rafmacalaba/datause-encoder-data huggingface dataset:
Hargrove, J. W., J. H. Humphrey, K. Mutasa, B. S. Parekh, J. S. McDougal, R. Ntozini, H. Chidawanyika, L. H. Moulton, B. Ward, K. Nathoo, P. J. Iliff, and E. Kopp. 2008. 'Improved HIV-1 incidence estimates using the BED capture enzyme immunoassay', _AIDS_ , 22: 511-8.

- Health, National Department of. 2011. "The National Antenatal Sentinel HIV and Syphilis Prevalence Survey, South Africa, 2010." In.

- ———. 2012. "The National Antenatal Sentinel HIV and Syphilis Prevalence Survey, South

Africa, 2011." In.

- Hladik, W., I. Shabbir, A. Jelaludin, A. Woldu, M. Tsehaynesh, and W. Tadesse. 2006. 'HIV/AIDS in Ethiopia: where is the epidemic heading?', _Sex Transm Infect_ , 82 Suppl 1: i32-5.

- Hogan, D. R., and J. A. Salomon. 2012. 'Spline-based modelling of trends in the force of HIV infection, with application to the UNAIDS Estimation and Projection Package', _Sex Transm Infect_ , 88 Suppl 2: i52-7.

- Hygiene, London School of Tropical Medicine and. 'The ALPHA Network'.

- <u>http://www.lshtm.ac.uk/eph/dph/research/alpha/index.html.</u>

- Institut National de la Statistique du Rwanda (INSR), and ORC Macro. 2006. "Rwanda Demographic and Health Survey 2005." In.

- Institute, Federal Ministry of Health/Ethiopian Health and Nutrition Research. 2011. "Report on the 2009 Round Antenatal Care Sentinel HIV Surveillance in Ethiopia." In.

- Instituto Nacional de Saúde (INS), Instituto Nacional de Estatística (INE), e ICF Macro. 2010. "Inquérito Nacional de Prevalência, Riscos Comportamentais e Informação sobre o HIV e SIDA em Moçambique 2009." In.

Jewkes, R., M. Nduna, J. Levin, N. Jama, K. Dunkle, A. Puren, and N. Duvvury. 2008. 'Impact of stepping stones on incidence of HIV and HSV-2 and sexual behaviour in rural South Africa: cluster randomised controlled trial', _BMJ_ , 337: a506.

- Johnson, L. F., T. B. Hallett, T. M. Rehle, and R. E. Dorrington. 2012. 'The effect of changes in condom usage and antiretroviral treatment coverage on human immunodeficiency virus incidence in South Africa: a model-based analysis', _J R Soc Interface_ , 9: 1544-54.

- Justman, Jessica, T Ellman, D Donnell, Y Duong, J Reed, G  Bicego, P Ehrenkranz, L Wang, N Bock, and R Nkambule. 2013. "Population HIV Viral Load Estimate in Swaziland: Assessing ART Program Effectiveness and Transmission Potential." In _20th Conference on Retroviruses and Opportunistic Infections_ . Atlanta, Georgia, United States.

Kapiga, S. H., F. M. Ewings, T. Ao, J. Chilongani, A. Mongi, K. Baisley, S. Francis, A. Andreasen, R. Hashim, D. Watson-Jones, J. Changalucha, and R. Hayes. 2013. 'The epidemiology of HIV and HSV-2 infections among women participating in microbicide and vaccine feasibility studies in Northern Tanzania', _PLoS One_ , 8: e68825.

Karita, E., M. Price, E. Hunter, E. Chomba, S. Allen, L. Fei, A. Kamali, E. J. Sanders, O. Anzala, M. Katende, N. Ketter, Iavi Collaborative Seroprevalence, and Team Incidence Study. 2007. 'Investigating the utility of the HIV-1 BED capture enzyme 74
Policy Research Working Paper 6469

# **Abstract**

Social protection is absent from the Millennium Development Goals (MDGs), and only recently has gained some prominence in the post-2015 discourse. In the past quarter century, however, rising inequality has often accompanied economic growth. At the same time, the growing importance of risk and vulnerability on the wellbeing of the poor has been recognized. Further, there is now a consensus on adopting more ambitious goals on poverty reduction. Defining social protection as a collection of programs that address risk, vulnerability, inequality and poverty through a system of transfers in cash or in kind, this paper argues that social protection needs to be on the post-2015 agenda as a key element of the discourse. It provides an empirical overview of social protection around the world based on the World Bank’s Atlas of Social Protection: Indicators of Resilience and Equity (ASPIRE) data set. Focusing on the goal of ending poverty, the paper estimates that social protection programs are currently preventing 150 million people from falling into poverty. Based on the data set, the paper develops, tentatively and for discussion, a set of candidate goals, indicators and targets for the acceleration of poverty reduction through social protection. The authors ask what it would take for social protection programs to contribute to halving the poverty gap in a country. They show that if all countries could achieve the actual poverty reduction efficiency already observed in the top quartile of countries, then 70 percent of the countries in the sample could achieve this goal. However, for 30 percent of the countries, even reaching the top quartile on efficiency will not be enough—for these countries, the issue is one of budgetary adequacy.

This paper is a product of the Social Protection and Labor Department of the Human Development Network. 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://econ.worldbank.org. The authors may be contacted at afiszbein@worldbank.org, sk145@cornell.edu and ryemtsov@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
onwards, and covers 154 countries for which we have trade data. Here coverage is almost complete for all years. Using two independent sources which employ different methodologies contributes to testing the robustness of our results. A full list of countries can be found in the appendix. We use the sum of the index for a country-pair as a regressor; that is, _Iijt_ = _Iit_ + _Ijt_ . This reflects the aforementioned symmetry built into our data.<sup>23</sup> Our measures of infrastructure quality are the number of telephone lines (landlines plus cellular phone lines) per 1,000 people, and the total country road length per 1,000 people; they are taken from the World Development Indicators and are available for the entire sample.

We obtained bilateral tariff data from the TRAINS dataset (via the World Bank) for 1988-99. Use of this data immediately eliminates observations from 1984-87. Although this is the most elaborate bilateral tariff dataset we are aware of, the coverage of the bilateral tariffs of all trade pairs in this sample is patchy (in the later years the coverage is significantly better than in the early years) and considerably reduces the sample size in regressions in which it is used. As a regressor, we use (trade-weighted average across goods) bilateral tariffs, averaged for each country-pair. As with institutional quality, the averaging reflects the symmetry assumption. We chose to average rather than to sum in order to make results easy to interpret. For many countrypairs the tariff data was available for only one country. In these cases, we treat the tariff of that country as the “average” of both. This procedure is used in order not to lose too many data points in the estimation of specifications with tariffs. Even so, the tariff data cover only 43% of the entire sample for which trade and institutional data are available. This restriction hardly changes the overall representation of country-pairs in the panel. However, using tariff data the sample is

> 23 We chose not to use the World Bank’s “Governance Matters” (see Kaufmann, Kraay and Mastruzzi, 2005) institutional quality indicators because its country- and especially year-coverage is less complete than our institutional indicators. Nevertheless, these indicators are highly correlated with our institutional indicators.

17
language skills of these children (Arenas Arroyo and Schmidpeter, 2022). Moreover, Santillano _et al._ (2020) also find that in the United States, enrollment of Hispanic immigrant children in the Head Start program—which provides comprehensive early childhood education, health, and nutrition—decreases by 10% after a law enforcement raid. Primarily, this decline occurs because parents are deterred from appearing in public spaces.

Concerning the education outcomes of immigrant children, Amuedo-Dorantes and Lopez (2015) and Amuedo-Dorantes and Lopez (2017) find that in U.S. areas with intensified immigration law enforcement, the probability of school-year repetition and dropping out for Hispanic children between ages 14 and 18 years increases by 14% and 18%, respectively. Likewise, Dee and Murphy (2020) find that new ICE partnerships lead to a 10% decrease in the Hispanic immigrant student population within a span of two years. Furthermore, the learning environment plays an important role in immigrant children’s motivation, focus, and parental involvement. Amuedo-Dorantes _et al._ (2023) use data from the “Between the Lines” project to show that immigrant students who are enrolled in U.S. school districts implementing safe-zone policies<sup>2</sup> demonstrate improvements in several outcomes. For instance, they are 17% less likely to report difficulties in concentrating during school hours, 65% more inclined to express diligence in their studies, and 31% more optimistic about their prospects of achieving higher education, relative to other students. Additionally, these policies enhance caregiver participation in parent-teacher meetings by 34%.

Similar results are observed in the health care domain. Particularly, Watson (2014) finds that an increase in federal immigration enforcement acts leads to a decrease in Medicaid enrollment and usage among children of non-citizens, even if the children themselves are U.S. citizens. Additionally, Amuedo-Dorantes _et al._ (2022) find that more intense local U.S. immigration enforcement measures, particularly during the third trimester of pregnancy, raise the probability of infants being born with low birth weight (less than 2,500 grams). They note increased maternal stress and a decrease in prenatal-care medical visits as underlying factors.

In terms of economic and family impacts, Amuedo-Dorantes _et al._ (2018) show that deportation enforcement raises the likelihood of children living in impoverished households by 4%, primarily due to reduced working hours among parents. Furthermore, Amuedo-Dorantes and Arenas-

> 2A safe-zone policy within a school district implies that immigration authorities have limited entry or access.

10
**–** **<u>Table 9: Financing Parameters in Sierra Leone, 2014 17 Averages</u>**

||Share of total<br>government spending as<br>% of GDP|Share of education in<br>total government<br>spending|
|---|---|---|
|Sierra Leone|11.8|13.8|
|**Median for LICs**|**15.6**|**16.2**|
|**75**<sup>**th**</sup>**percentile for LICs**|**21.9**|**18.7**|

_Source:_ World Bank calculations based on UIS and IMF data. _Note:_ LIC = low-income country.

How rapidly could Sierra Leone increase its public spending on education? The underlying drivers of public education spending growth can provide useful benchmarks. It is not realistic to expect Sierra Leone to reach the levels of the 75<sup>th</sup> percentile countries in five years. Table 8 shows that over a given five-year period, fast-spending-growth low-income countries expanded the overall size of their government sector as a share of GDP by 2.4 percentage points and increased education spending’s share of the government budget by 2.4 percentage points. These figures show that these rates of growth are feasible within five years and suggest that Sierra Leone should be able to increase its public education spending from 1.6 to 2.3 percent of GDP over a five-year period. A less ambitious expansion path would be to try to emulate median countries rather than 75<sup>th</sup> percentile countries. In this case, Sierra Leone would aim for the average growth of spending in low-income countries by increasing its public education spending as a share of GDP from 1.6 to 1.7 percent over five years (Figure 14a). These two potential pathways provide a plausible range of targets within which Sierra Leone could increase its public education spending over the next five years.

Using school-age population projections, these possible spending paths translate into a range of per child funding of between $166 and $218 in 2020/21 compared to $126 per child in 2015/16 (Figure 14b). Are these spending increases worth pursuing for Sierra Leone? Based on the past record of low spending in inefficient countries (see Table 8, Share of total government budget as % of GDP), spending increases in this range have on average resulted in an increase of approximately one-third to two-thirds of one year of learning-adjusted years of schooling (Figure 14c). This is not to say that just by increasing spending these improvements in education outcomes are automatic, only that this is the average conversion of spending into resources for countries like Sierra Leone.

41
MNREGA induces these changes by tightening local labor markets which raises the opportunity cost of schooling. As a result, boys leave school to provide labor in the market and girls substitute into domestic work.

Overall the existing literature on MNREGA suggests that it had positive impacts on wages, incomes, and potentially health outcomes. It is clear that MNREGA had meaningful impacts on local labor markets. In particular it appears to have tightened labor markets, especially for unskilled labor, by providing an outside option for unskilled labor in the form of public works at a wage that may have been above the prevailing agricultural wage and therefore made unskilled labor more expensive.

# **3 Research design and implementation**

I follow much of the existing literature analyzing MNREGA and utilize a difference-in-differences framework that takes advantage of the phased roll-out of MNREGA across the country to examine its overall impact on the use of fires in agriculture. As a robustness check, I also utilize the treatment pattern from the MNS experiment to determine if improving the implementation of MNREGA leads to an increase in agricultural fires. The design and results of this robustness check are described in Appendix 6.

## **3.1 Data**

**Agricultural fires:** The source of the raw data on fire presence comes from NASA’s Fire Information for Resource Management System (FIRMS).<sup>16</sup> The FIRMS data provides the latitude and longitude and detection time of fires around the world using imagery from the MODIS and VIIRS imaging platforms. For all the primary analysis I use only data from MODIS because VIIRS does not provide sufficient temporal coverage.<sup>17</sup> MODIS Aqua imagery is available from mid-2002 to the present. Imagery from the satellites is collected every 6-12 hours around the world and processed using NASA’s image processing algorithm to identify fires based on the emissions of mid-range infrared radiation. The algorithm is designed to filter out spurious signals

(e.g. solar glare and gas flaring). NASA suggests that the imagery can detect fires as small as

> 16I primarily use data from MODIS, available here: https://earthdata.nasa.gov/firms

> 17See Appendix 1.5 for additional details on the difference between MODIS and VIIRS imagery.

10
**Table 3** . Summary of the benefits of different adaptation programs discussed in terms of reduction of asset damages, service disruptions and temporary poverty incidence. *The service disruption benefits are derived for the local area that the embankments protect and not for the coastal region as a whole.

|||CEIP-<br>|I<br> <br>|FS-N<br>|EW<br> <br>|ALL-PO<br>|LDERS<br>|
|---|---|---|---|---|---|---|---|
|Metric|Day|Present|CC<br>|Present|CC<br>|Present|CC|
|Asset damages (mUSD)||6.9|15.7|47.1|82.6|149.4|280.5|
|Service disruption (%)<sup>*</sup>||33.8|46.1|40.6|68.5|14.2|35.9|
|Temporary MDP (x1,000 p|eople)|||||||
|25 year - extreme MDP|10|31|59|165|176|1143|1607|
|25 year - extreme MDP|30|13|19|67|85|597|1036|
|25 year - extreme MDP|120|0|0|8|13|53|137|
|100 year - extreme MDP|10|0|0|0|0|0|0|
|100 year - extreme MDP|30|0|0|0|0|0|0|
|100 year -extremeMDP|120|0|0|0|0|0|0|

32
payouts are determined by exogenous information which is unaffected by either unobserved household characteristics (adverse selection) or ex-post household decisions (moral hazard). Desirable features of an index include the following: (i) the index is transparent and verifiable to policy-holders, (ii) the calculation of the index is free of tampering or manipulation, (iii) the probability distribution of the index can be accurately estimated, so that the product can be appropriately priced, and the expected return assessed by households, (iv) the index can be measured inexpensively and in a timely fashion, and (v) the realization of the index, or a transformation of the index, is highly correlated with household income and consumption risk.

The most widespread index-type insurance available in India is the government-operated National Agriculture Insurance Scheme (NAIS), which provides a payout based on measured arealevel yields on individual crops. In participating states, farmers are required to purchase NAIS insurance if they take a crop loan from a formal financial institution; other farmers can choose to purchase the insurance voluntarily (Kalavakonda and Mahul, 2005; Mahul and Rao, 2005). For more information, we refer readers to Appendix B, in which we describe the features of NAIS in more detail, and summarize the costs and benefits of NAIS relative to rainfall insurance. (This text is omitted from the main text due to space constraints).

A necessary feature of any insurance contract is that payoffs are correlated with household income and consumption. Available evidence suggests deficient rainfall is a key risk faced by rural Indian households. Table 1 presents self-reported rankings from our survey data of the importance of different risks faced by households. An overwhelming proportion (88%) cite drought as the most important risk they face; crop failure for reasons other than drought, and crop disease, are cited second and third most frequently. Consistent with these self-reports, World Bank (2005b) estimates that a severe drought in Ananthapur and Mahbubnagar, the districts studied in our empirical work, would reduce average rice yields by 45% and 26% respectively, a potentially devastating loss of income for a household near subsistence level.

4
# **Blibliography**

Alvarez de la Campa, Alejandro. ―How to Expand Credit to SMEs – Creative Solutions to the Puzzle of Collateral Lending‖. IFC Smart Lessons, Washington D.C. 2007.

Alvarez de la Campa, Alejandro. ―Private Sector Approach to Commercial ADR: Commercial ADR Mechanisms in Colombia‖. The World Bank Group, March 2009.

Chaves Rodrigo, de la Pena Nuria and Fleisig Heywood. ―Secured Transactions Reform: Early Results from Romania.‖ CEAL Issues Brief, Center for Economic Analysis of Law, September 2004.

Dahan Frederique and Simpson John ―Secured Transactions Reform and Access to Credit‖. Elgar Financial Law Series, 2009.

Djankov Simeon, McLiesh Caralee and Schleifer Andrei. ―Private Credit in 129 Countries‖, 2006. Doing Business Database. World Bank, 2005 and 2010.

European Bank for Reconstruction and Development (EBRD), 2004. ―Publicity of Security Rights: Guiding Principles for the Development of a Charges Registry‖. Annex: Technical Requirements for a Charges Registry, page 18.

Fleisig, Safavian, De La Pena. ―Reforming Collateral Laws to Expand Access to Finance‖, 2006. Hawkamah, The Institute for Corporate Governance. Reports for Lebanon, Saudi Arabia, Oman, Yemen, Jordan, Egypt, Palestine, Qatar and UAE.

IFC, January 2010. ―Secured Transactions Systems and Collateral Registries‖. C. 1. 1.1 Capabilities of Government to Operate Registry, and Private Sector Alternatives, page 63.

IMF Working Paper. ―Financial Sector Reforms and Prospects for Financial Integration in Maghreb Countries‖. WP/07/125, May 2007.

Internet World Stats. http://www.internetworldstats.com/links10.htm ―Legal Benchmarks for Monitoring Implementation of Euro-Mediterranean Association Agreements‖. Draft August 5, 2004, unpublished, Annex 4c Secured Lending, Tunisia.

Safavian, Mehnaz, Heywood Fleisig and Jevgenijs Steinbuks. ―Unlocking Dead Capital: How Reforming Collateral Laws Improves Access to Finance.‖ Private Sector Development Viewpoint, No. 307, World Bank, March 2006.

Sundahl, Mark. ―Iraq, Secured Transactions & The Promise of Islamic Law‖. Cleveland-Marshall College of Law, Research Paper 07-138, September 2007.

38
working capital, (ii) investment projects; (iii) buyer loans; (iv) guarantees; and (v) credit letters (a guarantee payment instrument).

PAT subsidizes 50 percent of the cost of specialized consulting and technical services to help SMEs improve productivity and competitiveness in foreign markets. Some of the specific areas supported by the programs were international certifications, promotion materials, export business plans, and promotional campaigns abroad. From 2001 to 2005, the PAT channeled over US$9 million to more than 7,000 firms, supporting exports of about US$500 million. However, the budget of the program decreased from US$1 million to less than US$100,000 between 2001 and 2005, and coverage dropped from 3,000 to 835 firms over the same period.

# _CONACyT_

CONACyT is a decentralized agency of the federal government responsible for science and technology policies. The agency is in charge of promoting the accumulation of scientific development and technological modernization through human resources, the support of specific research projects and the diffusion of information about science and technology. Between 2001 and 2006, CONACyT implemented several programs to boost technological capabilities of Mexican firms: 1) the Technological Modernization Program ( _Programa de Modernización Tecnológica_ —PMT); 2) the Science and Technology Sectoral Fund for Economic Development; 3) the High Value-Added in Businesses with Knowledge and Entrepreneurs program ( _Alto Valor Agregado en Negocios con Conocimiento y Empresarios_ —AVANCE); 4) Mixed Funds Program; 5) the Knowledge and Innovation Program ( _Programa de Conocimiento e Innovación_ —PCI); 6) the Support Research and Development in Projects Program ( _Programa de Apoyo a Proyectos de Investigación y Desarrollo Conjuntos_ —PAIDEC); and 7) the fiscal incentives program. These programs are detailed below.

The PMT was established in 2001 to provide fiscal credits up to 30 percent per year for firms that made investment in research and development. From 2001 to 2006, PMT’s coverage increased from 90 to 738 firms. In 2006, the program’s budget was US$873 million, of which 40 percent was allocated to SMEs.

**<u>Table 8 Fiscal Incentives: Main Results 2001-2006</u>**

|**Year**|**Firms**|**Projects**<br>**Large fir**|**Incentives**<br>**(million**<br>**~~USD)~~**<br>**ms**|**Firms**|**Projects**<br>**SME**|**Incentives**<br>**(million**<br>**~~USD)~~**|**Firms**|**Projects**<br>**Total**|**Incentives**<br>**(million**<br>**~~USD)~~**|
|---|---|---|---|---|---|---|---|---|---|
|2001|60|315|32|90|233|13|150|548|44|
|2002|76|429|36|125|358|16|201|787|51|
|2003|102|508|30|143|150|16|245|658|46|
|2004|132|N/A|N/A|225|N/A|N/A|357|1,308|89|
|2005|202|N/A|N/A|411|N/A|N/A|613|2,083|275|
|2006|316|N/A|N/A|738|N/A|N/A|1,054|3,317|367|
|Total|889|N/A|N/A|1,731|N/A|N/A|2,620|8,701|873|

**Source:** Conacyt (2003, 2005, 2006 and 2007)

8