rafmacalaba/datause-encoder-data huggingface dataset:
Closing the gender labor force participation rate would increase GDP by 2.3 percent. Generally, women of working age (20-65) have high activity rates, with an average labor force participation rate of 77.8 percent, as compared to 88.6 percent for men.<sup>21</sup> Yet if we close the 10.7 percentage point difference, the workforce would grow from 1.90 million to 2.04 million (Figure 2). Ultimately, GDP would reach USD 4.14 billion and the contribution of women would rise to USD 1.13 billion from USD 1.08 billion. The influx of workers into the labor-market would not be equally absorbed, instead displacing female and male workers between sectors to differing degrees. The share of workers in the traditional sector would increase from 70.5 percent to 73.9 percent and the share of workers in the modern sector would decrease from 29.5 percent to 26 percent. Notably, the share of female in the modern sector would increase from 32.7 to 40 percent while its male share would decrease from 67.3 to 60 percent. Since the gender gap in labor force participation is similar in Liberia to those in Sub-Saharan Africa and the OECD, we do not present the results here.<sup>22</sup>

**Figure 2. Selected macro-economic changes due to complete convergence in the LFPR gender gap (in USD, growth in %)**

<!-- Start of picture text --> $4,500 20%<br>4,142<br> $4,000 15%<br>15.2% 15.9%<br> $3,500<br>10%<br>10.0%<br> $3,000<br>5%<br> $2,500<br>3.5%<br>2.3% 0%<br> $2,000<br>-5%<br> $1,500 1,252<br>-10%<br> $1,000 747 809 809<br>506<br> $500 -15%<br>-15.6%<br> $- -20%<br>GDP Female Trad. Mod. Trad. Mod.<br>Female Male<br>Source: author’s calculations<br>Millions<br>Growth (in %)<br><!-- End of picture text --> Fertility rates equal to the net reproduction rate of 1.0 would increase GDP by 3.1 percent (Figure 3). Overall, Liberian women have 4.47 children over the course of their reproductive years.<sup>23</sup> We initially investigated to what extent a fertility rate that is equal to an instant-replacement level alters the economic

> 21 These point estimates were drawn from ILO 2010, constructed to allow for 5-year cohort averages.

> 22 Estimates on these benchmarks are available upon request to the authors.

> 23 This figure is drawn from the World Population Prospects, which estimates population size, in five- year increments, over the century. These rates are slightly higher than the estimates derived from the recently released DHS 2019/2020, reported earlier in the paper. This number decreased from 6.8 in 1970-1975 and it is projected to reach 3.9 in 2025-2030 (United Nations, 2015). There is significant variation in the average fertility rate across regions, education levels, and wealth quintiles (DHS 2019/2020).

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POVERTY AND INFRASTRUCTURE ACCESS IN SLUMS population-weighted stratified random sample, and it is representative of the 1,263 EAs that CBS categorized as slums.

The Dakar survey covered 1,960 households selected randomly from a random sample of 99 EAs, from a universe of 2,074 EAs in the city, stratified by level of past slum-upgrading efforts. The household sample was selected from a 2002 listing of households, and stratification was carried out based on both official and unofficial information.

In Johannesburg, a different World Bank research team led surveys of 5,100 households over six weeks in August and September 2001. The survey formed part of a larger effort to monitor service delivery to the poor and focused on what the study team termed “poorly served” areas. Using data from a 1996 citywide sample, Bank staff identified 921 EAs that qualified as poorly served.<sup>1</sup> These EAs comprise 125,409 households, or about 24 percent of the city’s population. The 5,100 surveyed households are representative of this underserved quartile and are drawn from 253 of the 921 poorly served EAs. For purposes of comparison with the slums of Nairobi and Dakar, however, we analyze only a subset comprising 1,618 households living in informal housing, mostly shacks.

> 1 Cut-off points for inclusion in the set of poorly served areas is as follows: 5 percent of the households with less than basic water and sanitation, 10 percent for electricity, and 20 percent for housing quality. These cut-off points were selected to give the maximum feasible population of EAs to be surveyed.

3
POLICY **RESEARCH WORKING PAPER** 3074

# Abstract

Pension systems may have a different impact on gender because women are less likely than men to work in formal labor markets and earn lower wages when they do. Recent multipillar pension reforms tighten the link between payroll contributions and benefits, leading critics to argue that they will hurt women. In contrast, supporters of these reforms argue that **it** will help women by the removal of distortions that favored men and the better targeted redistributions in the new systems.

To test these conflicting claims and to analyze more generally the gender effect of alternative pension systems, James, Edwards, and Wong examine the differential impact of the new and old systems in three Latin American countries-Argentina, Chile, and Mexico. Based on household survey data, they simulate the wage and employment histories of representative men and women, the pensions they are likely to generate under the new and old rules, and the relative gains or losses of men and women because of the reform.

The authors find that women do accumulate private annuities that are only 30-40 percent those of men in the new systems. But this effect is mitigated by sharp targeting of the new public pillars toward low earners, many of whom are women, and by restrictions on payouts from the private pillars, particularly joint annuity requirements. As a result of these transfers, total lifetime retirement benefits for women reach 60-80 percent those of men, and for "full career" women they equal or exceed benefits of men. Also as a result, women are the biggest gainers from the pension reform. For women who receive these transfers, female/male ratios of lifetime benefits in the new systems exceed those in the old systems in all three countries. Private intra-household transfers from husband to wife in the form of joint annuities play the largest role.

This paper is a product of the Gender Division, Poverty Reduction and Economic Management Network. Copies of the paper are available free from the World Bank, 1818 H Street NW, Washington, DC 20433. Please contact Max Jira Ponglumjeak, roomMC4-426, telephone 202-473-1060, fax202-522-3237, emailaddress mponglumjeak@worldbank.org. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. June 2003. (77 pages) _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 qutckly, 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 view of the World Bank, its Executive Directors, or the countries they represent._
# The Cross-Section of Stock Returns: Evidence from the Emerging Markets

by Stijn Claessens World Bank Susmita Dasgupta World Bank and Jack Glen International Finance Corporation We would like to thank those in the IFC's Emerging Markets Database division, especially Peter Tropper and Peter Wall, for assisting with the data. The comments of Michael Adler, Robert Cumby, Robert Korajczyk, Kajal Lahiri, Ross Levine, Hemant Shah and Campbell Harvey are appreciated.
# **1 Introduction**

The effectiveness of foreign aid remains controversial. A large literature studies how aid is spent (Werker et al., 2009); how it is absorbed in the domestic economy (Temple and van de Sijpe, 2017); and how much it ultimately stimulates growth (Dalgaard et al., 2004), improves human development outcomes (Boone, 1996), and reduces poverty (Collier and Dollar, 2002). In light of the evidence, some scholars assert that aid plays a pivotal role in promoting economic development in the poorest countries (Sachs, 2005) while others are highly skeptical (Easterly, 2006). Many studies emphasize that aid effectiveness depends crucially on the quality of institutions and policies in the receiving countries (Burnside and Dollar, 2000).

A concern often voiced by skeptics is that aid may be captured by economic and political elites. The fact that many of the countries that receive foreign aid have high levels of corruption (Alesina and Weder, 2002) invokes fears that aid flows end up in the pockets of the ruling politicians and their cronies. This would be consistent with economic theories of rent seeking in the presence of aid (Svensson, 2000) and resonate with colorful anecdotal evidence about failed development projects and self-interested elites (Klitgaard, 1990). Yet, there is little systematic evidence on diversion of aid.

In this paper, we study aid diversion by combining quarterly information on aid disbursements from the World Bank (WB) and foreign deposits from the Bank for International Settlements (BIS). The former dataset covers all disbursements made by the World Bank to finance development projects and provide general budget support in its client countries. The latter dataset covers foreign-owned deposits in all significant financial centers, both havens such as Switzerland, Luxembourg, Cayman Islands and Singapore whose legal framework emphasizes secrecy and asset protection and non-havens such as Germany, France and Sweden.

Equipped with this dataset, we study whether aid disbursements trigger money flows to foreign bank accounts. In our main sample comprising the 22 most aid-dependent countries in the world (in terms of WB aid), we document that disbursements of aid coincide, in the same quarter, with significant increases in the value of bank deposits in havens. Specifically, in a quarter where a country receives aid equivalent to 1% of GDP, its deposits in havens increase by 3.4% relative to a country receiving no aid; by contrast, there is no increase in deposits held in non-havens. While other interpretations are possible, these findings are suggestive of aid diversion to private accounts in havens.

One may be concerned that the results are confounded by factors affecting both aid inflows and capital outflows. We address this potential endogeneity in three ways. First, we augment 1
of the transaction and limited enforcement ability. Deep trade agreements reduce contractual uncertainty, because in addition to smoothing differences in contractual institutions (either by setting common rules or by allowing mutual recognition of heterogeneous practices among PTA members), they provide a commitment device for countries with weaker institutions and a mechanism to enforce rules through dispute settlement. By doing so, deep agreements interact with the make-or-buy decisions of firms and, hence, with the way goods are traded internationally.

To guide our empirical analysis of the impact of PTAs on vertical FDI, we employ the model by Antràs and Helpman (2008) (henceforth, AH). AH's framework introduces different degrees of contractual frictions across countries in a model of the international organization of production. This setting allows us to study the impact of improvements in the quality of contracting institutions, such as the ones brought about by a deep PTA, on firms' location and control decisions. The main insight of the theory is that deep provisions in PTAs may increase or decrease vertical FDI, depending on whether they improve the contractibility of inputs provided by the headquarters (headquarter services) or by the suppliers (components). Provisions that improve the contractibility of headquarter services are, for example, protection of intellectual property rights or investment provisions; provisions that improve the contractibility of components are, for example, standards and other regulatory requirements that promote harmonization or mutual recognition. As we put it in the title: when it comes to the effects of deep agreements on vertical FDI, the devil is in the details (i.e. the content) of the agreement. The reason for this finding is entrenched in the logic of the property rights approach to the boundary of multinational firms. Because ownership is a means to reduce hold-up problems created by contractual incompleteness, it matters if the PTA provisions improve the relative contractibility of different inputs.

We test this theory using a new data set on the content of PTA provisions and using firm-level information to construct a sectoral measure of vertical FDI. We proxy the depth of an agreement with different indexes and we find that deeper agreements are associated with higher values of vertical FDI. However, once we look at the composition of PTAs, depth per-se is no longer positively correlated with vertical FDI, whereas the type of provisions included in an agreement matters. In fact, while provisions that improve the 4
_25_ _WATER WHEN IT COUNTS_ to tomato planted on plot 1010101.<sup>18</sup> The information treatments were delivered by our enumeration team during each agriculture survey. The feedback was provided prior to starting the survey. The information experiment began in December 2016 (Figure A1). The information treatment was repeated for the same farmers two additional times in April 2017 and July 2017 to ensure that farmers received feedback in each of the relevant seasons. Treatment is assigned only once, so that a farmer once assigned always receives the same type of feedback, but the crop they are informed about can vary depending on which crop was most relevant in that same upcoming period last year.

Water measurement and agriculture surveys continued for three rounds after the start of the treatment, following the schedule described in section 2.2. A total of 157 households were listed as part of the schemes, of which: 125 were surveyed in at least one of the prefeedback rounds (rounds 1-4), and 129 responded to at least one of three post-feedback surveys (rounds 5-7). Finally, 115 households responded to at least one pre-feedback and one post-feedback round. Since feedback was delivered during the survey, delivery of feedback is conditional on finding the household for that survey round. Out of the 75 and 72 assigned to the general guidance and individual feedback, respectively, 66 and 62 received at least one round of feedback.<sup>19</sup> Scheduling of water allocations is typically arranged by heads of water user associations, and is fixed according to the days of the week and time of day. The fact that the generalized feedback communicates to farmers that they should vary their water use throughout the crop season runs in direct contrast to the idea of a fixed schedule. We

> 18The farmers are reminded of the plot the information relates to using a map of the scheme. The feedback tools displayed here are shown with English translations. The versions used in the field were written in Portuguese. 198 households that joined the schemes after round 4 did not receive any treatment. New households that joined after the original matched pairs randomization were individually assigned a feedback treatment status.
_Notes_ : (1) The data are from children who were born between 1950 and 1989 using the CFPS 2010 round for China, the IHDS 2012 round for India, and the IFLS 2014 round for Indonesia. (2) Each row uses a subsample of children who were born in the given birth cohort and the given category.

**Table A.3: Evolution of Risk Adjusted IGRC by Birth Cohorts Across Geography and Gender**

||**CH**<br>|**INA**<br>|**IND**<br>|**IA**<br>|**INDO**<br>|**NESIA**<br>|
|---|---|---|---|---|---|---|
||Weighted<br>RIGRC|Canonical<br>IGRC|Weighted<br>RIGRC|Canonical<br>IGRC|Weighted<br>RIGRC|Canonical<br>IGRC|
||||**Urban**<br>|**Sons**<br>|||
|1980-1989|0.385|0.330|0.585|0.499|0.462|0.421|
|1970-1979|0.362|0.315|0.618|0.500|0.459|0.417|
|1960-1969|0.288|0.251|0.687|0.528|0.551|0.458|
|1950-1959|0.250|0.210|0.736|0.565|0.541|0.521|
||||**Urban D**|**aughters**<br>|||
|1980-1989|0.415|0.359|0.668|0.540|0.469|0.432|
|1970-1979|0.434|0.373|0.741|0.566|0.463|0.427|
|1960-1969|0.356|0.294|0.840|0.609|0.659|0.556|
|1950-1959|0.428|0.312|0.917|0.581|0.689|0.586|
||||**Rural**|**Sons**|||
|1980-1989|0.422|0.339|0.607|0.478|0.420|0.381|
|1970-1979|0.359|0.271|0.745|0.538|0.462|0.427|
|1960-1969|0.242|0.178|0.904|0.606|0.567|0.494|
|1950-1959|0.263|0.180|1.079|0.684|0.559|0.455|
||||**Rural D**|**aughters**|||
|1980-1989|0.484|0.381|0.730|0.532|0.456|0.411|
|1970-1979|0.446|0.326|0.819|0.522|0.560|0.514|
|1960-1969|0.350|0.247|0.905|0.521|0.698|0.593|
|1950-1959|0.367|0.251|0.947|0.496|0.451|0.463|

_Notes_ : (1) The data are from children who were born between 1950 and 1989 using the CFPS 2010 round for China, the IHDS 2012 round for India, and the IFLS 2014 round for Indonesia. (2) Each row uses a subsample of children who were born in the given birth cohort and the given category.

39
**Table 1: Overview of key data and assumptions**

|Data item|Value|Source|
|---|---|---|
|**Jatropha plantation**|||
|Economic life ofjatrophaplantation|30years|Assumption|
|Plantingdensityofjatropha|2.5 m * 2.5 m(1600plants/ha)|CJP,India|
|Labor requirement for jatropha<br>plantation(man-day/ha)|Land preparation = 15, Digging holes<br>= 32,Plantingof saplings = 16|Adhikari and<br>Wegstein,2011|
|Nutrient requirement of NPK (gm/plant)|60:100:60|Mohapatra and<br>Panda,2011|
|Fertilizer requirement (kg/ha)|Urea = 73, Diammonium Phosphate<br>(DAP) = 348,<br>Muriate of Potash(MOP)= 160|Authors’ calculation|
|Fertilizer prices (NRs/kg)|Urea = 19.3, DAP = 46.3,<br>MOP = 22.3|AIC, Nepal|
|Jatropha seed yield on arable land<br>(tonne/ha)|3 tonnes/ha, 5 tonnes/ha, 10 tonnes/ha|Alternative<br>assumptions|
|Labor requirement for harvesting<br>jatropha fruits|1 labor (man-day) for harvesting 60 kg<br>seed|Mitchell, 2011|
|Land rent(NRs/ha/year)|60,000|Field survey|
|Labor wage(NRs/man-day)|400|Field survey|
|**Biodiesel production**|||
|Economic life of biodieselplant|20years|Assumption|
|Biodiesel plant capacity|1000 liters per day; Operation of 300<br>days in ayear|Assumption|
|Land required for establishing biodiesel<br>plant|0.33 ha|Field survey|
|Total investment required for biodiesel<br>plant installation|NRs 25,000,000|Field survey|
|Operatingcost of oil extraction|US$0.12/liter|CJP,India|
|Oil extraction rate|36% ofprocessed seeds|Mitchell,2011|
|Glycerolproduction|4.6% ofprocessed seeds,NRs 48/kg|Shinojet al.,2010|
|Oil-cakeproduction|70% ofprocessed seeds,NRs 9.6/kg|Shinojet al.,2010|
|**Others**|||
|Importprice of diesel in Nepal|NRs 86.6/liter|NOC,Nepal|
|Diesel import in Nepal in the fiscal year<br>2012/13|721,203 KL|NOC, Nepal|
|Discount rate(real)|6.5%|NRB,Nepal|
|Exchange rate|US$1 = NRs 97|NRB,Nepal|

14
labor income from January to November 2020 **.** Additionally, variations in the number of employees throughout the year, peaking in the summer and dropping in the winter, impact data matching. The characteristics of employees also undergo seasonal changes, making the evolving employee pool more significant in our context than fluctuations in median/mean labor income values. When estimating the gap between median "true" and median "reported income" based on tax data for February 2020, we observed an increase in average tax compliance to 96%, while tax compliance at the median decreased to 85%. Considering these factors, we assert that July provides the most representative proxy for annual income, and therefore, we maintain our main estimate based on this month as the baseline.

**Bendek & Lelkes (2011) compare the “true income” reported in the household budget survey and “reported income” from the sample of tax declarations in Hungary and find that the average rate of underreporting of income in tax data is 9%– 13%.** The degree of underreporting is higher among selfemployed than among employees. The underreporting is highest at the bottom and the top of the income distribution. The underreporting of true income in tax data reduces the tax system's progressivity. Paulus (2015) compares the "true income" reported in labor force survey data and income reported in tax declarations in Estonia. The study found that about 12% of total employment income is not reported to the tax authority, primarily due to the partial underreporting of income (envelope payments). Kiełczewska et al. (2021) compare the "true income" reported in the household budget survey and "reported income" from tax declarations in Poland. According to their results, 31% of microenterprises employees and 12% of employees in Poland receive envelope payments. Envelope payments equal 6% of Poland's labor income and 1.6% of the Polish GDP.

**Research done for other countries clearly shows that underreporting of top incomes in survey data significantly biases the true measure of income inequality downwards; our analysis shows this is also the case in Romania** . In Table 4, we compare the measures of income inequality in the EU-SILC dataset, tax data, and imputed EU-SILC and find that this is also the case in Romania. Our reference income variable is gross labor income. We restrict our sample to employees because we do not have complete administrative tax data for self-employed. We measure income inequality on the individual level. Income inequality is significantly higher in tax and imputed tax data than in survey data. In the original

21
# 4.4  Expenditure Composition

The major complaint voiced by the private sector pertains to the quantity and quality of infrastructure. Roads in particular are singled out—the fuel levy has not translated into better roads.<sup>26</sup> This brings us to the Achilles’ heel of the Kenyan public finances: expenditure policy. Figure 7 plots total primary expenditure and two of its key components: development expenditure and recurrent expenditure in the past ten years. Development expenditure consists largely of capital expenditure, and most of it is on public infrastructure. During the fiscal consolidation of the 1990s, development expenditure was cut from a high of 6.4 percent of GDP in 1994/95 to 1.9 percent in 1999/2000. These cuts were accompanied by deterioration in the quality of public investment portfolio. A number of construction projects with questionable economic rationale were taken up (Eldoret airport was a prime example) and a large stock of incomplete projects accumulated.<sup>27</sup> <!-- Start of picture text --> Figure 7 Primary Expenditure<br>% of GDP<br>30.0<br>25.0<br>20.0<br>15.0<br>10.0<br>5.0<br>0.0<br>Primary excl drought o/w Recurrent o/w Development excl net lending<br>1996/97 1997/98 1998/99 1999/2000 2000/2001 2001/2002 2002/2003 2003/2004 2004/2005 2005/2006 2006/2007<br><!-- End of picture text --> 26 The Road Maintenance Fuel Levy was established in 1993. It consists of an automotive fuel levy and transit toll collections. The objective of the levy was to provide funds for maintenance of roads; its proceeds are also used for rehabilitation and reconstruction. In 2006/07, approximately KSh 18.6 billion (1% of GDP) was collected as fuel levy.

27 Kenya, Public Expenditure Review 1997. World Bank (1997).

20
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