rafmacalaba/datause-encoder-data huggingface dataset:
# **Social Protection in Latin America: Achievements and Limitations**

Francisco H.G. Ferreira and David Robalino The World Bank<sup>1</sup>

**Keywords:** Social Protection, Social Assistance, Social Insurance, Latin America **JEL Codes:** H53, H55, I38, N36

> 1 This paper was commissioned as a chapter for the _Oxford Handbook on Latin American Economics_ , edited by José Antonio Ocampo and Jaime Ros. We are grateful to the editors and to Augusto de la Torre, Emanuela Galasso, Margaret Grosh, Santiago Levy, Helena Ribe, Norbert Schady and Ian Walker for comments on an earlier version of the paper, and to Carlos Prada for excellent research assistance. We would also like to thank Helena Ribe and Ian Walker for permission to draw on their recent joint work with Robalino in the World Bank’s regional study “ _From Right to Reality: Towards an Integrated and Equitable Social Protection System that Works in Latin American and Caribbean Labor markets_ ” (Ribe, Robalino and Walker, forthcoming). The views expressed here are those of the authors, and they should not be attributed to the World Bank, its Executive Directors, or the countries they represent.
One possible identification issue regarding the exclusion restriction may be that fluctuations in oil prices directly affect the relative attractiveness of wage and self-employment activities in the home country (El-Mallakh and Wahba 2021). This might occur, for instance, when wage and self-employment work are concentrated in different sectors in Bangladesh. Two arguments mitigate this concern: First, our estimation conditions on a full set of year effects, so that only the interaction with destination country-specific oil shares in GDP provide the identifying variation.

Second, in our sample, the majority (two-thirds) of returned migrants living in rural and semi-urban areas work either in small-scale agriculture or retail businesses. According to the 2016 industry-level Input-Output tables for Bangladesh, both sectors have a very small share of their input values coming from “Coke or refined Petroleum”.<sup>23</sup> We do, however, observe a slightly higher importance of the transportation sector for the self-employed (21 percent) compared to wage workers (15 percent) in the sample. Since transportation is more dependent on oil-derived inputs compared to other sectors, we also run our IV estimation on a sample that excludes people employed in transportation. The results of this robustness check are reported in Table A2, and show that the IV coefficients are virtually identical when the transportation sector is excluded.

We next investigate changes in the share of self-employment among non-migrants over time, and a possible association with fluctuations in oil prices. We explore these potential connections to provide further evidence that oil prices do not directly affect the relative attractiveness of self-employment and wage work. We use several waves of the Bangladesh Labor Force Survey, which is nationally representative and available at several points in time between 2000 and 2017. We focus on workers who have not migrated overseas. As shown in Figure A1, the fraction of those who did not migrate and who are self-employed in rural and semi-urban areas (the areas covered by the BRMS) is fairly stable over time. In short, we do not observe any noticeable association between the share of self-employment in Bangladesh and large fluctuations in oil prices over time.

As the instrument primarily operates through its effect on the duration of stay abroad, another potential threat is that duration of stay may affect self-employment odds after return in ways that extend beyond effects on total earnings abroad. This could occur, for example, if a longer duration abroad reduces the likelihood of finding a wage job back in Bangladesh, due to a loss of social networks and contacts with local employers. However, as we have previously discussed, self-employment is typically preferred by workers in Bangladesh. Therefore, it is unlikely that workers who spent a longer time abroad would turn to self-employment because they encounter more frictions in finding a wage job. To provide further evidence on this,

> 23The ratio is around 1.2 percent in agriculture and 0.2 percent in retail.

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**Figure 4.0  Scatterplot of Civic Activism (2005) and the Environmental Performance Index (2006)**

<!-- Start of picture text --> 0.9<br>Sw eden<br>Sw itzerland<br>United States<br>0.8 Belgium Denmark<br>Netherlands United Kingdom<br>France<br>Germany<br>Spain<br>0.7 Korea, Rep. Czech Republic<br>Portugal<br>India<br>Indonesia Poland<br>Ukraine Slovenia Malaysia<br>Mexico<br>0.6<br>Peru Russian Federation<br>Tunisia<br>Jamaica<br>Vietnam Paraguay Panama Costa Rica<br>Kenya Uganda<br>0.5 Mozambique Zambia Armenia Cuba<br>Mauritania PakistanNigeria Liberia Tanzania Algeria Gabon<br>Mali<br>Kyrgyz Republic<br>Sudan Togo<br>0.4 Ethiopia<br>Guinea<br>Niger Angola<br>Uzbekistan Moldova<br>0.3 Haiti Myanmar<br>0.2<br>20 30 40 50 60 70 80 90 100<br>Environmental Performance Index<br>Civic Activism<br><!-- End of picture text --> The level of electoral democracy is significantly positively correlated with the ESI in virtually all regressions run. In column (i) of Table 4.0, both Civic Activism and democracy are statistically significant with positive point estimates. This implies that _both_ whether a country is democratic (as measured by the _Voice and Accountability_ index) and the extent to which individuals engage with the political process (as measured by the index of civic activism) are important in explaining cross-country environmental performance.

# **Institutions and Climate Change Mitigation**

If institutions have any role in bringing about improved environmental governance, this should imply some observable association, over time, between the presence of certain norms and concrete indicators of environmental performance. We can examine further whether such an association is observable, by taking data on reductions in carbon intensity (the ratio of gross domestic product to carbon emissions) over time.

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Policy Research Working Paper 9392

# **Abstract**

This paper analyzes the main trends and patterns of nominal lending interest rates and lending-deposit interest rate spreads in emerging markets and developing economies. Using data from 140 emerging markets and developing economies, analysis shows that nominal lending rates and spreads declined between 2003 and 2017, with regional heterogeneity. In addition, it finds that less economically and financially developed countries tend to exhibit higher lending rates and spreads. These higher rates tend to be driven by higher spreads, not deposit interest rates. Also, illustrative regressions suggest that relevant correlates of nominal lending rates include inflation, public debt, and policy interest rate (macro-fiscal conditions); overhead costs, nonperforming loans, and non-interest income (banking characteristics); and credit bureau coverage and time to resolve insolvency (business environment). Finally, illustrative decompositions of the level and 10-year change between 2007 and 2017 of nominal lending rates find relative differences across regions. On the decline of nominal interest rates in that decade, rising public debt and nonperforming loans have pushed rates up, which was counterbalanced by a reduction in inflation, the policy interest rate, and overhead costs and a better business environment. Since the global financial crisis, a common global factor has increased in importance and has contributed to the downward trend in nominal lending rates.

This paper is a product of the Finance, Competitiveness and Innovation 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 efeijen@worldbank.org and izuccardi@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
# **1 Introduction**

This paper investigates the existence and size of benefits from access to sanitation on child health outcomes in rural India. We emphasize in particular two sources of benefit. The first is a direct benefit, which is privately enjoyed by a household whose members stop defecating in the open, and move to either fixed-point defecation or an improved sanitation facility.<sup>1</sup> The second benefit is an external benefit, also called externality, generated by a neighbor’s access to sanitation that results in a lower probability of human contact with human excreta. In this paper we seek to answer two questions: (i) what is the private benefit of a household’s access to sanitation infrastructure on early childhood health outcomes?; and (ii) what is the benefit produced through externalities of a neighbor’s access to this sanitation infrastructure? These questions are motivated by the poor sanitation situation worldwide, where by the end of 2011, 2.5 billion people still lack access to improved sanitation (JMP, 2013). In India alone there are an estimated 62 percent of households without improved sanitation and 51 percent of households practice open defecation (Figure 4). This lack of access to adequate sanitation supposedly leads to diarrheal diseases in children and has been linked to child malnutrition and mortality. But the existence of evidence supporting the relationship between access to sanitation infrastructure and diarrhea prevalence is largely anecdotal, and a small proportion based on empirical evidence. Hence, there is a need to empirically quantify the benefits of sanitation infrastructure, as well as the sources of these benefits to develop more efficient policies and with higher impact.

We estimate a model for the individual production function of health for children in rural India assuming a linear-in-parameters approximation. The main inputs to the function are the household’s access to sanitation and the ratio of access to sanitation (i.e. coverage) at the village level. This model is estimated using a sample of 206,414 children from households in rural villages of India from the District Level Household Survey 2007-08 (DLHS-3). One of the novel features of this model is that we have a measure for the estimation of sanitation externalities impact through use of a robust proxy for village access to sanitation facility. Using this approach we can separate the direct from the externality benefits of sanitation, and analyze how households benefit from different levels of sanitation coverage.

## This paper contributes to the literature of the health impact of sanitation access in two

1In this paper we refer to ‘fixed-point defecation’ as defecation into a pit or other containment structure, regardless of the quality of the structure or whether it is hygienically maintained (i.e. includes access to both improved and unimproved facilities). The Joint Monitoring Program defines ‘improved sanitation’ as, “access to a sanitation facility that hygienically separates human excreta from human contact”. Open defecation is defined as, “not having access to any type of toilet” and implies ‘going in the field’.

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in 1979. In addition, the whole distribution shifted downwards with respect to 1974. There was also a further reduction in as of 1982.

The trend in trade reforms is broken in 1982; there was a slight increase in average tariffs starting in 1982 and continuing all throughout the eighties. In contrast, tariffs were reduced again in 1990 and 1991, remaining below 20% throughout the decade. In 1994, Mercosur was adopted and tariffs were further reduced. However, in an attempt to prevent the fiscal crisis, there was a slight increase in tariffs in 2001.<sup>4</sup> We turn now to the labor force data. The standard source of individual data on labor earnings and worker characteristics in Argentina is the Permanent Household Survey (EPH, Encuesta Permanent de Hogares). This is a typical labor force survey with information on wages, employment status, and individual and family characteristics (age, gender, family size, etc.). The data are usually collected twice a year, in May and October. The labor force surveys EPHs of the 1990s have been already used in the literature but, for our purposes, we needed to track the surveys back into the 1970s and 1980s. We were able to compile 40 EPH surveys. Table A3 in the appendix provides a brief description of the different data sets used here and their sample sizes. We have data for all years, except for 1979, 1983, and 1984. For years 1974, 1976, 1977, 1978, 1981, 1985, 1986, and 1992, we only have information for October (and thus not for May). In contrast, in 1980 and 1982, we use data on May but not on October.

To compute the skilled wage premium, we define at this stage three educational categories: skilled labor, which comprises workers who have finished college, semiskilled labor, which comprises workers who have finished secondary school (and may have incomplete college education), and unskilled labor, which comprises workers with no schooling, complete and incomplete primary education, and incomplete secondary education. The skill premium is calculated as the coefficient on the skilled dummy in a standard wage regression. Concretely,

> 4Trade policy is not limited to tariffs but includes non-tariff barriers like quotas, or quantitative restrictions. Unfortunately, we were unable to construct adequate measures of non-tariff barriers for the period under analysis. However, the historical accounts on the use of quotas in Argentina reveal that they were eliminated around 1959 and were not active until after 1982. Quantitative Restrictions were maintained during the eighties and were fully eliminated at the end of the 1980s as a pre-requisite to Mercosur negotiations. For more details, see Berlinski (1994) and Berlinski (2003).

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Figure 8. Government debt after global recessions, by region

# A. EAP

<!-- Start of picture text --> Index, t = 100<br>200<br>Previous global recessions 2020<br>150<br>100<br>50<br>t-2 t-1 t t+1 t+2 t+3 t+4 t+5<br>C. LAC<br>Index, t = 100<br>200<br>Previous global recessions 2020<br>150<br>100<br>50<br>t-2 t-1 t t+1 t+2 t+3 t+4 t+5<br>E. SAR<br>Index, t = 100<br>140<br>Previous global recessions 2020<br>120<br>100<br>80<br>t-2 t-1 t t+1 t+2 t+3 t+4 t+5<br><!-- End of picture text --> Source: Kose et al. (2021).

# B. ECA

<!-- Start of picture text --> Index, t = 100<br>110<br>Previous global recessions 2020<br>100<br>90<br>80<br>70<br>t-2 t-1 t t+1 t+2 t+3 t+4 t+5<br>D. MNA<br>Index, t = 100<br>200<br>Previous global recessions 2020<br>150<br>100<br>50<br>t-2 t-1 t t+1 t+2 t+3 t+4 t+5<br>F. SSA<br>Index, t = 100<br>220<br>Previous global recessions 2020<br>180<br>140<br>100<br>60<br>t-2 t-1 t t+1 t+2 t+3 t+4 t+5<br><!-- End of picture text --> Note: Swathe indicates the evolution of government debt in percent of GDP, indexed at 100 in the year of the global recession (year “t”). The previous global recessions include four global recessions: 1975, 1982, 1991, and 2009. For ECA, due to the data availability, only the global recession in 2009 is considered. The solid blue line is for the 2020 global recession. Data are available for up to 153 EMDEs, including 23, 24, 33 18, 8, and 47 countries in EAP, ECA, LAC, MNA, SAR, and SSA, respectively.

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questions such as how young is too young to work, are some work activities better or worse than others, does work impair the health of children and does combining work and school hinder learning remain largely unanswered. This paper seeks to provide an answer the last of these questions and contributes to the literature by assessing the impact of working while in school on learning as measured by the proficiency of students in the S ̃ao Paulo municipal school system through their performance on standardized exams.

Perhaps the main reason for the dearth of received evidence on the impact of child work is the inherent difficulty in uncovering causal linkages between the activities of children and their subsequent outcomes. The e↵ects of confounding and unobserved variables are persistent problems that are difficult to overcome. In this study, we utilize a unique panel data set of the standardized test scores of Brazilian children in the metropolis of S ̃ao Paulo that allow us to explore the causal link between the work activity of children and its e↵ect on their exam performance.

We find that, controlling for individual time-invariant unobservable characteristics, working while remaining in school has a depressing e↵ect on their proficiency test scores. The magnitude of these e↵ects range from 3% of a standard deviation in test scores to 8% which represents from one quarter to one half of a year of lost learning. Additionally, we find that the magnitude of the negative impact increases with a students ability and that there are both lingering and cumulative negative e↵ects from working while in school. These results provide valuable information to policy makers who wish to understand what types of child work to target for elimination and the e↵ect of child labor on human capital accumulation. As these are short-run e↵ects, it is likely that the long-run impact of the will be quite a bit larger. Additionally these results apply only to those who remain in school, factoring in drop-out and grade repetition would certainly increase the magnitude of the impact of 3
# **1 Introduction**

Female entrepreneurship is an important vehicle for women’s empowerment and economic growth (Duflo, 2012). Yet, women only represent 34% of all business owners worldwide (World Bank, 2020), and a gender gap in firm performance has been shown across a number of country contexts (De Mel, McKenzie and Woodruff, 2009; Fafchamps et al., 2014; Berge, Bjorvatn and Tungodden, 2015; Hardy and Kagy, 2018; World Bank, 2019). Labor economists who study the gender wage gap often highlight a childcare constraint and motherhood penalty to explain remaining gender inequalities in labor market outcomes (Goldin, 2021; Bertrand, 2020). However, in entrepreneurship, there is less evidence linking childcare and gender inequalities in firm performance, with a few exceptions (see for example, Delecourt and Fitzpatrick (2021)).

This paper examines childcare as a constraint to women’s entrepreneurial success. Specifically, we examine the impact of national school closure policies related to COVID-19 on business outcomes, disaggregated by the gender of the firm owner. We consider a governmentmandated COVID-19 school closure policy within a country as a shock to the domestic and childcare-related activities for households.<sup>1</sup> Overall, the COVID-19 pandemic has led to increased scrutiny on the public policies around childcare and norms around unpaid domestic and care work. For example, in the US there were frequent media reports of a greater exodus of women from the labor market, largely due to the increase in the domestic work burden as a result of the closures of schools and childcare facilities (Pitts, 2021).

The paper asks whether COVID-19 related school closure policies had a differential impact on the time spent on care and domestic responsibilities and business performance outcomes for male and female entrepreneurs. To shed light on this, the paper links entrepreneurlevel and firm-level data collected from business owners across 50 countries in 2020 and 2021 1According to UNESCO, more than 1.5 billion children were out of school in April 2020, with a quarter of a billion still out of school by the end of October 2020. Moreover, the COVID-19 pandemic has also dampened or removed the possibility of informal childcare through extended family support networks (UNESCO, 2020 and 2021).

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regime has been of a relatively short duration, as the memories of suffering seems to be more vivid and the emotions correspondently strong. A long term dictatorship must also have acquired a minimum level of consensus among a significant part of the population and has been able to establish more routinized mechanisms of social control (de Brito, Gonzalez-Enriquez & Aguilar, 2001: 309). Extending this logic to peace-building, we may also assume that long-lasting conflicts are less likely to result in PCJ, as both wrongdoers and victims may be more difficult to identify, and the emotions from suffering are less associated with particular acts or events. In the peacebuilding literature the findings have, however, been mixed, making our expectations regarding conflict-duration and transitional justice somewhat vague. Since the data we rely on allows us to control for the precise length of the conflict period, an analysis of the influence of conflict duration and transitional justice on peace can easily be conducted.

A third factor emphasized by scholars of democratization and transitional justice is the nature of the ideological preferences and the commitments of the new democratic forces or leadership (e.g. de Brito, Gonzalez-Enriquez & Aguilar, 2001). Since the probability of sustainable peace might depend on regime type, and some types of PCJ are more common in democratic societies, post-conflict regime type will be controlled for in the analysis. In the second part of the analysis, the same data on regime type are used to distinguish between PCJ in democratic and non-democratic societies. We expect the influence of truth-commissions and reparation to victims, in particular, to be more important in post-conflict democratic societies.

A states’ ability to carry out PCJ depends on the availability of institutional, human, and financial resources to carry out the processes of justice. More well-to-do states should, therefore, be better equipped for PCJ as well as peace, which is why we control for GDP/capita in the analyses.

# **Method**

To analyze the duration of post-conflict peace we use a Cox proportional hazards model. The data for this analysis are structured as multiple-record data with multiple events with censoring. Given that civil wars frequently occur in the same country at different points in time, and indeed with the Uppsala-PRIO data, more than one armed civil conflict can occur contemporaneously, we must also account for a separate peace period after the resolution of conflict between 10
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