rafmacalaba/datause-encoder-data huggingface dataset:
- 11 -

The dataset used in this study comprises 937 annuities issued in March of 1999, 1,517 annuities issued in March of 2002, 1,193 annuities issued in March of 2003, 1,490 annuities issued in March of 2004, and 1,391 annuities issued in March of 2005. These 5,137 annuities only include normal old age retirement and early retirement annuities, and exclude disability and survivorship annuities. Table 3 provides summary statistics for the whole dataset, while Table 4 provides information for separate subgroups.

As shown in Table 3, until 2004 the average age of retiring males and females was about 58 and 56, respectively, well below the normal retirement age of 65 and 60, and reflecting the large numbers of early retirees. The average age of retirement increased significantly in 2005, reflecting the introduction of stricter rules for early retirement. The share of deferred annuities (i.e., TWs) increased from 20 to 30 percent of the total, but the period of deferment remained short – roughly 80 percent of deferred annuities were only deferred for a year, and only 3 percent or less were deferred for 3 years or more. These patterns of selection reflect at least to some extent the influence of annuity brokers – since commissions are determined by the size of the annuity premium, brokers do not have incentives to recommend TWs paired with long periods of deferment.

While only 30 percent of annuities issued were deferred, close to 80 percent had payments guaranteed for a certain period of time independent of survivorship. The length of the guaranteed period is also relatively high – roughly 60 percent of all guaranteed annuities had a 10-year guarantee, and 90 percent were guaranteed for 10 or 15 years. The choice of guaranteed versus non-guaranteed annuities is not prescribed or influenced by broker activity, as the commission does not depend on whether the annuity is guaranteed or not. The preference for guaranteed payments probably reflects a decision to smooth retirement income within the family unit, as well as a bequest motive.

**<u>Table 3: Summary Statistics of the Dataset</u>**

||**1999**|**2002**|**2003**|**2004**|**2005**|
|---|---|---|---|---|---|
|_All Cases_||||||
|Number|937|1,517|1,193|1,490|1,391|
|Average Age of Males|57.83|56.98|57.77|57.70|59.46|
|Average Age of Females|55.76|54.85|55.55|56.02|58.46|
|Average Purchase Price (UF)|1,971.66|1,859.65|2,116.94|2,098.79|2,454.9|
|Number of cases with|199|331|307|409|419|
|deferment|(21.2%)|(21.8%)|(25.7%)|(27.5%)|(30.1%)|
|Of which:||||||
|- 12 months|164|275|238|322|315|
|- 24 months|32|54|60|75|91|
|- 36 months|2|2|8|10|9|
|- 48 months|1|0|1|2|3|
|Number of cases with|708|1,191|948|1,153|1,093|
|a guaranteed term|(75.6%)|(78.5%)|(79.5%)|(77.4%)|(78.6%)|
|Of which:||||||
|- 5 years|11|19|17|18|23|
|- 10 years|422|701|511|636|559|
|- 15 years|244|387|335|380|353|
|- 20 years|18|64|63|93|124|
|-other|13|20|22|26|34|

Source: SVS and Staff Analysis
In Table 5, we explicitly test our “marginal” child hypothesis that UCTs and CCTs would have similar positive effects increasing enrollment for children who are traditionally more likely to go to school, but CCTs are more effective at getting parents to invest in children they normally do not prioritize. We test this hypothesis by examining the impact of the two types of transfers on school enrollment for marginal and non-marginal children, as defined by their baseline enrollment status, gender, age, and cognitive ability. We focus our analysis on the more objective and reliable school-based measure of enrollment and on the Equation 3 specification, a difference-in-difference regression using the baseline and second follow-up surveys.<sup>24</sup> This specification acknowledges the absence of round 2 impacts and focuses on the round 3 impacts. Columns 1 and 2 in Table 5 compare the impacts of the different types of transfers for children who were already enrolled at baseline (column 1) and those who were not enrolled at baseline (column 2). All else equal, children not initially enrolled can be considered more marginal. Both types of transfers lead to positive and significant increases in enrollment for both types of children. Yet while the UCT and CCT coefficients are similar and not significantly different from each other for children enrolled at baseline, the CCT coefficient is significantly larger than the UCT coefficient for children who were not initially enrolled. Thus, CCTs seem to outperform UCTs in bringing into school children who had not been enrolled.

In columns 3-4 of Table 5, we compare the impact of conditional and unconditional cash transfers for boys and girls aged 7 to 15. For boys, CCTs and UCTs have a similar impact in magnitude, positively increasing enrollment by around 11 percentage points. In contrast, for girls

> 24 Baird and Özler (2012) suggest that self-reported enrollment is often overstated and recommend collecting schoollevel administrative enrollment data. In our survey, when comparing parental self-reports and school administrative data, we find that 11.4 percent of all children reported by their parents to be enrolled are not enrolled according to the school data. Appendix Table 1 provides a qualitative summary of the main enrollment results using the parental reports and school-level administrative data. As discussed below, results are consistent with both data sources. Appendix Table 2 presents results using the parental self-reports. Appendix Table 3 includes the other empirical specifications for the school-based data for all the sub-categories analyzed in Table 5 with consistent results.

19
# 2. The Basic Model

A common characteristic of developing countries is that a signi fi cant portion of their population, especially in periurban and rural areas, is without access to basic services. Thus, their network utilities are characterized by low coverage ratios. We consider an infrastructure sector that has not as yet achieved full coverage. A single utility fi rm dominates the sector serving N out of M potential customers. The remaining M − N consumers are either being served by alternative service providers (fringe), have no access at all, or a certain portion ρ of them may actually steal the service from the dominant utility through illegal connections. The services offered by the dominant utility and the fringe are assumed to be interchangeable in terms of their utility to the consumers.<sup>2</sup> The service arrangements of the customers not connected to the utility’s formal network vary by sector and country. In Yemen’s electricity sector, for example, small generators supply rural towns and villages not served by the public utility. Operations range from individual households generating power for themselves and a few neighbors to units supplying up to 200 households (Ehrhardt and Burdon 1999). Electricity theft through illegal connections is a serious problem in many developing countries, especially in the inner city communities and urban areas. Electricity theft accounted for over one-quarter of total production in 1992 when privatization reforms were initiated in Argentina (Haselip 2004). In Jamaica, in excess of 30,000 illegal connections were removed each month during 2003, allowing for a monthly reduction of 4.5 MWh of electricity production (Jamaica Public Service Company 2004). A 1989 study of the water supply in the Nigerian town of Onitsa found that water vendors delivered more water than the public water utility and that revenues for vended water exceeded revenues for water supplied by the public utility by a factor of more than 10 (Whittington et al 1991). These results indicated signi fi cant opportunities for expansion by the public utility.

> 2 This assumption of service homogeneity is likely to be violated in many real-world circumstances. Clearly, the characteristics of the services offered by the dominant utility can differ from those offered by the fringe on several dimensions of quality. Still, in the context of many developing countries where large segments of the population remain without access to basic services, costs rather than product differentiation are likely to be the main driving force. This paper, therefore, focuses more on the nature of production technology and costs facing the fringe rather than the properties of the demand function.

6
# **Cognitive and Non‐Cognitive Skills for the Peruvian Labor Market: Addressing Measurement Error through Latent Skills Estimations***

Wendy Cunningham, World Bank Mónica Parra Torrado, National Planning Department, Colombia Miguel Sarzosa, Purdue University

## JEL: J24, I24

Key Words: cognitive, non‐cognitive skills, schooling, wages, employment, latent skills, structural model, Peru

* This paper was prepared as a background paper for the World Bank study “Minds and Behaviors – Developing Socio-emotional Skills for Latin America’s Labor Markets.” The authors are grateful to Nöel Muller, William Maloney, Emily Farchy, Pablo Acosta, Sergio Urzúa and Margaret Grosh for their comments and suggestions; Omar Arias for leading the data collection process, and the 2014 LACEA Conference participants.
_Figure 8 “Fan chart” for RDR a. alpha=0.02 and b. alpha=0.22_ <!-- Start of picture text --> RDR, alpha=0.022 RDR, alpha=0.22<br>4 4<br>2 2<br>0 0<br>-22005 2006 2007 2008 2009 2010 2011 95-97.5 -22005 2006 2007 2008 2009 2010 2011 95-97.5<br>5-95 5-95<br>-4 -4<br>2.5-5 2.5-5<br>-6 -6<br>-8 Baseline -8 Baseline<br>-10 -10<br>-12 -12<br>-14 -14<br><!-- End of picture text --> 33
United States Government. 1980. _The Health Consequences of Smoking for Women: A Report of the Surgeon General_ . Department of Health and Human Services. Rockville, Maryland.

- United States Government. 1989. _Reducing the Health Consequences of Smoking: 25 Years of Progress, a Report of the Surgeon General_ . Department of Health and Human Services Publication No. (CDC) 89-8411.

- United States Government. 1994. _CDC Surveillance Summaries, Surveillance for Selected Tobacco-Use Behaviors - United States, 1900-1994_ , Center for Disease Control and Prevention, MMWR 43 (No. SS-3).

- United States Government. 2000. _Digest of Education Statistics._ Department of Education, Washington D.C.: UGSPO.

- United States Government. 2004. _History of the 1964 Surgeon General’s Report on Smoking and Health_ . Center for Disease Control and Prevention (http://www.cdc.gov/tobacco/30yrsgen.htm, accessed on May 11, 2004)

- United States Government. _National Health Interview Survey, 1978, 1979, 1980, 1983, 1985, 1987, 1988, 1990, 1991, 1992, 1994, 1995, 1997, 1998, 1999, 2000_ , Department of Health and Human Services, National Center for Health Statistics. Hyattsville, MD.

Viscusi, W. K. 1990. “Do Smokers Underestimate Risks?” _The Journal of Political Economy_ 98(6): 1253-1269.

Viscusi, W. K. 1992. _Smoking, Making the Risky Decision_ . Oxford University Press.

Wald, Nicholas, Stephanie Kiryluk, Sarah Darby, Richard Doll, Malcolm Pike, and Richard Peto. 1988. _UK Smoking Statistics._ Oxford University Press.

21
each year. These measures provide insights into the distribution of manufacturing firms across space and time in the country. Information on the number of months in the year for which the firm operated is also used in the analysis.

# **3.3 FDI Data**

To further understand the effects of outages on entry of (foreign) firms, I use a unique dataset on greenfield foreign direct investment projects. These data are obtained from fDi Markets,<sup>16</sup> a subsidiary of the Financial Times (FT) Group. fDi Markets database tracks cross-border investment projects around the world since 2003. The database is primarily used by agencies such as the World Bank, the Economist Intelligence Unit and UNCTAD in monitoring cross-border investments. It provides granular data on the project’s primary sector, sub-sector, country (city) of origin, destination country (city), investment size, etc. For the purpose of this paper, FDI project data on 23 emerging markets in Africa, Latin American and Caribbean, and Asia<sup>17</sup> between 2007 and 2017 focusing solely on investment in sectors excluding energy and construction sectors.

# **3.4 Lightning Data**

Lightning intensity is used as an instrument for electricity outages. However granular data lightning occurrence in Africa and many developing countries is a challenge. Available data on lightning activities in developing countries are mainly satellite-based measures of lightning intensity which come from NASA’s LIS/OTD Gridded Lightning Climatology Dataset.<sup>18</sup> . This dataset is cross-sectional and reports the average number of lightning strikes between 1995 and 2010 and is available at a relatively low spatial resolution of

> 16https://www.fdimarkets.com/

> 17Cambodia, Ghana, Guatemala, Honduras, India, Jamaica, Kenya, Morocco, Mexico, Myanmar, Mauritius, Namibia, Nicaragua, Pakistan, Philippines, Senegal, South Africa, Uganda, Uruguay, Uzbekistan, Vietnam, Zambia, Zimbabwe

> 18https://ghrc.nsstc.nasa.gov/uso/ds ~~d~~ ocs/lis ~~c~~ limatology/LISOTD ~~c~~ limatology ~~d~~ ataset.html This is arguably the most widely used measure of lightning intensity in the literature

14
THE CENTRAL AFRICAN REPUBLIC’S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE needed for other sectors, requirements for small-scale irrigation projects are also important, amounting to around $1 million a year (table 15).

**Table 14. Illustrative investment targets for infrastructure**

||Economic target|Social target|
|---|---|---|
|Transport|To connect Bangui, cities with more than 250,000<br>inhabitants, and border crossings with one-lane paved<br>roads in fair condition [1]|Providing rural road access to the highest-value agricultural<br>land, and urban road access within 500 meters|
|Irrigation|Develop additional 1,824 hectares of economically viable<br>small-scale irrigation projects [2]|—|
|WSS|—|Achieving Millennium Development Goals of halving the<br>population without access to improved water and improved<br>sanitation by 2015|
|Power|Develop 143 MW of new generation capacity to meet<br>national access rate of 34 percent|Increasing national electrification to 34 percent (84 percent<br>urban and 1 percent rural)|
|ICT|Install fiber-optic links from Bangui (the CAR) to<br>N’Djamena (the CAR) to allow for connectivity to the<br>submarine cable landing in Cameroon.|Providing universal access to GSM signal and public<br>broadband facilities|

_Sources:_ Mayer and others 2009; Rosnes and Vennemo 2009; Carruthers, Krishnamani, and Murray 2009; You and others 2009. _Note:_

[1] Regional connectivity is defined as the road network that links national capitals to each other, to all other cities with a population greater than 250,000, to international land borders, and to deep-water ports.

[2] Assuming an internal rate of return of 12 percent.

WSS = water supply and sanitation; ICT = information and communication technology; GSM = global system for mobile communications. — = Not available.

**Table 15. Indicative infrastructure spending needs for 2006–15**

|$ million per year|||
|---|---|---|
|**Sector**|**Capital expenditure**|**Operations and maintenance**<br>**Total needs**|
|Transport|91|69<br>160|
|ICT|30|56<br>86|
|Power|50|5<br>55|
|WSS|37|10<br>47|
|Irrigation|1|—<br>1|
|Total|208|141<br>349|

_Sources:_ Mayer and others 2009; Rosnes and Vennemo 2009; Carruthers, Krishnamani, and Murray 2009; You and others 2009. Derived from models that are available at http://www.infrastructureafrica.org/aicd/tools/models.

_Note:_ ICT = information and communications technology; WSS = water supply and sanitation.

36
(US$122), and 39 percent are below the national poverty line.<sup>7</sup> The mean firm is making profits of US$125 per week on US$1041 of weekly sales.

Table 1 shows that the randomized treatment and control groups look similar on most baseline observables for the full sample, and for the separate sub-samples of interested and uninterested firms. The last column then tests whether interested firms differ from uninterested firms on these owner and firm characteristics. Owners are more likely to be interested in Agruppa if they are female (which qualitative research suggested was in part due to the advantage of not having to deal with transporting heavy sacks of vegetables), and if they are younger, more educated and have higher household and business incomes (possibly reflecting a greater willingness to try new technologies or higher opportunity cost for their time). Firm owners who have a greater distance to travel to Corabastos are more interested (they have more to gain from saving on travel time), but owners who rely on the core Agruppa products for more of their sales and who travel most frequently to Corabastos are less interested (perhaps because they value the selection at Corabastos more). Column 1 of Table 2 considers these variables jointly in a probit and confirms that women with young children are more likely to be interested, as are owners who sell more Agruppa products and who live further from Corabastos, but those who shop at Corabastos every day are less likely to be interested.<sup>8</sup> We also did a one-time survey of 650 customers in 20 of the blocks (10 treatment and 10 control) to understand the characteristics of customers, and the extent to which our neighborhood blocks corresponded to their shopping locations.<sup>9</sup> This was done by randomly sampling customers shopping at stores in our sample to interview. Seventy-four percent of the customers are women, with a median age of 48, and 98 percent lived in the neighborhood they were interviewed shopping in, with a median time living in the neighborhood of 15 years. Median monthly per-capita household income is 250,000 pesos (US$81), which is approximately two-thirds of that of the median store owner. They shop for fruit and vegetables frequently, with a mean of 4.7 days per

> 7 Those who do not report household income tend to come from larger households. Imputing poverty rates on the basis of gender, age, education, household demographic composition, and geographic block gives an estimated poverty rate of 41 percent for those not reporting baseline income.

> 8 Note that the last variable in Table 2, the number of products Agruppa would have available at launch, was unknown to firms at the time of assessing interest in the product, which explains the lack of correlation with interest in column 1.

> 9 This survey was done between November 2017 and January 2018. There is no significant difference in the share spent in the neighborhood or likelihood of shopping outside of the neighborhood by treatment status.

10
13 Figure 7 Crude Birth and Death Rates, 1985-90 <!-- Start of picture text --> by Country Department<br><!-- End of picture text --> <!-- Start of picture text --> 0-<br>40<br>liue "I<br>Ar4 r2 AFA ArS API Ar3 CMI EMS ^SI CM2 AS4 LA2 LAS ^S2 ASS LAI L^4 ASS CMA<br>-<br>? H<br>P-Z7 Birth rate R Death at.<br>Figure 8<br>Total Fertility Rate, 1 985-90<br>by Country Oeportment<br>6<br>4<br>C O U N T R Y O E P A R T U C N T<br>-a~~X<br>3<br>2<br>I-<br>0-<br>Ar4 Ar2 ArG Art ArS AVs EMS EuM ASI E A 2 SS LA LAS ASS AS2 LA4 LAI ASS Etu<br>C O U NHT AY D E P A R T M E N T<br><!-- End of picture text --> <!-- Start of picture text --> Figure 9<br><!-- End of picture text --> <!-- Start of picture text -->
*  ~Life  Expectancy,  1 985-90<br>so  by C ... nt,y  Deportment<br>70<br>z<br>40<br>30<br>2. 0<br>10<br>DAES  AP2  Af4AF  AF3  t  AFO ^SI  EMS AS4  ASS  EMS  EM2  £32  LAI  LAS  LA2  LAS  ASS  CEMS<br>CO0U  NT  RY  D E PARPTMEtN  T<br><!-- End of picture text -->
In recent years, there has been increased recognition of the paramount importance of tetanus and measles as causes of childhood death in the developing world. It has been estimated that these diseases may together be responsible for more than 2.5 million childhood deaths annually. Considerable debate and uncertainty remains, however, concerning the actual reductions in childhood mortality which would result from the prevention of these diseases through immunization. Equally important, many unresolved questions remain regarding the most cost-effective and feasible operational strategies for measles and tetanus vaccination programs. The cbjective of this paper is to review existing empirical evidence on tetanus and measles immunization pertaining to these issues.

# MEASLES IMMUNIZATION

Measles has been estimated to account annually for as many as two million deaths to children worldwide (WHO, 1985). The risk period for measles begins when protection conferred by maternal antibodies wanes, and continues throughout early childhood. The beginning of the risk period appears to vary considerably between settings and according to residence, with the onset of measles cases frequently reported as early as 4-6 months of life in many urban African settings, but generally later in other settings such as South Asia (AssaaO, 1983).

# Mortality Impact of Immunization

The main studies which have evaluated the impact of meacles immpnization upon reductions in childhood mortality are summarized in Table 1. In the following sections, the study design and analytical approaches taken by each of these studies, as well as their principal findings, are reviewed.

The Kasongo study in Zaire represents the earliest attempt to syste.natically evaluate the impact of measles vaccination upon child survival (The Kasongo Project Team, 1981). All children in one area born during or after September, 1974 were offered measles vaccination at 8 months of age. A total of 255 children in this area accepted measles vaccination during the period of the study, representing 83 percent of all eligible children. Three comparison groups of unvaccinated children were also identified: 1) children born during the same period from a neighboring area where vaccination had not been offered, 2) children from the same area who were born during an earlier period (1973- 1974), and 3) children from the neighboring area also born during this earlier period. Survival status of children was ascertained through a system of quarterly household morbidity and mortality surveillance, carried out from mid-1974 through the end of 1977.

3