure.  

Infrastructure is expensive and requires extensive maintenance. The fiscal burden can be high, 

particularly for the less developed countries that face multiple challenges and at the same time 

have the most urgent needs. Focusing the investment in infrastructure in special economic zones 

or  industrial parks can be a useful approach  to  jump start  the process with  limited  resources. 

China has spent over 5 percent of GDP over the past decades in infrastructure investment, cutting 

transport costs and helping connect production centers to domestic and international consumers 

(Huang, 2017). By substituting domestic for  imported materials, China has been increasing the 

domestic content of its exports (Kee and Tang, 2015), and has become the world’s factory from a 

largely agrarian economy. The successful experience in China in the past decades shows that well‐

planned  and well‐managed  special  economic  zones with  targeted  investment  promotion  and 

catalytic development financing can help to unleash latent comparative advantages and facilitate 

integration  and  upgrading  along  the  global  value  chains.  Development  in  sectors  where  the 

economy has comparative advantages can stimulate gradual and sustained upgrading in the value 

chains and start the virtuous cycle building the ecosystem for more beneficial integration in the 

value chain for the entire economy. 

 

 

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1 Estimating poverty in the absence of consumption data: the case of Liberia Dabalen, A. L., Graham, E., Himelein, K., Mungai, R., September 2014

2 Female labor participation in the Arab world: some evidence from panel data in Morocco Barry, A. G., Guennouni, J., Verme, P., September 2014

3 Should income inequality be reduced and who should benefit? redistributive preferences in Europe

and Central Asia Cojocaru, A., Diagne, M. F., November 2014

4 Rent imputation for welfare measurement: a review of methodologies and empirical findings Balcazar Salazar, C. F., Ceriani, L., Olivieri, S., Ranzani, M., November 2014

5 Can agricultural households farm their way out of poverty? Oseni, G., McGee, K., Dabalen, A., November 2014

6 Durable goods and poverty measurement Amendola, N., Vecchi, G., November 2014

7 Inequality stagnation in Latin America in the aftermath of the global financial crisis

Cord, L., Barriga Cabanillas, O., Lucchetti, L., Rodriguez‐Castelan, C., Sousa, L. D., Valderrama, D. December 2014

8 Born with a silver spoon: inequality in educational achievement across the world

Balcazar Salazar, C. F., Narayan, A., Tiwari, S., January 2015

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9 Long‐run effects of democracy on income inequality: evidence from repeated cross‐sections

Balcazar Salazar,C. F., January 2015

10 Living on the edge: vulnerability to poverty and public transfers in Mexico Ortiz‐Juarez, E., Rodriguez‐Castelan, C., De La Fuente, A., January 2015

11 Moldova: a story of upward economic mobility

Davalos, M. E., Meyer, M., January 2015

12 Broken gears: the value added of higher education on teachers' academic achievement Balcazar Salazar, C. F., Nopo, H., January 2015

13 Can we measure resilience? a proposed method and evidence from countries in the Sahel

Alfani, F., Dabalen, A. L., Fisker, P., Molini, V., January 2015

14 Vulnerability to malnutrition in the West African Sahel Alfani, F., Dabalen, A. L., Fisker, P., Molini, V., January 2015

15 Economic mobility in Europe and Central Asia: exploring patterns and uncovering puzzles Cancho, C., Davalos, M. E., Demarchi, G., Meyer, M., Sanchez Paramo, C., January 2015

16 Managing risk with insurance and savings: experimental evidence for male and female farm

managers in the Sahel Delavallade, C., Dizon, F., Hill, R., Petraud, J. P., el., January 2015

17 Gone with the storm: rainfall shocks and household well‐being in Guatemala

Baez, J. E., Lucchetti, L., Genoni, M. E., Salazar, M., January 2015

18 Handling the weather: insurance, savings, and credit in West Africa De Nicola, F., February 2015

19 The distributional impact of fiscal policy in South Africa

Inchauste Comboni, M. G., Lustig, N., Maboshe, M., Purfield, C., Woolard, I., March 2015

20 Interviewer effects in subjective survey questions: evidence from Timor‐Leste Himelein, K., March 2015

21 No condition is permanent: middle class in Nigeria in the last decade

Corral Rodas, P. A., Molini, V., Oseni, G. O., March 2015

22 An evaluation of the 2014 subsidy reforms in Morocco and a simulation of further reforms Verme, P., El Massnaoui, K., March 2015

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23 The quest for subsidy reforms in Libya Araar, A., Choueiri, N., Verme, P., March 2015

24 The (non‐) effect of violence on education: evidence from the "war on drugs" in Mexico Márquez‐Padilla, F., Pérez‐Arce, F., Rodriguez Castelan, C., April 2015

25 “Missing girls” in the south Caucasus countries: trends, possible causes, and policy options Das Gupta, M., April 2015

26 Measuring inequality from top to bottom Diaz Bazan, T. V., April 2015

27 Are we confusing poverty with preferences? Van Den Boom, B., Halsema, A., Molini, V., April 2015

28 Socioeconomic impact of the crisis in north Mali on displaced people (Available in French)

Etang Ndip, A., Hoogeveen, J. G., Lendorfer, J., June 2015 29 Data deprivation: another deprivation to end

Serajuddin, U., Uematsu, H., Wieser, C., Yoshida, N., Dabalen, A., April 2015 30 The local socioeconomic effects of gold mining: evidence from Ghana

Chuhan‐Pole, P., Dabalen, A., Kotsadam, A., Sanoh, A., Tolonen, A.K., April 2015 31 Inequality of outcomes and inequality of opportunity in Tanzania

Belghith, N. B. H., Zeufack, A. G., May 2015

32 How unfair is the inequality of wage earnings in Russia? estimates from panel data Tiwari, S., Lara Ibarra, G., Narayan, A., June 2015

33 Fertility transition in Turkey—who is most at risk of deciding against child arrival? Greulich, A., Dasre, A., Inan, C., June 2015

34 The socioeconomic impacts of energy reform in Tunisia: a simulation approach Cuesta Leiva, J. A., El Lahga, A., Lara Ibarra, G., June 2015

35 Energy subsidies reform in Jordan: welfare implications of different scenarios

Atamanov, A., Jellema, J. R., Serajuddin, U., June 2015

36 How costly are labor gender gaps? estimates for the Balkans and Turkey Cuberes, D., Teignier, M., June 2015

37 Subjective well‐being across the lifespan in Europe and Central Asia Bauer, J. M., Munoz Boudet, A. M., Levin, V., Nie, P., Sousa‐Poza, A., July 2015

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38 Lower bounds on inequality of opportunity and measurement error Balcazar Salazar, C. F., July 2015

39 A decade of declining earnings inequality in the Russian Federation Posadas, J., Calvo, P. A., Lopez‐Calva, L.‐F., August 2015

40 Gender gap in pay in the Russian Federation: twenty years later, still a concern Atencio, A., Posadas, J., August 2015

41 Job opportunities along the rural‐urban gradation and female labor force participation in India Chatterjee, U., Rama, M. G., Murgai, R., September 2015

42 Multidimensional poverty in Ethiopia: changes in overlapping deprivations Yigezu, B., Ambel, A. A., Mehta, P. A., September 2015

43 Are public libraries improving quality of education? when the provision of public goods is not enough

Rodriguez Lesmes, P. A., Valderrama Gonzalez, D., Trujillo, J. D., September 2015

44 Understanding poverty reduction in Sri Lanka: evidence from 2002 to 2012/13 Inchauste Comboni, M. G., Ceriani, L., Olivieri, S. D., October 2015

45 A global count of the extreme poor in 2012: data issues, methodology and initial results Ferreira, F.H.G., Chen, S., Dabalen, A. L., Dikhanov, Y. M., Hamadeh, N., Jolliffe, D. M., Narayan, A., Prydz, E. B., Revenga, A. L., Sangraula, P., Serajuddin, U., Yoshida, N., October 2015

46 Exploring the sources of downward bias in measuring inequality of opportunity Lara Ibarra, G., Martinez Cruz, A. L., October 2015

47 Women’s police stations and domestic violence: evidence from Brazil Perova, E., Reynolds, S., November 2015

48 From demographic dividend to demographic burden? regional trends of population aging in Russia Matytsin, M., Moorty, L. M., Richter, K., November 2015

49 Hub‐periphery development pattern and inclusive growth: case study of Guangdong province Luo, X., Zhu, N., December 2015

50 Unpacking the MPI: a decomposition approach of changes in multidimensional poverty headcounts Rodriguez Castelan, C., Trujillo, J. D., Pérez Pérez, J. E., Valderrama, D., December 2015

51 The poverty effects of market concentration Rodriguez Castelan, C., December 2015

52 Can a small social pension promote labor force participation? evidence from the Colombia Mayor program Pfutze, T., Rodriguez Castelan, C., December 2015

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53 Why so gloomy? perceptions of economic mobility in Europe and Central Asia Davalos, M. E., Cancho, C. A., Sanchez, C., December 2015

54 Tenure security premium in informal housing markets: a spatial hedonic analysis Nakamura, S., December 2015

55 Earnings premiums and penalties for self‐employment and informal employees around the world Newhouse, D. L., Mossaad, N., Gindling, T. H., January 2016

56 How equitable is access to finance in turkey? evidence from the latest global FINDEX Yang, J., Azevedo, J. P. W. D., Inan, O. K., January 2016

57 What are the impacts of Syrian refugees on host community welfare in Turkey? a subnational poverty analysis Yang, J., Azevedo, J. P. W. D., Inan, O. K., January 2016

58 Declining wages for college‐educated workers in Mexico: are younger or older cohorts hurt the

most? Lustig, N., Campos‐Vazquez, R. M., Lopez‐Calva, L.‐F., January 2016

59 Sifting through the Data: labor markets in Haiti through a turbulent decade (2001‐2012) Rodella, A.‐S., Scot, T., February 2016

60 Drought and retribution: evidence from a large‐scale rainfall‐indexed insurance program in Mexico

Fuchs Tarlovsky, Alan., Wolff, H., February 2016

61 Prices and welfare Verme, P., Araar, A., February 2016

62 Losing the gains of the past: the welfare and distributional impacts of the twin crises in Iraq 2014 Olivieri, S. D., Krishnan, N., February 2016

63 Growth, urbanization, and poverty reduction in India Ravallion, M., Murgai, R., Datt, G., February 2016

64 Why did poverty decline in India? a nonparametric decomposition exercise Murgai, R., Balcazar Salazar, C. F., Narayan, A., Desai, S., March 2016

65 Robustness of shared prosperity estimates: how different methodological choices matter Uematsu, H., Atamanov, A., Dewina, R., Nguyen, M. C., Azevedo, J. P. W. D., Wieser, C., Yoshida, N., March 2016

66 Is random forest a superior methodology for predicting poverty? an empirical assessment Stender, N., Pave Sohnesen, T., March 2016

67 When do gender wage differences emerge? a study of Azerbaijan's labor market Tiongson, E. H. R., Pastore, F., Sattar, S., March 2016

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68 Second‐stage sampling for conflict areas: methods and implications Eckman, S., Murray, S., Himelein, K., Bauer, J., March 2016

69 Measuring poverty in Latin America and the Caribbean: methodological considerations when estimating an empirical regional poverty line Gasparini, L. C., April 2016

70 Looking back on two decades of poverty and well‐being in India Murgai, R., Narayan, A., April 2016

71 Is living in African cities expensive? Yamanaka, M., Dikhanov, Y. M., Rissanen, M. O., Harati, R., Nakamura, S., Lall, S. V., Hamadeh, N., Vigil Oliver, W., April 2016

72 Ageing and family solidarity in Europe: patterns and driving factors of intergenerational support Albertini, M., Sinha, N., May 2016

73 Crime and persistent punishment: a long‐run perspective on the links between violence and chronic poverty in Mexico Rodriguez Castelan, C., Martinez‐Cruz, A. L., Lucchetti, L. R., Valderrama Gonzalez, D., Castaneda Aguilar, R. A., Garriga, S., June 2016

74 Should I stay or should I go? internal migration and household welfare in Ghana Molini, V., Pavelesku, D., Ranzani, M., July 2016

75 Subsidy reforms in the Middle East and North Africa Region: a review Verme, P., July 2016

76 A comparative analysis of subsidy reforms in the Middle East and North Africa Region Verme, P., Araar, A., July 2016

77 All that glitters is not gold: polarization amid poverty reduction in Ghana Clementi, F., Molini, V., Schettino, F., July 2016

78 Vulnerability to Poverty in rural Malawi Mccarthy, N., Brubaker, J., De La Fuente, A., July 2016

79 The distributional impact of taxes and transfers in Poland Goraus Tanska, K. M., Inchauste Comboni, M. G., August 2016

80 Estimating poverty rates in target populations: an assessment of the simple poverty scorecard and alternative approaches Vinha, K., Rebolledo Dellepiane, M. A., Skoufias, E., Diamond, A., Gill, M., Xu, Y., August 2016

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81 Synergies in child nutrition: interactions of food security, health and environment, and child care Skoufias, E., August 2016

82 Understanding the dynamics of labor income inequality in Latin America Rodriguez Castelan, C., Lustig, N., Valderrama, D., Lopez‐Calva, L.‐F., August 2016

83 Mobility and pathways to the middle class in Nepal Tiwari, S., Balcazar Salazar, C. F., Shidiq, A. R., September 2016

84 Constructing robust poverty trends in the Islamic Republic of Iran: 2008‐14 Salehi Isfahani, D., Atamanov, A., Mostafavi, M.‐H., Vishwanath, T., September 2016

85 Who are the poor in the developing world? Newhouse, D. L., Uematsu, H., Doan, D. T. T., Nguyen, M. C., Azevedo, J. P. W. D., Castaneda Aguilar, R. A., October 2016

86 New estimates of extreme poverty for children Newhouse, D. L., Suarez Becerra, P., Evans, M. C., October 2016

87 Shedding light: understanding energy efficiency and electricity reliability

Carranza, E., Meeks, R., November 2016

88 Heterogeneous returns to income diversification: evidence from Nigeria Siwatu, G. O., Corral Rodas, P. A., Bertoni, E., Molini, V., November 2016

89 How liberal is Nepal's liberal grade promotion policy? Sharma, D., November 2016

90 Pro‐growth equity: a policy framework for the twin goals Lopez‐Calva, L. F., Rodriguez Castelan, C., November 2016

91 CPI bias and its implications for poverty reduction in Africa Dabalen, A. L., Gaddis, I., Nguyen, N. T. V., December 2016

92 Building an ex ante simulation model for estimating the capacity impact, benefit incidence, and cost effectiveness of child care subsidies: an application using provider‐level data from Turkey Aran, M. A., Munoz Boudet, A., Aktakke, N., December 2016

93 Vulnerability to drought and food price shocks: evidence from Ethiopia Porter, C., Hill, R., December 2016

94 Job quality and poverty in Latin America Rodriguez Castelan, C., Mann, C. R., Brummund, P., December 2016

95 With a little help: shocks, agricultural income, and welfare in Uganda Mejia‐Mantilla, C., Hill, R., January 2017

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96 The impact of fiscal policy on inequality and poverty in Chile Martinez Aguilar, S. N., Fuchs Tarlovsky, A., Ortiz‐Juarez, E., Del Carmen Hasbun, G. E., January 2017

97 Conditionality as targeting? participation and distributional effects of conditional cash transfers Rodriguez Castelan, C., January 2017

98 How is the slowdown affecting households in Latin America and the Caribbean? Reyes, G. J., Calvo‐Gonzalez, O., Sousa, L. D. C., Castaneda Aguilar, R. A., Farfan Bertran, M. G., January 2017

99 Are tobacco taxes really regressive? evidence from Chile Fuchs Tarlovsky, A., Meneses, F. J., March 2017

100 Design of a multi‐stage stratified sample for poverty and welfare monitoring with multiple objectives: a Bangladesh case study Yanez Pagans, M., Roy, D., Yoshida, N., Ahmed, F., March 2017

101 For India's rural poor, growing towns matter more than growing cities Murgai, R., Ravallion, M., Datt, G., Gibson, J., March 2017

102 Leaving, staying, or coming back? migration decisions during the northern Mali conflict Hoogeveen, J. G., Sansone, D., Rossi, M., March 2017

103 Arithmetics and Politics of Domestic Resource Mobilization Bolch, K. B., Ceriani, L., Lopez‐Calva, L.‐F., April 2017

104 Can Public Works Programs Reduce Youth Crime? Evidence from Papua New Guinea’s Urban Youth Employment Project Oleksiy I., Darian N., David N., Sonya S., April 2017

105 Is Poverty in Africa Mostly Chronic or Transient? Evidence from Synthetic Panel Data Dang, H.‐A. H., Dabalen, A. L., April 2017

106 To Sew or Not to Sew? Assessing the Welfare Effects of the Garment Industry in Cambodia Mejía‐Mantilla, C., Woldemichael, M. T., May 2017

107 Perceptions of distributive justice in Latin America during a period of falling inequality Reyes, G. J., Gasparini, L. C., May 2017

108 How do women fare in rural non‐farm economy? Fuje, H. N., May 2017

109 Rural Non‐Farm Employment and Household Welfare: Evidence from Malawi Adjognon, G. S., Liverpool‐Tasie, S. L., De La Fuente, A., Benfica, R. M., May 2017

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110 Multidimensional Poverty in the Philippines, 2004‐13: Do Choices for Weighting, Identification and Aggregation Matter? Datt, G., June 2017

111 But … what is the poverty rate today? testing poverty nowcasting methods in Latin America and the Caribbean Caruso, G. D., Lucchetti, L. R., Malasquez, E., Scot, T., Castaneda, R. A., June 2017

112 Estimating the Welfare Costs of Reforming the Iraq Public Distribution System: A Mixed Demand

Approach Krishnan, N., Olivieri, S., Ramadan, R., June 2017

113 Beyond Income Poverty: Nonmonetary Dimensions of Poverty in Uganda

Etang Ndip, A., Tsimpo, C., June 2017

114 Education and Health Services in Uganda: Quality of Inputs, User Satisfaction, and Community Welfare Levels Tsimpo Nkengne, C., Etang Ndip, A., Wodon, Q. T., June 2017

115 Rental Regulation and Its Consequences on Measures of Well‐Being in the Arab Republic of Egypt

Lara Ibarra, G., Mendiratta, V., Vishwanath, T., July 2017

116 The Poverty Implications of Alternative Tax Reforms: Results from a Numerical Application to Pakistan Feltenstein, A., Mejia‐Mantilla, C., Newhouse, D. L., Sedrakyan, G., August 2017

117 Tracing Back the Weather Origins of Human Welfare: Evidence from Mozambique?

Baez Ramirez, J. E., Caruso, G. D., Niu, C., August 2017

118 Many Faces of Deprivation: A multidimensional approach to poverty in Armenia Martirosova, D., Inan, O. K., Meyer, M., Sinha, N., August 2017

119 Natural Disaster Damage Indices Based on Remotely Sensed Data: An Application to Indonesia Skoufias, E., Strobl, E., Tveit, T. B., September 2017

120 The Distributional Impact of Taxes and Social Spending in Croatia

Inchauste Comboni, M. G., Rubil, I., October 2017

121 Regressive or Progressive? The Effect of Tobacco Taxes in Ukraine Fuchs, A., Meneses, F. September 2017

122 Fiscal Incidence in Belarus: A Commitment to Equity Analysis Bornukova, K., Shymanovich, G., Chubrik, A., October 2017

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123 Who escaped poverty and who was left behind? a non‐parametric approach to explore welfare dynamics using cross‐sections Lucchetti, L. R., October 2017

124 Learning the impact of financial education when take‐up is low Lara Ibarra, G., Mckenzie, D. J., Ruiz Ortega, C., November 2017

125 Putting Your Money Where Your Mouth Is Geographic Targeting of World Bank Projects to the Bottom 40 Percent Öhler, H., Negre, M., Smets, L., Massari, R., Bogetić, Z., November 2017

126 The impact of fiscal policy on inequality and poverty in Zambia De La Fuente, A., Rosales, M., Jellema, J. R., November 2017

127 The Whys of Social Exclusion: Insights from Behavioral Economics Hoff, K., Walsh, J. S., December 2017

128 Mission and the bottom line: performance incentives in a multi‐goal organization Gine, X., Mansuri, G., Shrestha, S. A., December 2017

129 Mobile Infrastructure and Rural Business Enterprises Evidence from Sim Registration Mandate in Niger Annan, F., Sanoh, A., December 2017

130 Poverty from Space: Using High‐Resolution Satellite Imagery for estimating Economic Well‐Being Engstrom, R., Hersh, J., Newhouse, D., December 2017

131 Winners Never Quit, Quitters Never Grow: Using Text Mining to measure Policy Volatility and its Link with Long‐Term Growth in Latin America Calvo‐Gonzalez, O., Eizmendi, A., Reyes, G., January 2018

132 The Changing Way Governments talk about Poverty and Inequality: Evidence from two Centuries of Latin American Presidential Speeches Calvo‐Gonzalez, O., Eizmendi, A., Reyes, G., January 2018

133 Tobacco Price Elasticity and Tax Progressivity In Moldova Fuchs, A., Meneses, F., February 2018

134 Informal Sector Heterogeneity and Income Inequality: Evidence from the Democratic Republic of Congo Adoho, F., Doumbia, D., February 2018

135 South Caucasus in Motion: Economic and Social Mobility in Armenia, Azerbaijan and Georgia Tiwari, S., Cancho, C., Meyer, M., February 2018

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136 Human Capital Outflows: Selection into Migration from the Northern Triangle Del Carmen, G., Sousa, L., February 2018

137 Urban Transport Infrastructure and Household Welfare: Evidence from Colombia Pfutze, T., Rodriguez‐Castelan, C., Valderrama‐Gonzalez, D., February 2018

138 Hit and Run? Income Shocks and School Dropouts in Latin America Cerutti, P., Crivellaro, E., Reyes, G., Sousa, L., February 2018

139 Decentralization and Redistribution Irrigation Reform in Pakistan’s Indus Basin Jacoby, H.G., Mansuri, G., Fatima, F., February 2018

140 Governing the Commons? Water and Power in Pakistan’s Indus Basin Jacoby, H.G., Mansuri, G., February 2018

141 The State of Jobs in Post‐Conflict Areas of Sri Lanka Newhouse, D., Silwal, A. R., February 2018

142 “If it’s already tough, imagine for me…” A Qualitative Perspective on Youth Out of School and Out of Work in Brazil Machado, A.L., Muller, M., March 2018

143 The reallocation of district‐level spending and natural disasters: evidence from Indonesia Skoufias, E., Strobl, E., Tveit, T. B., March 2018

144 Gender Differences in Poverty and Household Composition through the Life‐cycle A Global Perspective Munoz, A. M., Buitrago, P., Leroy de la Briere, B., Newhouse, D., Rubiano, E., Scott, K., Suarez‐Becerra, P., March 2018

145 Analysis of the Mismatch between Tanzania Household Budget Survey and National Panel Survey Data in Poverty & Inequality Levels and Trends Fuchs, A., Del Carmen, G., Kechia Mukong, A., March 2018

146 Long‐Run Impacts of Increasing Tobacco Taxes: Evidence from South Africa Hassine Belghith, N.B., Lopera, M. A., Etang Ndip, A., Karamba, W., March 2018

147 The Distributional Impact of the Fiscal System in Albania Davalos, M., Robayo‐Abril, M., Shehaj, E., Gjika, A., March 2018

148 Analysis Growth, Safety Nets and Poverty: Assessing Progress in Ethiopia from 1996 to 2011 Vargas Hill, R., Tsehaye, E., March 2018

149 The Economics of the Gender Wage Gap in Armenia Rodriguez‐Chamussy, L., Sinha, N., Atencio, A., April 2018

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150 Do Demographics Matter for African Child Poverty? Batana, Y., Cockburn, J., May 2018

151 Household Expenditure and Poverty Measures in 60 Minutes: A New Approach with Results from Mogadishu Pape, U., Mistiaen, J., May 2018

152 Inequality of Opportunity in South Caucasus Fuchs, A., Tiwari, S., Rizal Shidiq, A., May 2018

153 Welfare Dynamics in Colombia: Results from Synthetic Panels Balcazar, C.F., Dang, H‐A., Malasquez, E., Olivieri, S., Pico, J., May 2018

154 Social Protection in Niger: What Have Shocks and Time Got to Say? Annan, F., Sanoh, A., May 2018

155 Quantifying the impacts of capturing territory from the government in the Republic of Yemen Tandon, S., May 2018

156 The Road to Recovery: The Role of Poverty in the Exposure, Vulnerability and Resilience to Floods in Accra Erman, A., Motte, E., Goyal, R., Asare, A., Takamatsu, S., Chen, X., Malgioglio, S., Skinner, A., Yoshida, N., Hallegatte, S., June 2018

157 Small Area Estimation of Poverty under Structural Change Lange, S., Pape, U., Pütz, P., June 2018

158 The Devil Is in the Details; Growth, Polarization, and Poverty Reduction in Africa in the Past Two Decades F. Clementi F., Fabiani, M., Molini, V., June 2018

159 Impact of Conflict on Adolescent Girls in South Sudan Pape, U., Phipps, V., July 2018

160 Urbanization in Kazakhstan; Desirable Cities, Unaffordable Housing, and the Missing Rental Market Seitz, W., July 2018

161 SInequality in Earnings and Adverse Shocks in Early Adulthood Tien, B., Adoho, F., August 2018

162 Eliciting Accurate Responses to Consumption Questions among IDPs in South Sudan Using “Honesty Primes” Kaplan, L., Pale, U., Walsh, J., Auguste 2018

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163 What Can We (Machine) Learn about Welfare Dynamics from Cross‐Sectional Data? Lucchetti, L., August 2018

164 Infrastructure, Value Chains, and Economic Upgrades Luo, X., Xu, X., August 2018

165 The Distributional Effects of Tobacco Taxation; The Evidence of White and Clove Cigarettes in Indonesia Fuchs, A., Del Carmen, G., August 2018

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