rafmacalaba/datause-encoder-data huggingface dataset:
pability is something that all elected leaders have the opportunity to exercise in office. Understanding whether the demonstration of this capability can successfully lead voters to prioritize politician competence over politician gender has far-reaching welfare implications.

Specifically, we study whether the District Primary Education Program (DPEP), a large national primary school expansion program in India, impacted women’s probability of being elected as members of legislative assemblies (MLAs) at the state level. The DPEP was implemented in a staggered manner during the period 1993-2004 in districts that had female literacy rates below the national average (according to the 1991 Census of India). Central and state governments in concert built new primary schools and trained new teachers in program districts across the country. They also facilitated the creation of local school committees to prioritize community engagement with student learning. At the time of its implementation, the DPEP was the largest program for primary education in the world, in terms of budget, geographical spread, and number of beneficiaries. The DPEP not only improved educational attainment and earnings of its direct beneficiaries (Azam and Saing, 2017; Khanna, 2023), but also indirectly improved learning outcomes of children whose mothers were direct beneficiaries of the DPEP (Sunder, 2020).

To illustrate the channels through which the DPEP potentially altered political outcomes, we develop a probabilistic voting model in the spirit of Dal Bó and Finan (2018). The model captures both the demand and the supply sides of the electoral process: voters face a trade-off between politician competence and their bias in favor of male leaders, and politicians of both genders choose whether or not to contest elections based on their probability of winning.

The scale of the DPEP provided ample opportunity for leaders to demonstrate their competence in its implementation. Moreover, the program explicitly emphasized reductions in gender disparities in access to education and incorporated community awareness initiatives on the importance of girls’ education. For these reasons, in our model (we assume that) the DPEP increases voters’ marginal utility from leader competence relative to that from having male leaders.<sup>3</sup> As a consequence, the DPEP leads to an increase (decrease) in the threshold level of competence that male (female) politicians must possess to contest elections as voters increasingly prioritize this attribute over their desire for male leadership.

The model delivers five main predictions. First, the DPEP should increase the probability of female candidates winning elections. Second, the DPEP should decrease (increase) the number of men (women) competing in elections. Third, the average quality of male (female) candidates should improve (decline) in DPEP districts relative to non-DPEP districts. As

> 3The change in voters’ relative utility in the framework occurs due to either a direct increase in voter utility from leader competence, or a decrease in voter utility from leaders being male, or both these channels acting simultaneously.

2
At different poverty thresholds, the paper finds little statistically significant difference between the diary and recall arms. Household characteristics such as employment and education are vital in explaining observed differences in food and total consumption expenditure.

The study is limited in the following ways. First, the implementation of the survey used separate teams for the diary and recall arms, which could explain some of the observed differences in consumption expenditure across the three designs. The analysis did not correct for this. Second, the non-availability of conversion factors forced respondents to report food consumption in standard units, which is very restrictive and difficult, especially for respondents and enumerators with low cognitive prowess.

# **References**

- <mark>Battistin, E., De Nadai, M., & Krishnan, N. (2023). The insights and illusions of consumption measurements.</mark> _<mark>Journal of Development Economics</mark>_ <mark>,</mark> _<mark>161</mark>_ <mark>, 102991.</mark>

- <mark>Bee, A., Meyer, B. D., & Sullivan, J. X. (2012).</mark> _<mark>The validity of consumption data: are the consumer expenditure interview and diary surveys informative?</mark>_ <mark>(No. w18308). National Bureau of Economic Research.</mark>

- Backiny-Yetna, P., Steele, D., & Djima Y.I. (2017). The impact of household food consumption data collection methods on poverty and inequality measures in Niger. _Food Policy_ , 72, 7-19

- Beegle, K., De Weerdt, J., Friedman J., Gibson, J. (2012) **.** Methods of household consumption measurement through surveys: Experimental results from Tanzania. _Journal of Development Economics_ , 98(1), 3-18.

- Belghith, B.H.N., Lopera, A.M., Ndip, E.A., & Karamba, W. (2018). Analysis of the Mismatch between Tanzania Household Budget Survey and National Panel Survey Data in Poverty and Inequality Levels and Trends.  Policy Research Working Paper 8361, World Bank, Washington DC, USA.

- <mark>Bogmans, C., Kearns, J., Pescatori, A., & Prifti, E. (2022). War-fueled surge in food prices to hit poorer nations hardest.</mark> _<mark>IMF blog</mark>_ <mark>,</mark> _<mark>16</mark> ._

- <mark>Brzozowski, M., Crossley, T. F., & Winter, J. K. (2017). A comparison of recall and diary food expenditure data.</mark> _<mark>Food policy</mark>_ <mark>,</mark> _<mark>72</mark>_ <mark>, 53-61.</mark>

- <mark>Christiaensen, L., Ligon, E., & Sohnesen, T.P. (2022). Consumption subaggregates should not be used to measure poverty. The World Bank Economic Review, 36(2), 2022, 413–432.</mark> https://doi.org10.1093/wber/lhab021

25
**In addition to these systematic differences in overlapping variables between both surveys, the sample design slightly differs.** According to information published by the National Statistical Office (2023a), in the case of the EU-SILC in Bulgaria, primary sampling units are census enumeration units. From these units, five secondary sampling units (households) are selected. The HBS follows a similar design but chooses six secondary sampling units (households) from each census enumeration unit (National Statistical Office, 2023b).

**We identify potential auxiliary variables to approximate the underlying conditional independence assumption of statistical matching** . For this purpose, we correlate each of the potential matching variables with energy expenditure shares in the HBS. Table A.3 in the Appendix details the results. The highest correlation coefficient is above -0.37 for the income category variable. There is also a strong correlation between the number of part-time employed household members (-0.2561) and those having tertiary education (-0.192). There is no consensus in the literature on when a correlation coefficient is high enough to approximate the conditional independence assumption. The rule of thumb identified previously in the literature is that auxiliary variables are those variables with a correlation coefficient higher than 0.4 (Johnson and Young, 2011). The income category variable is close to this threshold, although the correlation is negative.<sup>21</sup>

Final Matching Variables via Feature Selection

**To achieve the most parsimonious model possible, we apply lasso regressions and identify those variables most relevant to explaining the energy expenditure share.** In addition to similarity, relevance is another important criterion when choosing matching variables (Serafino and Tonkin, 2017). As the inclusion of too many matching variables could result in unnecessary noise (Donatiello et al.,

> 21 This approach is in line with Donatiello et al. (2016b) who argue that, based on income being measured in both the HBS and EU-SILC, income is a strong auxiliary variable as households who belong to lower income categories in the HBS likely coincide with those in the EU-SILC.

23
average quality of male candidates should improve in DPEP districts relative to non-DPEP districts, while the average competence of women should decline. As the majority of political candidates running for election are male, this should also translate into an increase in average candidate competence in treated districts relative to untreated districts (Prediction 3).

To examine this empirically, in Table 3 we estimate whether the program had an impact on candidate competence using data we collected from candidate affidavits on educational attainment, asset ownership, and criminality. Unfortunately, we do not have a breakdown by gender and so we can only look at average characteristics of the entire pool of candidates. Moreover, this data is only available for 2004-2018, i.e., after the DPEP had ended, as candidate declaration of their attributes was only made a legal requirement in 2004. Hence, this data set is smaller than what we use for our previous results, and our coefficients may be imprecisely estimated. Nevertheless, we find that candidates in DPEP districts are significantly more likely to have secondary education by 15 p.p., which constitutes an 19 percent increase over the already high baseline secondary school attainment rate of 81 percent among candidates in non-DPEP districts. The effect, however, does not remain significant after correcting for multiple hypotheses testing. There is no effect on primary education attainment in column (1), likely due to even higher levels of primary school completion rates among candidates even in the absence of the program (94 percent for candidates in non-DPEP districts). Similarly, we do not find any significant impact on candidates’ criminality and asset ownership.

Although our ability to estimate effects on candidate competence is curtailed by data limitations, the increase in candidate educational attainment that we observe is consistent with an increase in the equilibrium competence level among contesting candidates during post-DPEP years.<sup>14</sup> We wish to stress that, because of the timing of the effects, the increase in candidates’ schooling is unlikely to be the result of the direct impact of the DPEP on education. In Section 7.4, we will discuss this issue in detail.

# **6.3 Prediction 4: Heterogeneity by Gender of Past Winner**

Recall that our results in Table 2 show no statistically significant increase in the total number of female candidates who contest in post-DPEP elections. In addition to societal barriers that prevent women from entering politics in India, parties may also be unwilling to field female candidates if they (correctly or incorrectly) believe that the prospects of female candidates are not good. However, the DPEP-induced increase in women’s probability of winning may have a “demonstration effect” and increase women’s candidacy as political parties respond

> 14The program eligibility criteria continue to have strongly significant impact on treatment probability in the first stage estimates of 23.3-27.8 percent across all columns, for optimal bandwidths of 10.50-11.04 literacy points on either side of the cut-off threshold.

20
and store of value. Finally, many authors define currency substitution as a situation in which domestic money demand is influenced by foreign economic variables.

Another term that has been subject to different interpretations is _dollarization._ Throughout the 1980s, it was common to treat the terms "currency substitution" and "dollarization" as indistinguishable. Both terms described a situation where local residents demand dollars. This misunderstanding follows perhaps from the fact that most of the studies of currency substitution in the 1980s were focused on Latin America, and it is well documented that the substitution of currencies in Latin American countries favored the U.S. dollar. Currently, the term dollarization is also used to describe the replacement, by monetary authorities, of the national currency by the dollar as legal tender.' While there exists a good theoretical understanding of the implications of having two monies, the empirical consequences are still an open issue. It is commonly believed tlhat allowing a foreign currency to coexist with the domestic one provides the opportunity for greater domestic intermediation, promotes financial sophistication by increasing the number of available assets, and increases credibility by raising the cost of monetary indiscipline. Furthermore, the rapid development of foreign currency-denominated operations in the banking system affects the stability of monetary aggregates, the dynamics of exchange rates, and government revenues from seigniorage.<sup>2</sup> Specifically, the higher the demand elasticity of substitution between monies, the larger the shift from foreign to domestic currency as a result of the fall in expected inflation, and thus the higher the fall in the nominal exchange rate. Currency substitution also reduces monetary independence, which may then endanger the ability of central bankers to implement stabilization programs. Finally, currency substitution lessens the central bank's ability to act effectively as a lender of last resort.

The purpose of this paper is to determine empirically the causes and significance of currency substitution in Latin America, as well as to explore some of its macroeconomic consequences in the last decade. Using panel data for thirteen Latin American countries from 1990 to 1998, we estimate a static (one-period) portfolio balance model, where optimal bank deposits denominated in both local currency and dollars are chosen simultaneously. Our results reveal that the dollar deposits to broad money ratio is strongly influenced by depreciation expecta'In the current debate of adopting the dollar as legal tender, a new distinction has developed: unilateral full dollarization, meaning a country adopts the U.S. dollar on its own, versus the unlikely but theoretically feasible multilateral agreement of an economic block with the U.S. dollar as the common currency. 2A good discussion of seigniorage losses due to the adoption of a foreign currency is provided in Fischer (1982).

3
# **TABLE OF CONTENTS**

|**I.**|**INTRODUCTION ................................................................................................................................... 2**|
|---|---|
|**II.**|**THE DEVELOPMENT FRAMEWORK .............................................................................................. 3**|
||1.<br>THEPOST-WARINTERNATIONALSYSTEM............................................................................................ 3|
||2.<br>THEMILLENNIUMDEVELOPMENTGOALS............................................................................................. 4|
||3.<br>SHAPING THEPOST-2015 DEVELOPMENTAGENDA........................................................................... 6|
||4.<br>SUSTAINABLEDEVELOPMENT: ROLE OF THEFINANCIALSECTOR..................................................... 8|
|**III.**|**ISLAMIC FINANCE AND SOCIAL SECTORS**............................................................................................**10**|
||1.<br>RULESGOVERNINGISLAMICFINANCE..................................................................................................... 10|
||2.<br>VOLUNTARY ANDCHARITABLESECTORS(_ZAKAT_AND_WAQF_) ........................................................... 12|
|**IV.**|**ISLAMIC FINANCE AND SUSTAINABLE DEVELOPMENT: PRACTICE AND EVIDENCE ... 14**|
||1.<br>ENHANCINGSTABILITY ANDRESILIENCE OF THEFINANCIALSECTOR.............................................. 14|
||2.<br>INCLUSIVEFINANCE.................................................................................................................................... 18|
||3.<br>REDUCINGVULNERABILITY OF THEPOOR ANDMITIGATINGRISK.................................................... 22|
||4.<br>CONTRIBUTION TO ENVIRONMENTAL AND SOCIAL ISSUES................................................................... 24|
||5.<br>INFRASTRUCTUREDEVELOPMENT........................................................................................................... 28|
|**V.**|**CONCLUDING REMARKS ................................................................................................................... 30**|
|**RE**|**FERENCES ................................................................................................................................................ 31**|

## **TABLES**

|1: EXTENT OFPROGRESS TOWARDACHIEVING THEMDGS,BY NUMBER OF COUNTRIES.............................. 6|
|---|
|2: TRENDS INEQUITY-BASEDSUKUKISSUANCES................................................................................................. 17|
|3: TYPES OFINSTITUTIONSOFFERINGSHARIAH-COMPLIANTMICROFINANCE ANDCLIENTSREACH........ 19|
|4: SUMMARYTABLE................................................................................................................................................... 30|
|**ANNEX TABLES**|

1: FINANCIAL INSTITUTIONS, CAPITAL MARKETS AND SOCIAL SECTORS: PRACTICE AND EVIDENCE ............ 42 2: CONTRIBUTION OF THE FINANCIAL AND SOCIAL SECTORS TO SDGS ............................................................. 43
Russian Federation, Republic of South Africa, Switzerland, the United Kingdom, United States) and Euratom are participating in the planning, testing and development of these systems under the auspices of the Generation IV International Forum (GIF). After an in-depth analysis of the different available technologies and design options, GIF selected six concepts as the most promising, and decided to target all R&D efforts on these systems (table 3): the very-hightemperature reactor (VHTR); the sodium-cooled fast reactor (SFR); the supercritical-watercooled reactor (SCWR); the gas-cooled fast reactor (GFR); the lead-cooled fast reactor (LFR); the molten salt reactor (MSR)—see ANNEX C. Four of the Generation IV designs are hightemperature reactors that can generate both electricity and high-quality process heat for a wide range of industrial purposes—petroleum refining, chemical processes, and large-scale hydrogen production (Bouchard, 2009).

**Table 3 Generation IV systems**

|**SYSTEM**|**NEUTRON**<br>**SPECTRUM**|**COOLANT**|**TEMP (°C)**|**FUEL**<br>**CYCLE**|**SIZE (MWe)**|
|---|---|---|---|---|---|
|**VHTR**<br>Very High Temperature<br>Gas Reactor|thermal|helium|900-1000|open|200-300|
|**SFR**<br>Sodium-cooled<br>Fast Reactor|Fast|sodium|550|closed|30-150<br>300-1500<br>1000-2000|
|**SCWR**<br>Supercritical<br>Water-cooled Reactor|thermal/<br>fast|water|510-625|open or<br>closed|300-700<br>1000-1500|
|**GFR**<br>Gas-cooled<br>Fast Reactor|Fast|helium|850|closed|1200|
|**LFR**<br>Lead-cooled<br>Fast reactor|Fast|lead|480-800|closed|20-180<br>300-1200<br>600-1000|
|**MSR**<br>Molten Salt<br>Reactor|Epithermal|fluoride<br>salts|700-800|closed|1,000|

_Source_ : Bouchard (2009).

27
Policy Research Working Paper 10337

# **Abstract**

This paper studies the impacts of the COVID-19 pandemic on Indonesia’s labor market by exploiting the exogeneous timing of the pandemic in a seasonal difference-in-differences framework. The analysis uses multiple rounds of Indonesia’s National Labor Force Survey from 2016 to 2020 to establish a pre-pandemic employment trend and then attribute any excess difference in employment outcomes from this trend as the estimated effect of the pandemic on individual employment outcomes. The results suggest that the pandemic has had mixed effects on the Indonesian labor market. While the pandemic has narrowed the gender gaps in employment participation through the “added worker effect” among women, it has also lowered the overall employment quality among both gender groups. The findings show that the increase in female employment is primarily driven by women in rural areas without high school education, entering informal work, agricultural employment, or unpaid family work. For men, the pandemic has had adverse impacts on their employment across the board in all sub-populations. Consistent with findings from other studies, steeper employment declines are observed in urban areas, particularly among males. Among those employed, both women and men work fewer hours and earn lower wages.

This paper is a product of the Social Sustainability and Inclusion Global Practice, the Poverty and Equity Global Practice, and the Gender Global Theme. 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 dhalim@worldbank.org and rpurnamasari@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
-v -

|V. CONCLUSIONS|
|---|
|5.1 General|

|Box 0.1|
|---|

||A. Issues|
|---|---|
|5.2|Country Concerns|
|5.4|Theoretical Concerns|
|5.6|Operational Concerns|

||B. Recommendations||
|---|---|---|
|Count|ry Approach||
|5.8|The Territorial Distribution of Population and||
||Economic Activities|Table 1.2|
|.5,.9|Intermediate Cities Programs||
|5.10|Small Towns Programs|Box 10|
|5.11|Large Cities Programs||
|5.12|Reviewing Fiscal Assignment|Table 1.9|
|5.14|Containing Central Government Transfers||
|5.15|Decentralizing Fiscal Authority||
|5.16|Improving the Existing Revenue Sharing Systems||
|5.17|Improving Subnational Administrations||
|5.113|Substituting Borrowing for Grant-Transfers||
|5;19|Assessing Local Capacity and Willingness to Pay||
|5.20|Containing the Growth of Fiscal Deficits||
|Theoret|ical<br>Approach||
|5.21|Intersectoral Allocation of Resources||
|5.23|Spatial Allocation of Resources and Factor Mobility||
|5.25|Equity and Efficiency in Spatial Policy||
|5.26|Fiscal Equity||
|5.27|Approaches to Inter-Area Equalization||
|5.28|Delegating Some Distributive Activities||
|<br>5.29|<br>A Regional Perspective on Investment Distribution||
|5.30|Direct or Indirect Cost Recovery?||
|5.31|Should the Cost of Urban Services be Fully Recovered|?|
|5.32|Setting Targets of Overall Fiscal Performance||
|Opera|tional Approach||
|5.32|Revising the Traditional Bank Approach to Urban Lend|ing|
|5.33|The Conventional Cycle of Project Development||
|5.34|Project Specific or Poverty Alleviation Objectives||
|5.35<br>|The Concern with Project Replicability<br>||
|5.36|The Volume of Urban Development Lending||
|5.37|Leveraging the Impact of External Funding||
|5.38|The Concern with Counterpart Funding||
|5.39|Non Additionality of Bank Lending||
|5.40|A Fiscal Perspective on City Size||
|<br>5.41|<br>Selecting Target Municipalities||
|5.42|Should the Worst Come First?||
|5.43|A Gradualistic Strategy||
|5.44|Inducing Resource Mobilization with Matching Grants||
|<br>5.45|<br>Developing Local Planning Capabilities|Boxes 10, ll, 12|
|5.46|The New Lending Approach: Country Dialogue,<br>Transfer of Responsibilities,<br>Financial||
||Intermediation;<br>Alternative Lending Tools;<br>Research Focus||