rafmacalaba/datause-encoder-data huggingface dataset:
the share of electrical machinery increased from 4 to 10 percent. ASEAN countries, with the exception of Indonesia, saw exports of office and telecommunications equipment and electrical machinery rise significantly, and these now accounted for a combined share ranging from 30 to 60 percent of total country exports. Similar to the changes in exports, the share of imports of machinery, in particular office and telecommunications equipment and electrical machinery, increased in total imports in many East Asian economies, including Japan. The export commodities where East Asia is specializing are inherently products with increasing returns to scale and high skill intensity (see figure 6).

**Table 2 The Commodity Composition of Foreign Trade in East Asia** _<u>percentage share of total trade</u>_

||_East_|_Asia_|_Ch_|_ina_|_Ja_|_pan_|
|---|---|---|---|---|---|---|
|_Composition_|_1990–94_|_2000–04_|_1990–94_|_2000–04_|_1990–94_|_2000–04_|
|_Export composition_|||||||
|Agriculture|7.0|4.1|13.7|5.2|1.1|1.0|
|Mining, fuels|5.4|5.1|6.4|4.1|1.3|1.7|
|Total manufacture|86.1|88.7|78.5|90.1|95.8|93.0|
|Machinery|46.6|53.6|17.4|40.6|71.6|67.1|
|Textiles, garments|12.7|9.1|29.1|18.3|2.1|1.5|
|_Import composition_|||||||
|Agriculture|12.9|8.9|9.3|7.7|23.3|15.6|
|Mining, fuels|15.4|16.8|7.7|13.7|27.9|25.5|
|Total manufacture|68.8|72.7|82.3|77.9|45.7|56.7|
|Machinery|34.3|41.8|42.0|45.0|16.9|27.6|
|Textiles, garments|7.3|5.4|9.4|4.4|6.6|6.5|

_Source:_ UNCOMTRADE

**Figure 6 The Share of Exports Increased More in Sectors with Increasing Returns to Scale, 1994–** **<u>2004</u>**

<!-- Start of picture text --> Inst rument s<br>scale elasticit y > 1 Electrical machinery<br>Nonelect ronics machinery<br>Iron and steel<br>Pharmaceuticals<br>Wood products<br>scale elast icity = 1 Footwear<br>Leather<br>Apparel<br>Textiles<br>-4.0 -2.0 0.0 2.0 4.0 6.0<br>change in export share, 1994-2004<br><!-- End of picture text -->

**_...and for most countries over half of exports is accounted by machinery._** There was a growing similarity in the commodity composition of exports among economies within the region between 1990–94 and 2000–04. This is reflected in the increase in the correlation coefficient of export composition between most pairs of economies in East Asia (the averages are shown in figure 7). In 2000–04, Indonesia was practically the only country that exhibited a different composition in export products. The export composition of the East Asian countries is more similar in terms of their trade with each other than it is in terms of their trade with the rest of the world. In most East Asian countries, exports of machinery account for more than half of their total exports.

_Sources:_ Antweiler and Trefler 2002 and World Bank.

9
wage labor employment and non-farm employment in rural India. The analysis reveals that poverty is associated in a complex way with the non-farm sector. First the data indicate that, controlling for agricultural wages, agricultural productivity, land availability and consumption levels in nearby urban centers, expansion of non-farm employment is directly associated with poverty decline. We suggest that this is consistent with the idea that while at early levels the non-poor may have been more successful at “capturing” non-farm income earning opportunities, there is some evidence that “marginal incidence” of further expansion of the sub-sector is pro-poor. We show that the pro-poor impact of the non-farm sector is attenuated in settings where education levels are particularly low. Second, the analysis further shows that expansion of the nonfarm sector appears to put pressure on wage rates in agriculture (again, less strongly so in settings where education levels are particularly low). Rising agricultural wage rates are, in turn, strongly correlated with rural poverty reduction. Thus, there is some evidence consistent with an important _indirect_ impact of the non-farm sector on rural poverty.

The evidence assembled in this study from the NSS surveys thus offers some empirical support to the view that the period between 1983 and 2004/5 was one of gradual economic diversification out of agriculture and limited poverty reduction in rural areas. But it is important, as well, to acknowledge the limitations to the analysis here. The analysis stops in 2004/5 and we are unable to say what has happened since that survey year. The analysis is also somewhat partial in its examination of sources of rural livelihoods. Notably, we are not able to carry out a very detailed analysis of the relationship between poverty and agricultural production, or on the evolution of agricultural output over time. This omission is due to lack of detailed data in the NSS surveys on farm production and household incomes.

In the remaining sections of this paper we turn in greater detail to the empirical underpinnings of the basic story outlined above. In Section II we consider the evolution of poverty in India. Section III looks at agricultural labor and agricultural wages. Section IV documents the size and evolution of the non-farm sector between 1983 and 2004/5, and Section V exploits a region-level panel dataset across three of our four surveys to bring together the arguments of the preceding sections and Section VI offers some concluding comments.

4
Policy Research Working Paper 10169

# **Abstract**

Somalia, one of the poorest countries in Sub-Saharan Africa, still faces many challenges as it remains fragile. Terrorist groups and their attacks are threatening the government and limiting its capacity to implement effective development policies. Using difference-in-difference and instrumental variables approaches with micro-data from two waves of the Somali High Frequency Survey, this paper estimates the immediate (within a week) impact of terrorist attacks on households. The consumption of households exposed to terrorist incidents decreases by 33 percent, mainly on food items. As a result, poverty and the depth of poverty among the poor increases. The decline in consumption seems to be explained by a smaller share of household members working and earning income after an attack. In addition, the effect on consumption is restricted to a 4-kilometer radius from incidents and has a heterogeneous impact, not affecting households in the top 20 percent of the consumption distribution. The paper also finds a deterioration in people’s perception of police competence. Achieving peace is a fundamental first step to increase welfare conditions that will also bring other wider long-term benefits in Somalia.

This paper is a product of the Poverty and Equity Global Practice. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at gnunez1@worldbank.org and upape@worldbank.org.

_The Policy Research 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._ Produced by the Research Support Team
|(6)<br>2.796<br>(5.964)<br>0.678**<br>(0.276)<br>16.901***<br>(2.645)<br>-9.226**<br>(4.577)<br>33.031*<br>(16.820)<br>-7.613<br>(12.369)<br>-11.571<br>(20.545)<br>-124.197***<br>(28.143)<br>96<br>0.63<br>Dependent<br>of GDP;<br>P;<br>_navian, and_<br>rage values|
|---|
|(5)<br>2.785<br>(6.308)<br>0.939***<br>(0.322)<br>18.019***<br>(2.441)<br>-143.515***<br>(26.517)<br>96<br>0.56<br>ignificant at 1%;<br>utions as a share<br>as a share of GD<br>_German, Scandi_<br>variables are ave|
|(4)<br>11.043<br>(7.338)<br>1.074***<br>(0.363)<br>-7.674<br>(6.456)<br>50.243**<br>(19.202)<br>15.9<br>(11.601)<br>-7.909<br>(17.965)<br>-27.199<br>(27.862)<br>96<br>0.44<br>t at 5%; *** s<br>inancial instit<br>ts and imports<br>bles;_French,_<br>8). All of the|
|(3)<br>11.499<br>(7.176)<br>1.544***<br>(0.403)<br>-40.715<br>(25.344)<br>96<br>0.31<br>; ** significan<br>ks and other f<br>s log of expor<br>enn World Ta<br>orta et al. (199<br>in the text.|
|(1)<br>(2)<br>Dep. Var.: Private Credit/GDP<br>Log(Trade/GDP)<br>14.511*<br>(8.540)<br>EFNX<br>1.596***<br>(0.389)<br>Log(Income)<br>French Legal Origin<br>German Legal Origin<br>Scandinavian Legal Origin<br>Socialist Legal Origin<br>Constant<br>-17.246<br>3.949<br>(34.788)<br>(8.195)<br>Observations<br>96<br>96<br>R-squared<br>0.05<br>0.28<br>Notes: Robust standard errors in parentheses; * significant at 10%<br>variable,_Private Credit/GDP_is credit to the private sector by ban<br>_EFNX_is the external finance need of exports;_Log(Trade/GDP)_i<br>_Log(Income)_is log of PPP-adjusted real per capita income from P<br>_Socialist Legal Origin_dummies are as defined originally by La P<br>over 1970-99. Variable definitions and sources described in detail|

29
measure is in constant Brazilian _reais_ and comes from Brazil’s Institute for Geography and Statistics (2017).

# _Competitive Elections_

We code data on the relative competitiveness of municipal elections to address the prospect that electoral accountability drives better municipal governance and incentivizes tax collection. Specifically, we address this prospect by recording the mayor’s overall vote share in the previous election’s first round.<sup>7</sup> These measures come from Brazil’s Superior Electoral Tribunal: http://www.tse.jus.br/.

# _Mayor’s Party_

Mayors from Brazil’s Workers’ Party (PT) have historically supported local political participation. PT mayors may therefore adopt and support participatory institutions at greater rates than non-PT mayors, which could influence institutional performance. Mayors from the PT may also support greater spending on services, such as for health and sanitation, and efforts to achieve desirable outcomes in these areas, such as by reducing infant mortality levels (Touchton and Wampler 2014). PT mayors might convince residents to comply with tax regulations at greater rates than other mayors in this scenario, but there are also reasons to believe that municipalities with PT mayors could collect systematically lower taxes than other municipalities with mayors from a different party, all else equal. For example, the PT is a center-left party, but firms may believe that other parties serve their business interests better and may withhold taxes to protest PT spending on poor populations over infrastructure projects that benefit firms as well as middle- and upper-class Brazilians more directly. The point here is that the mayor’s party could influence participatory institutional performance and tax compliance and we therefore account for it in our estimates. We do this by coding a dummy variable as “1” if municipalities have a PT mayor in a given year, with mayors from all other parties receiving a score of “0” to account for this prospect.

# _Presidential Vote_

We include a measure of municipal support for PT presidential candidates, who were elected in 2002, 2006, 2010, and 2014. These PT Presidents promoted participatory institutions and social programs; we control for the possibility that some municipalities and their residents are more committed to specific programs and institutions associated with these presidents, which could potentially influence the general support for empowering these programs, and, in turn, the municipal governments that adopt them by complying with tax laws.

> 7 Brazilian municipalities with fewer than 200,000 residents use single-round mayoral elections. These municipalities represent the overwhelming majority of our data set.

19
# **S1.3 Administrative Matched Employer-Employee Data Sets**

Section 7 of this paper used administrative data for Brazil covering 1995-2014 from the Rela ̧c ̃ao Anual de Informa ̧c ̃oes Sociais (RAIS), Costa Rica covering 2006-2011 from the _Caja Costarricense de Seguro Social (CCSS)_ , and Ecuador 2006-2012 from the Instituto Ecuatoriano de Seguridad Social (IESS).

The Brazilian administrative data cover all workers who have a signed work card. It omits interns, domestic workers (until 2014), along with those without signed work cards, including the self-employed that are not contributing to the system. The Costa Rican administrative data cover all workers registered with “Caja Costarricense de Seguro Social.” Registration is mandatory for all manual and intellectual workers who receive a salary. Benefits include not just old age pension, but also medical services, subsidies for disability, and maternity leave. It also includes uncovered workers and self-employed who voluntarily contribute. The Ecuadorian administrative data cover all workers registered with “Instituto Ecuatoriano de Seguridad Social.” Registration is mandatory for all people who work with or without a dependency relationship (in particular, workers in a dependent relationship), self-employed workers, freelance professionals, administrators or employers of a business, unpaid workers at home, and minor independent workers. Benefits include health, pension, rural social security, and labor risks protection. Workers can decide to contribute voluntarily.

The three data sets have unique worker and employer identifiers. In all cases, the analysis focuses on private sector employees. Self-employed are excluded because the administrative data is unlikely to be representative for this group, as there is a large share of self-employed workers non-contributing to the system. If a person had two jobs at the same time, the analysis only considers the main job, which was proxied by the one with the highest wage. The wage measure used in the administrative data is the real monthly wage. Nominal monthly wages are converted into real terms using national consumer price index (CPI) deflators, and they are expressed in dollars using 2005 purchasing power parity (PPP).

Supplementary online appendix table S1.3 presents the average wage and size of the formal workforce in household surveys versus administrative data. Although the definition of formal employment differs between household surveys and administrative data (see section 7), the number of workers covered in the two data sources and their distribution of wages are roughly comparable (see also figure S5.1 for a comparison of wage distributions in the two data sources).

50
2005). Evidence from Latin America, Africa, South Asia and other regions suggests that **remittances reduce the depth and severity of poverty** , as well as indirectly stimulate economic activity (Adams 1991, Lachaud 1999, Fajnzylber & Lopez 2007, Adams 2006b, Gupta _et al_ . 2007, Anyanwu and Erhijakpor 2010, Ajayi _et al._ 2009). The dramatic increase in remittances was responsible for one third to one half of the overall reduction in headcount poverty rate in Nepal from 42 percent in 1995-96 to 31 percent in 2003-04 (World Bank 2006a).

Remittances have been found to have an income stabilizing effect at both the macroeconomic level (World Bank 2006b, Chami _et al_ . 2009) and at the household level. Historically, remittances have tended to rise in times of economic downturns, financial crises, and natural disasters because migrants living abroad send more money to help their families back home (World Bank 2006b, Yang 2006, Yang and Choi 2007, Mohapatra _et al._ 2010). In Ghana, remittances were found to help households to minimize the effects of economic shocks on household welfare (Quartey 2006).<sup>3</sup> Remittance-receiving households in Ethiopia used their cash reserves and thus avoided having to sell their livestock to cope with drought (Mohapatra _et al_ . 2009). Recent evidence from Mali confirms that a substantial part of remittances is saved for unexpected events and the migrant thus serves as an insurer for the whole household (Ponsot & Obegi 2010).

Cross-country analysis indicates that remittances are related to greater income inequality in Africa (Anyanwu & Erhijakpor 2010) and Latin America (Barham & Boucher 1998). However, other studies suggest that migration enhances the welfare of the rural poor disproportionally, for example, in Mexico (Stark and Taylor 1980), in rural Egypt (Adams 1991) and in other regions (Portes 2009).<sup>4</sup> Migration may also raise inequality initially, as only the relatively well-off have the resources to send workers

> 3 The consumption smoothing effect of remittances allows households to engage in high-risk but possibly more profitable economic activities that have a poverty-reducing effect, but that in absence of migration would have been difficult. See Morduch (1994) for discussion on stochastic poverty causing chronic poverty in absence of credit markets.

> 4 The impact of remittances on inequality depends on the initial position of the recipients in the income distribution: in Mexico 61 percent of the remittance receiving households fall in the first quintile of nonremittance income, whereas in Peru fewer than 6 percent of the remittance-receivers belong to the lowest quintile (Fajnzylber & Lopez 2007, p. 6).

4
the latter down to a historic low in 2007. We also show that integration into global financial markets has increased over the past years, as measured by international bond issues, international loans, offshore deposits and remittance flows. However, the increase in international lending and bond issues has been concentrated in high-income countries, while low- and lower-middle income countries have benefitted from higher remittance flows. While off-shore deposits from low-income countries relative to domestic deposits are relatively high compared to middle- and high-income countries, reflecting the lack of trust in domestic banking systems, this ratio has halved over the past 12 years.

We also build on the recent literature on market- vs. bank-based financial systems by analyzing trends in the relative importance of financial markets and financial institutions over the past 20 years. We find a trend towards market-based financial systems, especially in high-income countries; while both market and bank finance has deepened over recent years, the deepening was stronger for markets than for banks. Where there has been a somewhat less pronounced trend towards markets in the developing world, it is mostly driven by a rise in market capitalization (less than in trading), while banking credit across the developing world has shown less of a clear trend.

Unlike at its first publication in 1999, when the Database of Financial Development and Structure was the only cross-country database published by the World Bank, the current version is complementary to several other efforts of the World Bank to improve measurement and thus quantitative analysis of financial systems across the world. First, Beck, Demirguc-Kunt and Martinez Peria (2007) and Honohan (2008) provide indicators of access to and use of financial services across a broad cross-section of countries, while Beck, Demirguc-Kunt and Martinez Peria (2008) and World Bank (2007) provide indicators of barriers to banking access in developing and developed countries.<sup>2</sup> Second, IFC’s Doing Business Database contains several indicators measuring the efficiency of financial infrastructure, including enforcement of contracts, creditor rights, collateral registration and credit registries, while IFC’s Enterprise Surveys provide firm-level information on financing patterns and obstacles.<sup>3</sup> Third, Barth, Caprio and Levine (2008) present indicators on the regulation and supervision of banks for a broad cross-section of countries for the years 1997, 2001 and 2005, and Demirguc-Kunt et al. (2007) present indicators on the coverage and structure of deposit insurance schemes across a large number of countries. Fourth, Beck et al. (2008) uses information from

> 2 World Bank (2007) provides an overview of different indicators related to the breadth or penetration of financial systems.

2
**Figure 15. Individuals with an account at a bank or other financial institution, %**

<!-- Start of picture text --> 30% 28%<br>26%<br>20% 20%<br>20%<br>17%<br>16%<br>15%<br>13% 13%<br>9% 11% 10% 10% 10%<br>10% 7% 7% 6% 7% 6% 8% 8% 7% 9% 8% 9% 9%<br>6%<br>4% 4% 4% 4% 4% 4%<br>3% 3%<br>2%<br>0%<br>All (15+) Rural Male Female In Labor Out of Young Older Primary secondary Poorest Richest<br>Force Labor Adults Adults Education education 40% 60%<br>Force (25+) or less or more<br>By Gender By LF Participation By Age By Education By Quintile<br>Account 2011 Account 2014 Borrowed to start, operate, or expand a farm or business 2014<br><!-- End of picture text --> _Source_ : Global Findex Data 2011, 2014.

Women rely to a larger extent than men on informal institutions for access to money and finance. For example, women have a harder time coming up with emergency funds according to Global Findex 2014 data. While almost half of the women surveyed (48 percent) reported not being able to come up with emergency funds, only 39 percent of the men reported the same. There is also a noticeable difference in the source of these emergency funds, with 64 percent of women relying on family and friends, compared to 42 percent of men. There are a number of informal financial institutions in Sudan, and Kevane and Stiansen highlight three: _sandug_ , _dayn_ , and _shayl._<sup>19</sup> Of these, _sandug_ are the only viable credit option for most women. _Sandug_ are monthly gatherings of small groups of women at which each woman contributes something from her savings to the group’s pool of savings enabling one woman—based on a rotating system—to borrow from the group’s savings for consumption or investment.<sup>20</sup> Microfinance is another option for some Sudanese women, and according to a study of microfinance’s role in supporting women entrepreneurs in urban Sudan, there are a variety of institutions that offer microfinance.<sup>21</sup> The lack of access to finance contributes to low levels of entrepreneurial activity among women. Data from the Enterprise Survey conducted in Sudan in 2014 show that only 3 percent of firms have a woman

> 19 _Dayn_ is a form of informal credit utilized by those who trade in the markets; for example, traders may maintain a ‘line of credit’ with a small shopkeeper who agrees to provide them with the staple items they need to prepare the food they sell. _Shayl_ is a form of ‘futures contract’ for those who engage in smallholder agriculture.

> 20 For example, the UN International Fund for Agricultural Development (IFAD) has helped women in Kordofan State who rely on _khatas_ , which are similar to _sandugs_ , channel their groups’ savings into the Agricultural Bank of Sudan’s microfinance program. This microfinance program had, as of 2017, worked with 1,800 women’s groups which comprised 30,000 members (IFAD 2019).

> 21 (Siddig, Siddig, and Hegazi 2014) The study highlights, for example, the Savings and Social Development Bank and the Youth Foundation for Microfinance.

39