rafmacalaba/datause-encoder-data huggingface dataset:
- 2 -

# **I. INTRODUCTION**

Spatial data and techniques are becoming increasingly important in applied economics. A wide variety of new spatial data have recently been developed using innovative data mining techniques, such as high resolution satellite imagery and geo-referenced road network data. For instance, there exist several detailed global population distribution data, including the Gridded Population of the World and the WorldPop. The latter has the highest resolution of 100 meters and is continuously updated over time. OpenStreetMap locates many roads over the world. Such spatial data allow to develop a useful tool to identify potential economic opportunities and bottlenecks in developing countries (e.g., World Bank, 2009 and 2010).

In Africa, agriculture remains an important sector, generating $31 billion or nearly half of the total GDP of the region (World Bank 2013). Africa has great potential according to global spatial data, such as the Global Agro-ecological Zones (GAEZ) system developed by the FAO and the International Institute for Applied Systems Analysis (IIASA). Theoretically, crop suitability based on climate and soil conditions is not necessarily low in Africa. However, the potential has not been fully explored yet. For instance, the ratios of potential to actual agricultural outputs are estimated at 1.5 for cassava, 1.9 for rice, 2.7 for maize and 5 for wheat in West Africa (World Bank 2012).

There are a number of constraints: Africa’s agriculture is mostly small-scale subsistence farming. Irrigation and fertilizer are among the most important missing inputs (e.g., GyimahBrempong, 1987; Bravo-Ortega and Lederman, 2004; Xu et al., 2009; Dillon, 2011). Access to input and output markets is also important. In India, roads and fertilizer are found to be two important inputs to increase agricultural production (Binswanger, Khandker and Rosenzweig, 1993). In Africa, rural accessibility measured by the proportion of the rural residents within a 2-km walking distance from an all-weather road is less than 30 percent (Gwilliam 2011). Transport access has a crucial role to play to reduce input prices and increase agricultural production (e.g., Khandker, Bakht and Koolwal, 2009; Donaldson, 2010).
three phases: the demobilization, the reinsertion and the reintegration. The demobilization phase started with disarmament, followed by the transfer of ex-combatants to a demobilization center. Ex-combatants spent eight days in the center, attending training on economic strategies and opportunities, HIV/AIDS, civic responsibility, as well as peace and reconciliation.

As part of the reinsertion phase, demobilized combatants received a cash allowance worth 18-month salary, paid in four installments over a period of eighteen months. Demobilized combatants received the first reinsertion payment when leaving the demobilization center. Called the Transitional Subsistence Allowance (TSA) by the World Bank, the reinsertion money was dedicated to _“enable the ex-combatants to return to their community and to sustain themselves and their families for a limited period following demobilization”_ (The World Bank Group, 2004). The total amount of the cash allowance increased with military rank, starting from a minimum of FBU 566,000 (US$ 515).<sup>6</sup> The average benefit amounted to FBU 644,000 per demobilized combatant (US$ 586). Data from our survey in 2010 shows that civilian households consumed on average about FBU 190,000 (US$ 173) per adult equivalent per year, which is about one third of the minimum cash allocation to FNL rebels.

Finally, the reintegration phase consisted of a one-off in-kind transfer worth FBU 600,000 (US$ 545). The ex-combatants could choose from a range of options, including vocational training, support for agro-pastoral activity, and start-up material for a small business or a construction project. This phase was launched in September 2006 for the CNDD+.<sup>7</sup> Of the 23,000 CNDD+ beneficiaries, 85% had received the reintegration support by December 2008. This phase was just starting for the FNL ex-combatants at the time of our 2010 survey.

Some rebels had ties with the factions, but did not benefit from the DDR program. A list of criteria was established in order to assess the military aptitudes of candidates, defining whether rebels were eligible or not for the DDR program. The DDR program also included the disarmament and the dismantling of militias. These were formed by people helping the factions, notably in terms of logistics. These people were called “Gardiens de la Paix” (GdP) if they belonged to the FAB, “Militants Combatants” (MC) if they were part of the CNDD-FDD and “Adultes Associés” (AA) if they supported the FNL. 20,000 GdP, 10,000 MC and 11,000 AA benefited from the program. They received FBU 100,000 (US$ 91) as compensation.

# **2. Theoretical Framework**

The DDR program in Burundi was a social transfer program combining cash and in-kind benefits. We aim to assess its short- and long-run impacts, and to disentangle its direct impact

> 6All US$ equivalents are expressed in 2010 US$. US$ 1 was worth 1,100 Burundian francs in 2010.

> 7This phase did not start before March 2008 in the central provinces (Gilligan et al, 2013); the provinces included in the present analysis were not affected by this disruption.

5
Finally, it should be kept in mind that our IV strategy only captures the local average treatment effect in the sense of the impact in basins where dams were built because of favorable river characteristics and would not have been built otherwise. Thus, the above strategy provides us only with an estimate of the economic impact of technologically feasible dams. It does not have sufficient power to capture the effect of dams on cropland productivity placed because of political reasons, for example.

# _II._ **<<A>>** _DATA SOURCES_

To proceed to the econometric analysis, we collected data regarding dam location and characteristics, the spatial unit of analysis, the cropland productivity and other factors. The description of these data is provided below.

# **<<B>>** _Dams_

To identify and geographically locate dams in South Africa, we use the Department of Water Affairs (DWA) dams database (DWA 2011), which collects detailed information on dams that fall within the dam safety permit system, essentially covering all known dams with at least 5 m height and a reservoir capacity of 50,000 m<sup>3</sup> .<sup>8</sup> Importantly, the DWA dams database provides information on the exact latitude and longitude of the location, construction date, reservoir surface area and capacity, purpose, size classification, and, for many dams, height.

Our purpose here is to distinguish between the effects of large and small dams in South Africa. A crucial component in this regard is the definition of dams as large versus 16
# **6. Globalization**

<mark>A country’s growth/job performance also depends on its trade performance. It provides an important feedback loop for improving productivity, reinforcing competitiveness by increasing competition in the home market, better access to technology and new knowledge, and greater room for specialization and economies of scale. But globalization itself is changing both in terms</mark> of outcomes and policy.

<mark>The paradox of low income countries is that they appear to be somewhat ‘closed’ in terms of trade policy, but more ‘open’ in terms of trade outcomes. Ethiopia, Rwanda and Kenya trade more than a typical country does at its stage of development (see figure 12). Its share of service export has grown robustly. The share of service exports in GDP for them is higher compared to China or oil producing countries in Africa. Implementing a less restrictive and more efficient</mark> trading regime is a no brainer.

**<mark>Figure 12: Service Trade Outcome</mark>**

<!-- Start of picture text --> Services Exports in 2011 (% of GDP)<br>30<br>20<br>10<br>ETH RWA<br>VNM KOR<br>UGA KEN ZMB<br>CHN<br>0 TZA<br>6 8.5 11<br>Log of GDP per capita (PPP)<br>Percent<br><!-- End of picture text --> Source: World Bank Services Trade Database (June 2013) <mark>Developing countries now account for more than half of the world's economic activity and more than half of global exports. Manufacturing industry’s share in global trade has declined, while the share of services has increased. Services are the fastest growing component of trade, but they remain the poor relation of globalization; even agriculture, which accounts for 7% of international trade, receives closer consideration. And yet, services are at the very heart of value chains, because the provision of industrial or commercial services, such as information technology (IT) and factoring, marketing,</mark> 18
# **How Sensitive Are Latin American Exports to Chinese Competition in the U.S. Market?**

* J. Ernesto López-Córdova, Alejandro Micco, and Danielken Molina

_Keywords:_ Trade elasticities; trade policy; United States; China; Latin America _JEL Classification:_ F1

> * The authors are affiliated, respectively, with the International Finance Corporation, World Bank Group; the Chilean Ministry of Finance; and the University of California, San Diego. The opinions expressed herein do not necessarily reflect the views of those institutions.

1
other hand, it would be relatively easy to attract high-skill workers back to the country from the diaspora. Further, raising funds even in large volumes was not seen as a serious problem.

The government itself is positioning services as the future engine of growth. Its development policy framework highlights the importance of bolstering infrastructure for achieving its economic growth targets via the five hubs concept—a naval hub, an aviation hub, a commercial hub, an energy hub and a knowledge hub in South Asia. In this connection, IMF Staff note in the 2010 Article IV Consultation that Sri Lanka‘s strategic geographical location and comparative advantage in services could be the engine of growth in the medium-to-long term.

The 2011 budget sets public investment at 6.5 percent of GDP in the medium-term expenditure framework. While fiscal consolidation efforts will continue, the government has made it clear that public investment spending will remain at this level. In fact, public infrastructure spending has been significant in recent years. Donor commitments since 2005 have totaled 20 percent of 2010 GDP, although actual disbursements have been half of that amount (see Table 3). The five main areas of commitments are: roads, power and energy, water supply and sanitation, railways, and ports and aviation. The main donor in each area is: Japan in roads, China in power and energy, Japan and the ADB in water supply, India in railways, and China and the ADB in ports. Overall, China and Japan are the two largest financiers of infrastructure in the country. Some of the signature projects are the Hambantota Port (China), the Southern Expressway (Japan/ADB) and the Puttalam Coal Power Project (China).

|Category<br>**Table 3. Sri Lanka: Infrast**|Commitment<br>**ructure Financing, 20**|Disbursement<br>**05 -2010(US$, mill**|KeyDonor<br>**ions)**|
|---|---|---|---|
|Road Sector|2,553|1,293|Japan|
|Power & Energy Sector|1,886|1,311|China|
|Water supply and sanitation|1,168|657|Japan/ADB|
|Transport Sector - Railways|1,165|n.a.|India|
|Ports and Aviation Sector|1,136|564|China|
|Total|7,907|3,825||
|Source: Ministry of Finance||||

31
# **1. Introduction**

Violent conflict is one of the most important development challenges facing the world today. The incidence of wars has decreased in recent years (Harbom and Wallensteen 2009). However, the legacy of violence persists in many regions, affecting millions of men, women and children (Geneva Declaration Secretariat 2008, UNHCR 2008). The economic, political and social consequences of violence are far-reaching. Violent forms of conflict kill, injure and displace people, destroy physical capital and infrastructure and change the ways in which societies are organized. These effects will have considerable consequences for the long-term human capital accumulation of populations exposed to violence. This is well visible in the fact that no conflict-affected country will reach the Millennium Development Goals by 2015 (DFID 2009): conflict-affected countries contain one-third of those living in extreme poverty, and are responsible for almost one-half of child mortality in the world (Collier, 2007, DFID 2009). They also account for 42% of all out-of-school children (28 million children), even though only 18% of all children in the world of primary school age live in conflict-affected countries (UNESCO 2011).

The objective of this paper is to examine one important channel linking violent conflict and development outcomes: the level and access to education of children living in contexts of conflict and violence. The paper focuses on the impact of the conflict in Timor Leste on primary school attendance, grade deficits and primary school attainments of boys and girls. We look in particular at the impact of the last wave of violence in 1999 that followed the withdrawal of Indonesian troops from the territory. We analyze the short-term impact of the 1999 wave of violence on primary school attendance and primary school grade deficits in 2001, and the medium-term impact on primary school completion in 2007. In addition, we are also able to examine separately the impact of early periods of high-intensity violence of the 25 years of Indonesian occupation. This rich amount of information allows us to compare and contrast the impact of different processes of violence that take place in long-lasting conflicts. Finally, we assess also the effects of the entire conflict on primary school completion in 2007 in order to check whether the average impact is different or in line with analyzing singularly peaks of violence. To the best of our knowledge this is the first time that researchers are able to compare the impact of violence on educational outcomes in the short, medium and long terms. The paper represents also one of the very first attempts to quantify empirically the impact of the violence in Timor Leste on individuals exposed to the 25 years of violent conflict. To this purpose, we make use of three unique datasets that allow us to understand in detail the mechanisms linking violence and educational achievement.

2
7 indicates that the distribution was extremely skewed to the right, with 50% of the population receiving incomes less than approximately half of the arithmetic mean.

The second key feature of Table 1 is the inverted-U inequality dynamics, with the three subperiods previously mentioned: a steady increase from 1981 to 1989 (with the Gini rising from 0.574 to 0.625); a highly volatile “peak period” between 1989 and 1993; and a steady decline from 1993 to 2004 (with the Gini falling from 0.595 to 0.564). A very similar inverted-U pattern (with a volatile peak region) obtains for the other three inequality measures.<sup>12</sup> Figure 1 plots the evolution of the Gini coefficient (on the left scale) and the two Theil indices (on the right scale) over the period.

**Figure 1: Three Measures of Inequality in Brazil, 1981-2004**

<!-- Start of picture text --> 0.63 0.93<br>0.62 0.89<br>0.61 0.85<br>0.60 0.81<br>0.59 0.77<br>0.58 0.73<br>0.57 0.69<br>0.56 0.65<br>0.55 0.61<br>0.54 0.57<br>0.53 0.53<br>1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004<br>Years<br>Gini GE (0) GE (1)<br>Gini<br>GE(0) and GE(1)<br><!-- End of picture text --> How about the dynamics of poverty over this period? Unlike many other countries, Brazil does not have an official poverty line. A set of regionally-specific poverty lines calculated by Rocha (1993) for use with PNAD 1990 data has historically been used by many researchers. Rocha

> 12 The E(2) series is not shown on Figure 1, but it is similar and available from the authors upon request.
Adults living in Baghdad are significantly less likely to be satisfied with the quality of education and water in their area. However, this might reflect the relatively higher income and education of adults living in Baghdad, who might have higher expectations of government services. The perceptions of government services among Kurds are typically higher. The Kurds, with an autonomous history of local governance, are satisfied with these services throughout the decade, and even during the period of ISIS control. Perceptions of the quality of health care delivery are not significantly different between ethnoreligious groups. This is echoed by the findings of the World Bank’s Iraq Human Development Public Expenditure Review (2021) that found deteriorating outcomes in health care services across the board in the past two decades and limited availability of quality services, even for upper income groups (Panel C).

# **7. Conclusion**

The history of Iraq over the past decade is a stark example of increasing vertical and horizontal inequalities, preceding and following a period of violent conflict. This paper uses cross-sectional individual-level nationally representative survey data to study how adults in Iraq report confidence in national institutions, quality of life, and quality of service delivery. The analysis finds that positive perceptions across these categories declined during ISIS-control of parts of Iraq and are slowly picking up in recent years. Over the last decade, poor adults are more likely to be food insecure and have a weaker outlook on the standard of living. Men are more likely than women to report lower country leadership approval ratings, a lower standard of living, and weaker job prospects in the post-ISIS period. The findings show that Shias, Kurds, and adults in living in Baghdad have significantly deteriorating quality of life, over time, and a lower quality of life than Sunnis in the post-ISIS period. This is largely driven by the marginalization of the Sunnis in the last couple of decades (Bormann et al. 2021). Nearly all ethnoreligious groups perceive the government to be corrupt. Additional research (Dodge and Mansour 2021) finds this to be politi <mark>cally sanctioned government corruption and a key barrier to reform.</mark> 20
# MONGOLIA: Distributional Impact of Taxes and Transfers

Samuel Freije Judy Yang<sup>1</sup> JEL classification: D31, H22, H23, I38 Keywords: Poverty, inequality, taxes, transfers, redistribution, Mongolia

> 1 This a background paper of the Mongolia Public Expenditure Review lead by Jean-Pascal Nguessa Nganou. It has been prepared by Samuel Freije-Rodriguez (lead economist, GPV01) and Judy Yang (economist, GPV01). The authors have benefited from inputs and comments from Davaadalai Batsuuri, Tungalag Chuluun, Gabriela Inchauste, Jean Pascal Nguessa Nganou and Altantsetseg Shiilegmaa. Special thanks to Richard Schlirf and Yun Wu for data <u>about electricity and central heating production costs.</u>

MONGOLIA Distributional impact of taxes and transfers / November 2018
the total population size. We believe these two assumptions give good approximations of the brain drain rate, broadly consistent with anecdotal evidence.

# 2.3 Speci...c assumptions in release 1.0

Obtaining Census and Register data from all OECD countries is a long process involving numerous exchanges of information. Before data are available in the ...nal desired format, adequate estimates can be provided on the basis of Survey data. This is especially the case for European countries where the Censuses for 2000 or 2001 are sometimes not yet available. In these cases, estimates can be obtained by crossing European Council, Register or Census data on the origin of immigrants, with Labor Force Survey data on education and age structures.

The last column in Table 1 describes the speci...c assumptions in release 1.0. Labor Force Survey data are used for 12 EU countries in 2000 and 1990 (Austria, Belgium, Denmark, Finland, Germany, Ireland, Italy, the Netherlands, Portugal, Spain, Sweden and the United Kingdom) and immigrants’ educational attainment in Norway is temporarily extrapolated on the basis of the available OECD countries. In 2000, while Census data will ...nally capture 55.974 million OECD immigrants (95.7% of the 2000 OECD stock), Release 1.0 uses Survey data for characterizing 13.626 million of them (23.3% of the 2000 stock). In 1990, Release 1.0 uses Survey data for identifying 8.315 million (20.9% of the 1990 OECD stock) out of 36.862 million immigrants for which Census data will be available (92.5% of the 1990 stock).

Such temporary assumptions<sup>11</sup> induce two major shortcomings. First, European Council data must be used for 10 countries. These data are based on the concept of citizenship (rather than country of birth). In all cases, information on the birth country will be available from the national Censuses. Second, the Labor Force Survey list of country of origin is usually less detailed than the Census list. The survey distinguishes 22 countries of origin and 10 groups of countries in 1990, 26 countries of origin and 13 groups of countries in 2000. The most striking example is Africa, which is divided in three groups (South Africa, Northern Africa and Other Africa). We compute the skill structure of emigration for these groups of countries and consider it as homogenous within groups. Despite this limitation, we attempted to a comparison between Labor Force Survey and Census data for France and obtained very accurate estimates for most African countries.

Note that we also use the Labor Force Survey to eliminate immigrants aged under 25. For countries where detailed data are not available, the share of young immigrants is also assumed to be homogenous within groups.

> 11The ...nal database for 1990 and 2000 should be available by December 2004.

14