rafmacalaba/datause-encoder-data huggingface dataset:
household wealth are significant correlates of attendance. We also show that the supply of schools and teachers is positively associated with attendance, while greater distance to schools and higher levels of school fees are associated with lower attendance.

The finding from the regression results that the poor are much less likely to attend school is compatible with the subjective responses of parents: 43 percent of families of children not attending school report that the major reason is cost.<sup>3</sup> Given these findings, we analyze the determinants of school fees and the market structure of the schooling system. Higher fees are associated with the presence of teaching-related infrastructure and higher teacher quality but are not associated with the presence of recreational facilities or a lower teacher-student ratio. We also find that schools with larger shares of the local educational market charge higher fees.

A number of policy recommendations follow from our analysis. In the shorter run, given that poverty prevents families from sending their children to private schools in Haiti, scholarships or cash transfers can help increase attendance and provide incentives for timely enrollment into grade 1. Additionally, strengthening of the state’s role as regulator and ongoing efforts by the Ministry of Education to license rural schools would allow for better enforcement of a minimum quality of education.

The earthquake that struck Haiti on January 12<sup>th</sup> 2010 has exacerbated the constraining factors on accessing schools. On the supply-side, an estimated 4,228 schools were severely damaged or destroyed, and approximately 1,350 teachers were killed (along with approximately 38,000 students). The Ministry of Education itself was largely destroyed. On the demand side, the earthquake represents a significant reduction in the already low ability of households to pay for private schooling.<sup>4</sup> While the analysis presented here predates the earthquake, the conclusions and corresponding policy implications remain relevant, particularly considering the significant donor resources expected in the coming years for the education sector in Haiti, and the paucity of data to guide those investments.

# **2. The Data**

We draw mainly on the Demographic and Health Surveys (DHS) and the 2003 School Census. The DHS was carried out in Haiti in 1994-95, 2000, and 2005 and is representative at

> 3 World Bank (2006), based on analysis of the 2001 _Enquête sur les Conditions de Vie en Haiti_ . 4 See Government of Haiti (2010) and UNICEF (2010)

3
# **Social Sustainability, Poverty, and Income: An Empirical Exploration**

Jose Cuesta, Lucia Madrigal and Natalia Pecorari* *World Bank, Social Sustainability and Inclusion Global Practice

**Topics:** Social development, social analysis, data for policy analysis **Key words** : Social sustainability, measurement, indices, empirics, global **JEL codes** : I30, D63

_This paper exclusively reflects the views of the authors and does not necessarily represent those of the World Bank nor its Board of Directors. The authors thank E. Bardasi, P. Barron, P. Ballon, L. Cord, M. Cloutier, R. Damania S. Espinoza, A. Kraay, A. Narayan, G. Larson, S. Onder and M. Woolcock for useful feedback and suggestions. All remain errors are solely the responsibility of the authors._
# **How Does Long-Term Finance Affect Economic Volatility?**<sup>**1**</sup>

Asli Demirgüç-Kunt World Bank Bálint L. Horváth Tilburg University and World Bank Harry Huizinga Tilburg University and CEPR

**Keywords** : Debt maturity; financial dependence; firm volatility; financial development **JEL classification** : G20, G32, O16

> 1 This paper’s findings, interpretations, and conclusions are entirely those of the authors and do not necessarily represent the views of the World Bank, its Executive Directors, or the countries they represent.
<!-- Start of picture text --> 45<br>AD 36.3<br>= Venezuela<br>35 @ Ukraine<br>50 30.1 BkKyrgyz Rep.<br>24.9 Bg Algeria<br>25 22.4 22.4 m Kazakhstan<br>21.0 20.9 20.8<br>50 loa 19.2 B Mongolia<br>@ Russian Federation<br>15 Blran<br>10 @ Tajikistan<br>= Saudi Arabia<br>5<br>oO<br><!-- End of picture text -->
**Table 10: long-term impacts of the 4P program on empowerment - time-use**

||Fraction of our<br>t<br>|s spent on acti<br>otal 24 hours<br>|vity; out of<br>|Fraction of ho<br>of to<br>|urs spent on<br>tal awake hou<br>|activity, out<br>rs<br>|
|---|---|---|---|---|---|---|
||Household<br>activity|Paid<br>activity|Unpaid<br>activity|Household<br>activity|Paid<br>activity|Unpaid<br>activity|
||||**Wo**<br>|**men**<br>|||
|ITT|0.015|-0.013|-0.001|-0.025|-0.128|-0.004|
||(0.33)|(0.35)|(0.80)|(0.68)|(0.22)|(0.80)|
|Observations|436|436|436|422|422|422|
|Adj. R2|0.04|0.02|-0.06|-0.00|0.02|-0.06|
|Control mean|0.240|0.059|0.010|0.668|0.261|0.026|
||||**M**|**en**|||
|ITT|0.013|-0.002|0.001|0.082|-0.072|-0.010|
||(0.25)|(0.91)|(0.87)|(0.17)|(0.27)|(0.64)|
|Observations|435|435|435|418|418|418|
|Adj. R2|0.00|0.03|0.06|-0.02|0.02|0.10|
|Control mean|0.095|0.121|0.018|0.257|0.392|0.056|

P-values in parentheses: * p<0.1 ** p<0.05 *** p<0.01 33
<!-- Start of picture text --> Daughters' Primary Completion Estimates by Birth Year<br><!-- End of picture text --> <!-- Start of picture text --> Intercept Linear Coefficient Quadratic Coefficient<br>.05 .006<br>4<br>4 .004<br>><br>2 a Se a :<br>$ .002<br>><br>> ¢ J<br>a em ee a _ -_-_ 05 ><br>—_- - T ItOO CS Oo Or Ore -<br>><br>2 -.002<br>-1<br>59 60 61 62 68 69 70 71 72 59 60 61 62 68 69 70 71 72 59 60 61 62 68 69 70 71 72<br><!-- End of picture text --> Birth Years Omitted Birth Year 1957-58 © Comparison Cohort @ Fullly Exposed Cohort
Jhajharia, D. and V.P. Singh, 2011. Trends in Temperature, Diurnal Temperature Range and Sunshine Duration in Northeast India. International Journal of Climatology 31: 1353-1367.

- Kalra, N., P.K. Aggarwal, S. Chander, H. Pathak, R. Choudhary, A. Choudhary, S. Mukesh, H.K.Rai, U.A.Soni, S.Anil, M.Jolly,U.K.Singh, A.Owrs and M.Z.Hussain, 2003. Impacts of Climate Change on Agriculture. In PR Shukla, SK Sharma, NH Ravindranath, A Garg and S Bhattacharya (Eds.) Climate Change and India: Vulnerability Assessment and Adaptation. Orient Longman Private Ltd., Hyderabad. pp. 193-226.

Kargel J.S., R. Armstrong, Y. Arnaud, E. Berthier, M. P. Bishop, T. Bolch, A. Bush, G. Cogley, K. Fujita, A. Gillespie, U. Haritashya, G. Kaser, S. J. S. Khalsa, G. Leonard, A. Racoviteanu, B. Raup, and C. Van derVeen, 2009. Satellite-era glacier changes in High Asia. Background support presentation for NASA “Black Carbon and Aerosols” press conference associated with Fall AGU, Dec. 14, 2009 Kargel, J.S., J.G. Cogley, G.J. Leonard, U. Haritashya, and A. Byers, 2011. Himalayan Glaciers: the Big Picture Is a Montage. Proceedings of the National Academy of Sciences 108: 14709-14710.

Kaser, G., M. Großhauser, and B. Marzeion, 2010. Contribution Potential of Glaciers to Water Availability in Different Climate Regimes. Proceedings of the National Academy of Sciences 107: 20223-20227.

Kaspari, S.D., M. Schwikowski, M. Gysel, M.G. Flanner, S. Kang, S. Hou, and P.A. Mayewski, 2011. Recent Increase in Black Carbon Concentrations from a Mt. Everest Ice Core Spanning 1860–2000 AD. Geophysical Research Letters 38: L04703, doi:10.1029/2010GL046096.

Kattelmann, R., 1993. Role of Snowmelt in Generating Streamflow During Spring in East Nepal In: Snow and Glacier Hydrology. IAHS Publication 218: 103–111.

Kattelmann, R., 2003. Glacial Lake Outburst Floods in the Nepal Himalaya: A Manageable Hazard? Natural Hazards 28: 145-154.

Kehrwald, N.M., L. Thompson, Y. Tandong, E. Mosley-Thompson, U. Schotterer, V. Alfimov, J. Beer, J. Eikenberg, and M. Davis, 2008. Mass Loss on Himalayan Glacier Endangers Water Resources. Geophysical Research Letters 35: L22503, doi:10.1029/2008GL035556.

36
# **Table of Contents**

|Acknow|ledgments........................................................................................................................... 3|
|---|---|
|Acrony|ms ........................................................................................................................................ 4|
|1<br>Int|roduction ............................................................................................................................. 5|
|2<br>Ris|k analysis and measurement process .................................................................................. 7|
|2.1|Context and defining characteristics ................................................................................ 7|
|2.2|Credit risk analysis ........................................................................................................... 9|
|2.3|Credit risk quantification ................................................................................................ 13|
|2.4|Application in risk management .................................................................................... 15|
|3<br>Co|untry examples in developing and applying a risk analysis and measurement framework|
|18||
|3.1|Colombia ........................................................................................................................ 18|
|3.2|Sweden ........................................................................................................................... 22|
|3.3|Turkey ............................................................................................................................ 26|
|3.4|Indonesia ........................................................................................................................ 29|
|3.5|Key insights from country examples .............................................................................. 36|
|4<br>Co|nsiderations in implementing a risk analysis and measurement framework ..................... 38|
|5<br>Co|nclusion ............................................................................................................................. 40|
|Append|ix A - Stylized summary of risk management practices in four countries ....................... 42|
|Bibliog|raphy ................................................................................................................................. 43|

2 | P a g e
# **METHODOLOGY FOR THE ASSESSMENT OF DATA QUALITY: APPLICATION TO HIV AND AIDS PROGRAMS IN LATIN AMERICA**

Rosalía Rodriguez-García, Michel Eric Gaillard, Alejandra Suarez Lissi, and Pedro Magne Condarco<sup>1</sup> The World Bank <u>Keywords: Data quality, HIV and AIDS, Andean Region</u>

**The Spanish version of this study is included at the end of this report.**

1 The authors are staff or consultants with the Global HIV and AIDS Program, HNP, Human Development Network. The paper benefited from a peer review process that included specialists who reviewed the English and Spanish versions. The authors wish to thank and acknowledge the reviewers listed in the appendix for providing useful comments and insights. The authors would also like to acknowledge the support of David Wilson, Director for HIV and AIDS at the World Bank. The opinions expressed in this paper are those of the authors only and need not represent the views of the World Bank, its Executive Directors of the countries they represent.
**Figure 2:** Distribution of perceived oxen skill level for main household members

<!-- Start of picture text --> None 1 2 3 or higher<br>Reported oxen skill<br>Producer Boys<br>Spouse Girls<br>Note: Oxen skill reported by the household head for all household members on a 0-10 scale.<br>100<br>80<br>60<br>40<br>Percent of sample<br>20<br>0<br><!-- End of picture text --> The presence of social norms regarding handling oxen is reinforced by the existence of district-level patterns in the likelihood that women work with oxen. In our survey data, almost a third of households reside in districts where other households’ spouses performed fewer than one in three agricultural oxen tasks (sowing/weed, plow, or transport) over the prior year, while another third reside in districts where women performed at least 1.33 tasks. The intra-household labor impacts from the distribution of oxen are likely to critically depend on norms around the appropriateness of women working with oxen.

Women’s likelihood of working with oxen is highly correlated with broader district-level descriptive norms regarding women’s decision-making over their own health care, large household purchases, and visits to family and relatives (correlation coefficient of 0.75). Districts in which women are less likely to work with oxen are also those where women have less overall decision-making power. Regional patterns in these norms are shown in Figure 3.<sup>11</sup> Underlying these patterns in women’s decision-making is variation in kin-

> 11 We use the three standard DHS women’s decision-making questions (decision-making around women’s health care, large household purchases, and visits to family and relatives) to define a household-level decision-making index. We then take the median within each third-level administrative region, or districts (d ́epartements), and characterize districts as either high or low decision-making if they are above or below the median district. The main assumption underlying this approach relates to the mapping of DHS clusters to administrative geographic visions. Specifically, the DHS does not report the third-level geographic administrative division (d ́epartment) that we use to characterize the sample. We rely on the reported geo-coded coordinates to map clusters to departments. These coordinates are shifted up to 5km, with 1% of clusters shifted up to 10km. Our approach assumes that the clusters do not shift across department boundaries.

10
- Rentschler, J., Kornejew, M. (2017). Energy price variation and competitiveness: firm-level evidence from Indonesia. _Energy Economics_ 67, 242–254.

- Sadorsky, P. (1999). Oil Price Shocks and Stock Market Activity. _Energy Economics_ , 21(5), 449–469.

- Across Firms. _Environmental and Resource Economics_ , 72(4), 935–962.

- _Journal of Environmental_

- _Economics_ , 67(2), 345-370.

Stern, D. I. (2013). The Role of Energy in Economic Growth. _Energy Economics_ , 40, 15–22.

Syverson, C. (2011). What Determines Productivity? _Journal of Economic Literature_ , 49(2), 326–365.

- Van den Bergh, K., & Delarue, E. (2023). Energy subsidies and technological inertia: A cross-country comparison. _Energy Policy_ , 48(5), 587-601.

World Bank. (2024). _Energy Subsidies and Economic Growth_ . World Bank Group.

- Yusuf, S., Nabeshima, K., & Perkins, D. H. (2006). _Under New Ownership: Privatizing China's State-Owned Enterprises_ . Stanford University Press.

15
Policy Research Working Paper 5382

# **Abstract**

Using a stochastic general equilibrium model with overlapping generations, this paper studies a policy rule for the retirement age aiming at offsetting the effects on the supply of labor following fertility changes. The authors find that the retirement age should increase more than proportionally to the direct fall in labor supply caused by a fall in fertility. The robustness of this result is checked against alternative model specifications and parameter values. The efficacy of the policy rule depends crucially on the link between the preference for leisure and the response of the intensive margin of labor supply to changes in the statutory retirement age. The model has subsequently been calibrated for Brazil by Jorgensen (2010), in the context of the Brazil Aging Study.

This paper—a product of the Economic Policy Sector, Poverty Reduction and Economic Management in the Latin American and Caribbean Region—is part of a larger effort in the department to understand the economic implications of population dynamics in less developed economies, as well as being a contribution to the Brazil Aging Study (http://go.worldbank.org/ NMFNG40F30). Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted at ojorgensen@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
# **Appendix.**

# **Banco Azteca Serves Low-Income Customers**

As of the opening date, “the bank was the first and only all-Mexican-owned franchise to be licensed by the Finance Ministry since 1994. It is also the first bank to aim at Mexico's middle and working classes: the 73 million people who live in households with combined family incomes of $250 to $4,000 a month, a mass market largely neglected by Mexico's banking system.”<sup>17</sup> Before Azteca, access to credit was largely unavailable to millions of informal businesses, such as taxi drivers, plumbers or street merchants. Banco Azteca officials claimed that credit will be more available to Mexico's large informal sector, the small businesses and selfemployed who operate outside regulatory frameworks.<sup>18</sup> “Banco Azteca SA, a new bank belonging to retail giant Grupo Elektra SA, wants to woo the millions of teachers, plumbers, cabbies and sidewalk vendors who traditional banks have long shunned.” "Mexican banks are focused on the sectors with the highest income," said Carlos Septien, Banco Azteca's chief executive officer. "We're aiming for the C and D segments, which represent 70 percent of the population, or about 16 million families."<sup>19</sup> Commenting on the start-up of operations of the bank, Ricardo B. Salinas, Chairman of the Board of Grupo Elektra, stressed that: "Banco Azteca will improve access to goods and services for our people. A major impediment to the growth of the Mexican middle class has been the lack of access to credit, one of the main vehicles for personal financial improvement. Banco Azteca will demonstrate the importance of offering financial services to this under- served segment of the Mexican population." (Reuters, 2002) Banco Azteca benefited from synergies with their retail operations, which provided a rich source of data on their customers. With Elektra's 48 years of know-how in loaning to lowerincome consumers, the Banco Azteca obtained information on about 4 million borrowers. Many of those customers buy Elektra's products, develop film at its stores or receive money transfers from the United States through Western Union. “We know this segment of Mexican society better than anyone else,'' says Banco Azteca President Carlos Septien.<sup>20</sup> “The sophisticated technology and collection systems already in place at Grupo Elektra will provide us with invaluable data about our customers' buying habits and financial needs, allowing us to succeed." The group has spent $20 million a year over three years on information technology, including high-tech “fingerprint readers” that eliminate the need for customers to present IDs or passbooks. The bank also commands a 3,000-strong army of motorcycle-riding loan agents.

> 17 The New York Times, 31 December 2002. 18 The New York Times, 31 December 2002.

> 19

> By Brendan M. Case, The Dallas Morning News, 31 October 2002. 20

> Business Week, 13 January 2003

17
41 government consumption. The data are derived from **Summers** and Heston (1984), the Government Financial Statistics (IMF, 1986) and other sources, and are discussed in more detail in Engen and Skinner (1988). The Summers and Heston data have been converted to internationally comparable price levels, and have been widely used in cross-country studies. I begin first with ad-hoc linear models of taxation and national output, and of government spending and national output. Second, Ram's model of government spending, and Engen and Skinner's model which includes both government spending and taxation, is presented. Finally, potential shortcomings of these cross-country estimation models are discussed.

The study by Marsden (1983) was among the first to test the hypothesis that taxes should affect output growth rates.<sup>1 3</sup> He matched 10 high tax countries, ouch as Zambia, Britain, Chile, and Zaire, with 10 low tax countries such as Singapore, Korea, Uruguay, and Japan. The country pairs were chosen on the basis of "similar per capita incomes but contrasting tax levels," and the difference in growth rates for the two sets of countries were then calculated. Countries with high tax rates (defined to be the ratio of tax revenue to GDP) experienced a lower average growth rate than those with low tax rates. Marsden's results imply that "an increase of

> 13 The earlier literature on taxation and output focused on the opposite question -- what is the "appropriate" tax effort for a country in a particular stage of development. The direction of causation is modeled in reverse; GDP, the independent exogenous variable, affects the choice of tax effort, the dependent variable (Newlyn, 1985; Tanzi, 1987).
scores, particularly math, and future labor market outcomes has been documented also for the United Kingdom and Sweden (Lindqvist and Vestman, 2011; Meghir et al., 2013). But high school test scores, are, in turn, predicted by test scores at earlier grades, meaning that early grade test scores can, in principle, predict labor market outcomes. Chetty et al. (2011) show that test scores at kindergarten are a good predictor of college attendance, earnings at age 27, home ownership and savings for retirement. Although evidence on the importance of early test scores for future education outcomes is very scarce, data for the United Kingdom shows that higher test scores at age seven relate to higher test scores at age 16 (Lindqvist and Vestman, 2011).

To the best of our knowledge, our paper is the first exploiting individual-level information on the association between test scores and future education and labor market trajectories in a developing country. In addition, the present paper contributes to the literature on the relevance of standardized tests showing that, despite their limitations, test scores from large-scale, census-based, assessments have a strong relationship with future outcomes, and that this relationship goes beyond socio-economic status. Furthermore, we find evidence that supports the case that these assessments can accurately capture the foundational skills that they are designed to measure, and that these skills are persistent over the years of a young person’s life. Our results are particularly interesting because they come from a national education system where people were subject to types of incentives that can result in score inflation. The results presented here have two important policy implications. First, they support the design and implementation of this type of assessments on a broad scale. Second, and importantly for the income inequality and social mobility agendas, results from large-scale assessments, especially those of early grades, could be used to target resources towards schools serving students with the lowest learning levels—which tend to be the poorest. In a country like Mexico, with a large concentration of wealth and high income disparities, building a public education system that guarantees foundational skills to all children and youth can be an effective strategy to reduce income inequality and promote social mobility.

The paper is organized in the following way. After this introduction, Section 2 de5