rafmacalaba/datause-encoder-data huggingface dataset:
overestimate their children’s attendance rates. Even though some students have dropped out of school, the attendance rates (even the control students) are higher than the observed attendance rates in Panel B of Table 5. As with the self-reported enrollment data, we find no treatment effects. Had we relied on this self-reported measure, we would have significantly underestimated the effects of the program.

The cause of these inflated self-reported measures of enrollment and attendance is unclear. The other self-reported information we collected seems to conform much more closely to estimates obtained through our other data sources. They cannot be due to the incentives provided by the subsidy since these estimates are similarly high for treatment and control students. These results do, however, highlight the caution required when interpreting findings based on self-reported data. They also belie the argument that the exaggeration inherent in selfreported attendance data differences out when comparing treatment and control groups, at least when the reported rates are close to one.

Finally, in Panel F, we present our final academic participation estimates – graduation and tertiary enrollment estimates for students who where in grade 11 in 2005. Given the results in Panel D and E, it is important to exercise caution in interpreting these results. However, unlike the data presented in those panels, the self-reported graduation and tertiary enrollment levels seem much more reasonable. Looking at the control averages for the graduation rates, for example, 88 to 90 percent of eleventh graders report graduating – a rate that is slightly higher than the 85 and 96 percent average reenrollment rates presented in Panel C for students in grades nine and ten. It is also consistent with our estimates for the average number of students reporting that they passed in 2005 (Table 7, Panel A). Finally, the estimates are also consistent with the students reported activities, school fees, and labor market activities presented below in Table 8.

Turning to the estimated treatment effects, all of the estimated treatment effects are positive. However, not all of them are significant, most likely because the sample is much smaller than that used in the other panels. All treatments have positive point estimates for graduation, but only the estimated treatment effect in the pooled regression is statistically significant (10 percent level). For tertiary enrollment, the basic treatment generates a statistically insignificant increase of 4 percentage points, while the savings and tertiary treatments cause increases of 8.8 percentage points and 49.7 percentage points respectively, both of which are statistically significant at the 1 percent level even with the smaller sample.

- 25 -
_International Journal of Hydrogen Energy_ , 46(14), 9553-9566. <u>https://doi.org/10.1016/j.ijhydene.2020.12.100</u>

- Li, S.-h., Guo, L.-j., Cao, C.-g., & Li, C.-f. (2021c). Integrated assessment of carbon footprint, energy budget and net ecosystem economic efficiency from rice fields under different tillage modes in central China. _Journal of Cleaner Production_ , 295, 126398. <u>https://doi.org/https://doi.org/10.1016/j.jclepro.2021.126398</u>

- Li, Y., & Kimura, S. (2021). Economic competitiveness and environmental implications of hydrogen energy and fuel cell electric vehicles in ASEAN countries: The current and future scenarios. _Energy Policy_ , 148, 111980. https://doi.org/10.1016/j.enpol.2020.111980

- Liang, Y., Yu, B., & Wang, L. (2019). Costs and benefits of renewable energy development in China's power industry. _Renewable Energy_ , 131, 700-712. <u>https://doi.org/10.1016/j.renene.2018.07.079</u>

- Lio, M., & Liu, M. C. (2006). ICT and agricultural productivity: Evidence from cross-country data. _Agricultural Economics_ , 34(3), 221-228. <u>https://doi.org/10.1111/j.15740864.2006.00120.x</u>

- Liu, Y., Liu, T., Ye, S., & Liu, Y. (2018). Cost-benefit analysis for energy efficiency retrofit of existing buildings: A case study in China. _Journal of Cleaner Production_ , 177, 493-506. <u>https://doi.org/https://doi.org/10.1016/j.jclepro.2017.12.225</u>

- Lohwanitchai, K., & Jareemit, D. (2021). Modeling energy efficiency performance and costbenefit analysis achieving net-zero energy building design: Case studies of three representative offices in Thailand. _Sustainability_ , 13(9). <u>https://doi.org/10.3390/su13095201</u>

- Luddeni, G., Krarti, M., Pernigotto, G., & Gasparella, A. (2018). An analysis methodology for large-scale deep energy retrofits of existing building stocks: Case study of the Italian office building. _Sustainable Cities and Society_ , 41, 296-311. <u>https://doi.org/https://doi.org/10.1016/j.scs.2018.05.038</u>

- Mai, T., Cole, W., & Reimers, A. (2019). Setting cost targets for zero-emission electricity generation technologies. _Applied Energy_ , 250, 582-592. <u>https://doi.org/10.1016/j.apenergy.2019.05.001</u>

49
# **Figure B33: Permanent component—Agriculture**

<!-- Start of picture text --> Index, January 1970 = 100<br>110<br>Cotton Maize Rice Soybean meal Soybean oil Wheat<br>90<br>70<br>50<br>30<br>1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020<br>Source : Authors’ calculations<br><!-- End of picture text --> <!-- Start of picture text --> Index, January 1970 = 100<br>120<br>Cocoa Coffee, Arabica Coffee, Robusta Natural rubber Tea<br>100<br>80<br>60<br>40<br>20<br>1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020<br>Source : Authors’ calculations<br><!-- End of picture text --> _— 74 —_
<!-- Start of picture text --> GDP and population, by region (2004 − 2009)<br>Share of GDP and population in Brazil, by region (2004 − 2009) GDP per capita in Brazil, by region (2004 − 2009)<br>North Northeast Southeast South Center−West<br>GDP Population North Norhteast Southeast South Center−West Brazil<br>60<br>20<br>40 15<br>10<br>20<br>Share on GDP and population<br>5<br>GDP per capita (R$ thousand − prices of 2009)<br>0<br>2004 2005 2006 2007 2008 2009 2004 2005 2006 2007 2008 2009 2004 2005 2006 2007 2008 2009 2004 2005 2006 2007 2008 2009 2004 2005 2006 2007 2008 2009 0<br>2004 2005 2006 2007 2008 2009 2004 2005 2006 2007 2008 2009 2004 2005 2006 2007 2008 2009 2004 2005 2006 2007 2008 2009 2004 2005 2006 2007 2008 2009 2004 2005 2006 2007 2008 2009<br><!-- End of picture text --> Figure 2: Distribution of GDP and population in Brazil, by region (2004-2009) Source: IBGE (2012).

# **4.2 The data set**

To investigate households’ investment behaviors in child human capital, we rely on the Brazilian Household Expenditure Survey (Pesquisa de Or ̧camento Familiar - POF) conducted between 2008 and 2009 by the Brazilian Institute of Geography and Statistics (IBGE, acronym in Portuguese). POF 2008-2009 is the fifth survey conducted by IBGE on household expenditures. Previous surveys included ENDEF 1974-1975, POF 1987-1988, POF 1995-1996 and POF 20022003. Primarily, these surveys were designed to update the consumption patterns used as a reference for the consumer price index produced by IBGE, but after 2000, POF has also been used as an important survey to evaluate the living conditions of Brazilian households. POF 2008-2009’s sample allows us to make inferences about the entire Brazilian territory.

The POF 2008-2009 survey was conducted according to seven different questionnaires. Of these, we used POF1 (Characteristics of the house and its respective dwellers); POF2 (household common assets); POF3 (Collective expenditure by household); POF4 (Individual expenditure) and POF5 (Individual work and income). The data was collected between 19 May 2008 and 18 of May 2009. The sample covers 190,159 individuals, 93,175 men and 96,984 women. Each surveyed individual has an identifier composed of 11 digits that allows us to identify their residence, household and geographical location, composed of 550 strata. Each of the households that were surveyed was visited by an interviewer on nine consecutive days. In addition to the detailed data about income and expenditure this survey also allows us to identify the households which participated in social programs, including the ‘Bolsa Fam ́ılia’ Program (BFP).

In line with BFP’s design, we use the household level as reference unit. Therefore, our first 22
integration, the success of migrants also depends on trust in state institutions to which they apply for social services or to seek protection. We document that regularization empower migrants to request state action against crime, an important step toward social integration in receiving countries.

# **II THE PROGRAM: THE PEP REGULARIZATION**

Colombia has led regional efforts to regularize the status of Venezuelan forced migrants. As is typical in crisis-driven migration, a large share of Venezuelans who migrated to Colombia did so without a formal migratory process. Between April and June 2018, Colombian authorities at 1,109 authorized points in 413 municipalities registered undocumented Venezuelan immigrants (see Figure A1 in the Appendix). This registry, the _Registro Administrativo de Migrantes Venezolanos_ or RAMV, conducted a massive public campaign to attract Venezuelan immigrants to register and self-report personal information such as name, date of birth, current address, municipality of origin in Venezuela, date of entry, education level, and job status, among others. It succeeded in registering 442,617 undocumented Venezuelans from 253,575 different households.

It is important to note that in advertising the RAMV, the government explicitly stated that registration would not result in deportations or other negative legal consequences. Yet, it did not promote the RAMV either as a path to work permits or other legal benefits to enhance the migrant experience. The program was advertised simply as a registry to count and identify migrants.<sup>8</sup> However, in July 2018, just days before leaving office, outgoing President Juan Manuel Santos decreed that all Venezuelans who registered in the RAMV would be eligible for regular migratory status that would let them stay in Colombia and join the workforce. In particular, previously undocumented migrants who registered in RAMV could apply for the _Permiso Especial de Permanencia_ , or PEP, a comprehensive two-year regular migra-

> 8We subsequently spoke with government officials and confirmed that these were, in fact, their intentions at the time.

8
of firms being bribed, even when there are a small number of clusters. In Mexico, 22 percent of firms in the Greater Mexico City area were solicited for bribes whereas in the Monterrey region 9% were solicited. In Argentina, 16 and 11 percent of firms in Buenos Aries and Mendoza respectively were bribed. While there is only one cluster in several small island economies, there is variation across these economies: 27 percent in the Bahamas, and 2.7 percent in St. Kitts and Nevis.

Corruption is not consistently higher in a particular sector across countries. In Peru, the bribery rate is virtually the same in both manufacturing and services sectors, about 17 percent. In Argentina, there is a larger differential across sectors: 15.3 percent of firms in manufacturing were bribed compared to 9.4 percent of firms in services.

# **3.2 The Bribery Indicator (Whole Sample)**

We construct another version of the bribery indicator that incorporates firms who did not have a business transaction ( ). Here we denote firms who did not conduct a business transaction as not being bribed.

In the full LAC sample, 74 percent of firms participated in at least one business transaction. The remaining 26 percent may be poor performing firms, and this may contribute to selection bias in unobservables affecting sales growth and the likelihood of being solicited for a bribe. Inclusion of firms who did not conduct a business transaction also increases the sample a fair amount since there will be more country-location-sector cells with at least 30 firms. In the full sample, 7.7 percent of firms were bribed when we include firms who did not participate in business transactions, this is about 3 percentage points lower than when not including these firms. Since the sample is larger, there are 174 clusters when the bribery indicator is computed for the whole sample, 13 more clusters than with the main Bribery Indicator.

13
Policy Research Working Paper 10327

# **Abstract**

Understanding the specific factors associated with cholera outbreaks is an integral part of designing better approaches to mitigate their impact. This paper uses georeferenced case data from the cholera epidemic that occurred in Harare, Zimbabwe, from September 2018 to January 2019. The paper applies spatio-temporal modeling to understand how the outbreak unfolded and the factors associated with higher risk of being a reported case. The study highlighted a number of findings. First, using call detail records to estimate weekly population movement throughout the city, the results suggest that human movement helps to explain the spatiotemporal patterns of the cases observed. In addition, the results highlight a number of sociodemographic risk factors and suggest that there is a relationship between cholera risk and water infrastructure, with populations living in close proximity to the sewer network with high access to piped water being at higher risk. A possible explanation for this surprising observation is that sewer bursts led to the contamination of the piped water network, turning access to piped water, usually assumed to be protective, into a risk factor. Although further studies are required to test this hypothesis, if it is true, it highlights the importance of maintenance for achieving the Sustainable Development Goals of improved water and sanitation infrastructure.

This paper is a product of the Water 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 gjoseph@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
- 28

# Tebl. I

# Nm-mw CUMs of Laber

**(poreenteg.e*)**

||1665|1070|~~~1075|3016||
|---|---|---|---|---|---|
|Latin amrle|(1)<br>(1)|(1)<br>(1)|(1)<br>(2)|(1)<br>(2)|(1)<br>(2)|
|Arj<br>lttna|0.33 (0.49)|0.33 (0.51)|0.35 (0.50)|0.4<br>(0.61)|0.46 (0.64)|
|Iresil|0.34 (0.60)|0.34 (O.U)|O.3(0.8)|0.80 (0.86)|0.U4 (0.42)|
|C.l_b1|0.31 (0.10)|0.48 (0.24)|0.52 (0.40)|0.61 (0.60)|0.62 (0.60)|
|Chil,|0.36 (0.30)|0.48 (0.49)|0.51 (0.41)|0.21 (0.15)|0.15 (0.24)|
|Mexlo<br>|<br>0.87 (0.78)<br>|<br>0.37 (0.67)<br>|<br>O.6 (0.71)<br>|<br> <br>0.41 (0.57)<br><br>|<br>0.45 (0.50)<br> <br>|
|Port|0.24 (0.37)|0.24 (0.36)|0.24(0.37)|<br>0.25 (0.13)|0."<br>(0.23)|
|Aft ie||||||
|Konya|n|0.13(0.U)|0.12(0.71)|<br>0.13 (0.69)|0.13 (0.44)|
|<br>mero|..|0.14 (0.64)|0.16(0.16)|<br>0.10(0.77)|0.10 (0.70)|
|slei|n.e.|0.14 (0.91)|0.14(0.66)|<br>0.13(0.64)|0.13(0.46)|
|Nigeri|0.00(0.31)|0.10 (0.20)|0.10 (0.14)|0.10 (0.10)|0.10(0.#5)|
|T-anzali|0.10 (O.63)|0.10 (O."6)|0.10(O.66)|<br>0.12 (0.50)|0.12 (0.44)|
|Zambia|0.50 (0.11)|0.06 (0.14)|0.06(0.34)|<br>0.06 (0.36)|0.50(0.37)|
|Zimb_be|0.15(0.73)|0.15(0.66)|0.15 (0.47)|0.16 (0.06)|0.15(0.31)|
|India|0.12 (0.55)|0.11 (1.06)|0.u4 (1.4)|0.13(1.13)|0.36 (1.0$|
|Pekieta|0.15 (0.60)|0.15(0.66)|0.15 (0.41)|0.15 (0.30)|0.15 (0.42)|
|Sri Lantk|0.25(0.71)|0.25 (0.62|0.n3 (O.5)|0.25(0.34)|0.33(0.28)|
|E..t**Asia**||||||
|HWo Kon|0.11 (0.06)|0.11 (0.06)|0.15 (0.10)|0.20 (0.10)|0.20 (0.10)|
|Korea|0.20 (0.24)|0.20 (0.25)|0.20 (0.20)|0.20 (0.21)|0.20 (0.21)|
|Slapore|0.11 (0.14)|0.14 (0.06)|0."1 (0.14)|0.20 (0.12)|0.35(0.17)|
|Europ.||||||
|a<br>c|O.<br>(0.53)|0.50(0.40)|0.15(0.54)|<br>0.55 (0.66)|O.56(0.90)|
|Portugl|0.16(0.21)|0.S1 (0.24)|0.14 (0.40)|0.23 (0.$3)|0.80 (0.")|
|AwlAril|||<br>0.76 (0.77)|<br>0.61 (0.73)|0."<br>(0.76)|
|Fr|||<br>0.70 (0.6)|<br>0.74(0.65)|0.63(0.73)|
|Germay|||0.60 (0.74)|0."<br>(0.76)|0.75 (0.77)|
|Siml|||0.50 (0.")|0.40 (0.67)|0.40(0.67)|
|b de|||<br>0.45 (0.66)|<br>0.61(0.70)|0.67 (0.66)|
|United<br>Kingo|||0.21(0.33)|<br>**0."**<br>(0.$5)|O.U(0.36)|
|USA|||O.31(0.43)|0.3 (0.4)|<br>0.37(0.44)|
|Canad|||O.1(0.81)|0.25(0.33)|0."1(0.35)|
|Japan|||<br>0.14 (0.16)|0.16 (0.16)|0.17 (0.17)|

a **N4C are** expresood **as a** proportion of labor earnings. Sotwoen breckot, tle *tae formd by the yeor eqivalont monetary value of _UC_ of lor enW the hourly per capita Ince.

Soure.s For industrial countries, Bureau of Labor Statiatle:s Hourly Com_eestio Cot for Production Workers (ratle of additioenl cempnotien to hoIrly earnings); NK figures are nt totlly comprable becaus vaction days and vacation are not coneidaerd In the cas_ of ldusrll countriee.

For UICe. * Ameedix_ 1.
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<!-- Start of picture text --> 100<br>m Primary<br>90 mSecondary<br>= ;<br>= 80 m Tertiary<br>E 70<br>:65°<br>e 50<br>3”a<br>5<br>a)<br>= 20<br>10<br>0 .<br>Burundi Kenya Rwanda Tanzania Uganda Sub-Saharan<br>Africa<br>average<br><!-- End of picture text --> <!-- Start of picture text --> 60<br>= Classified<br>— & Total network<br>— 50<br>aj<br>8 40<br>g<br>£30<br>z<br>35 20<br>210<br>na<br>° 5 o<br>c 2 g N g% oo<br>a3 «s ecc 3 =>8 s<br>2 Bo<br>as<br><!-- End of picture text -->
# **1. Introduction**

This paper presents a theoretical framework for analyzing some key issues related to urban public utility services in developing and emerging economies, with specific reference to Latin America, South Asia, and Africa. The allocation problems for utility services including household water and electricity access and service, encountered these regions are threefold: 1) Low service quality levels for households covered by the regular system. Water or electricity service is often provided only during part of the day or sometimes not at all (including frequent outages); water may have low quality or pressure, and power may have incorrect and variable voltage. 2) Low coverage levels of households, with many households not having access to regular service, and where those without access must rely on other more expensive and less reliable sources. 3) Inadequate long-run overall supply (of water and electricity).

Water and electricity supply are crucial services in many developing countries. Surveys have shown that water service improvement is the most important public-service issue for urban residents in many developing countries.<sup>1</sup> While piped water access is now high in Latin America, in many cities 20-40 % of the urban population still lacks such access, and service is inferior to many, only during part of the day or by having low water pressure. Estache et.al. (2000) find that providing piped water and electricity access, in addition to increasing the level of welfare directly, may significantly raise real household income in many Latin American countries e.g. by freeing time for market work or education among household participants.<sup>2</sup> This implies the potential for enormous overall welfare gains from improvements in these areas, in both the short and long run. The situation may be even worse in Africa and South Asia, where coverage rates for tap water and electricity are lower, and

> 1 An example is Tegucigalpa, Honduras, where almost 25 % of surveyed households (in 1995) rated water issues as the single most important issue, with sewerage service as a distant number 2 (at about 10 %). 2 Overall, their estimates indicate that the resulting increase in household income is approximately 10 % from water access alone, although the figure is uncertain due to possible selection problems. See also Estache et al (2006).

2
<!-- Start of picture text -->
1.15<br>1.10<br>1.05<br>1.00<br><!-- End of picture text -->

<!-- Start of picture text --> 0.95/0.85 |<br>urban rural urban rural urban rural urban rural urban rural urban rural urban rural urban<br>Tehran Caspian Northwest Northeast Central Southeast Persian Gulf Zagros<br>mTM2008 TM2009 #2010 m2011 m2012 m2013 m2014<br><!-- End of picture text -->
Policy Research Working Paper 7469

# **Abstract**

Despite recent calls in support of cash transfers, there is little rigorous evidence of the relative impacts of cash versus in-kind transfers, especially in humanitarian contexts, where a majority of such programs take place. This paper uses data from a randomized experiment in the Democratic Republic of Congo to assess the relative impacts and costs of equivalently valued cash and voucher transfers. The voucher program distorted households’ purchases along both the extensive and intensive margin as compared with unconstrained cash households. Yet there were no differences in food consumption or other measures of well-being, in part due to the fact that voucher households were able to resell part of what they purchased. As there were no significant benefits to vouchers, cash transfers were the more cost effective modality for both the implementing agency and program recipients in this context.

This paper is a product of the Operations and Strategy Team, Development Economics Vice Presidency. 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 author may be contacted at Jenny.Aker@tufts.edu.

_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