rafmacalaba/data-use-mentions-extended huggingface dataset:
*Poverty**|**diction**<br> <br>**Difference**<br>**(%)**|
|---|---|---|---|---|---|---|---|---|---|---|
|IE-LFS<br>|Urban|66.9|0.083|84.2|55|54.1|1.6%|51.1|52.8|3.3%|
|2020/19<br>Quarter 3|Rural|58.2|0.083|72.4|51|52.0|2.0%|52.3|54.4|4.0%|

**Source** : World Bank estimations using 2019/20 IE-LFS and 2019/20 and AWMS R3 surveys.

# Validity of the results

The validity of the survey-to-survey imputation model relies on two main assumptions **.** First, sampling must be comparable across the surveys. Second, the predictors for poverty imputations should be key determinants of the intertemporal variations in household expenditure and be stable over time. This section discusses these assumptions in detail.

**Assumption 1** : The survey sampling process must be comparable across surveys. To estimate comparable poverty measures, survey-to-survey imputation techniques require that information in both surveys was collected following similar protocols. Doing this requires that both surveys follow the same sampling process. If that is not the case, poverty imputations can be biased and over/underestimate the true poverty rate, even if the model correctly predicts the relation between household characteristics and expenditure in training data. This is a particularly valid concern in the case of phone surveys since phone ownership positively correlates with higher expenditure.

The comparability of the AWMS sample with the IE-LFS 2019-20 sample relies on the reweighting process that corrects a
# **Figure 1: Number of deaths by year among siblings of women age 15-49, Demographic and Health Survey 2000, Cambodia**

<!-- Start of picture text --> 1400<br>1200<br>1000<br>800<br>600<br>400<br>200<br>0<br>Year of death<br>1950 1952 1954 1956 1958 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998<br><!-- End of picture text --> 21
WPS3794

# **Disability, Poverty and Schooling in Developing Countries: Results from 11 Household Surveys**

Deon Filmer Development Research Group The World Bank dfilmer@worldbank.org This paper analyzes the relationship between whether a young person has a disability, the poverty status of their household, and their school participation using 11 household surveys from nine developing countries. Between 1 and 2 percent of the population is identified as having a disability. Youth with disabilities sometimes live in poorer households, but the extent of this concentration is typically neither large nor statistically significant. However, youth with disabilities are almost always substantially less likely to start school, and in some countries have lower transition rates resulting in lower schooling attainment. The order of magnitude of the school participation disability deficit is often larger than those associated with other characteristics such as gender, rural residence, or economic status differentials.

## World Bank Policy Research Working Paper 3794, December 2005

_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 view of the World Bank, its Executive Directors, or the countries they represent. Policy Research Working Papers are available online at http://econ.worldbank.org._ I thank Tomoki Fuji, Johannes Hoogeveen, Elizabeth King, Daniel Mont, Susan Peters, and Dan Rees for helpful comments on an earlier draft. Partial funding for this work was provided by the Disability Team of the Human Development Network of the World Bank. Excellent research assistance work was provided by Dilip Parajuli.
).

The paper proceeds as follows: Section 2 describes the nature of the shocks experienced by Afghans during the period between study’s midline and endline surveys and the trends in critical outcomes for nontreated households during this period. Section 3 describes the TUP program and Section 4 explains the study design. We present the main results in Section 5, present a discussion on mechanisms in Section 6, provide a benchmarking of these results against non-UP socioeconomic conditions in Section 7, and discuss costs and benefits of the program in Section 8. Section 9 concludes.

Yemen during an onset of social unrest but changes in the implementation post-randomization affected the study’s ability to reliably measure with precision impacts across multiple dimensions. Therefore, the authors are unable to determine whether the lack of impacts on some dimensions are due to the crisis or to the compromise in the design for the implementer re-qualification process after the randomization (Brune et al., 2022).

> 6Own estimates using the yearly battle-related civilian and military deaths for the years in which the TUP was implemented in each country Pettersson et al. (2021), divided by the country’s population from the World Bank’s World Development Indicators. Afghanistan’s battle-related deaths estimate is 17 times as large as Pakistan’s (10 battle-related deaths per 100,000 people); 7 times as large as the Republic of Yemen’s (24 per 100,000 people); and 6 times as large as South Sudan’s (29 per 100,000 people), for the years when the TUP studies took place in each country. The periods include intervention and impact analyses as follows: 2016-2018 for Afghanistan, 2009-2013 for Pakistan, 2010-2014 for Yemen, and 2013-2015 for South Sudan. The average battle-related casualties per year were also much higher in Afghanistan (58 per 100,000 people), followed by South Sudan (9.8), Yemen (4.8), and Pakistan (2.4).

5
~~~ ~<br>|_%_of Coy. Pay<br>~~Country<br>% of Cov. PayI<br>|
|Argentina|2.410|
|Chile|2.291|
|Peru|2.294|
|Uruguay|2.070|
|<br>**Mexico**|**1.919**|
|_Simple Av._|_2.197_|

Another challenge to the Peru 2.294 Mexican reform lying in the months Uruguay 2.070 ahead is the problem of AFORE agents **Mexico 1.919** aiming at "switching" affiliates among _Simple Av. 2.197_ AFOREs. In Chile, Argentina, and other countries, prevailing fee Source: CONSAR (1997), p. 19-20. regulations induce "armies" of AFP Note: Mexican data affiliate-weighted as of I April 1997 agents, a torrent of account transfers, All computations assume commission isa 1-time frontloaded fee. and a considerable increase in operation costs.

**Moral hazard concerns.** All privately run pension systems with mandatory contributions suffer from some general moral hazard. However, the Mexican reform may induce two additional sources of moral hazard. First, the government guarantees a MPG irrespective of the aggressiveness of the investment strategy chosen by the workers. This could encourage near-retirement workers whose investments have significantly under-performed to "bet the bank" at the government's expense. This effect is compounded by the lack of a minimum return requirement. Second, the implications of the life time switch option. Nevertheless, these sources of moral hazard are mitigated by three factors: (i) the majority of transition workers (65 %) are under 32 years of age; (ii) workers will have their own individual retirement accounts as opposed to a hypothetical Government guarantee; and (iii) initially the investment regime will be quite restrictive.
R. F. KRUEGER, J. M. RICHARDS, AND P. L. HILL (2014): “What is Conscientiousness and How Can it be Assessed?” _Developmental Psychology_ , 50, 1315.

- ROBERTS, B., J. JACKSON, J. FAYARD, G. EDMONDS, AND J. MEINTS (2009): “Conscientiousness,” in _Handbook of individual differences in social behavior_ ed. by Leary, M., and Hoyle, R. New York: Guilford Press, 369–381.

- SAWILOWSKY, S. S. (2009): “New Effect Size Rules of Thumb,” _Journal of Modern Applied Statistical Methods_ , 8, 26.

- SOTO, C. J. (2019): “How Replicable are Links Between Personality Traits and Consequential Life Outcomes? The Life Outcomes of Personality Replication Project,” _Psychological Science_ , 30, 711–727.

- SOTO, C. J., C. NAPOLITANO, M. SEWELL, H. YOON, AND B. ROBERTS (2022): “An Integrative Framework for Conceptualizing and Assessing Social, Emotional, and Behavioral Skills: The BESSI,” _Journal of Personality and Social Psychology_ , DOI: 10.1037/pspp0000401.

20
(0.142)|(0.011)|(0.011)|(0.020)|
|Observations|18,114|17,689|16,327|16,316|16,171|
|R-squared|0.880|0.543|0.472|0.466|0.509|

Note: This table reports the effects of financial structures on the number, size and dynamics of exporters in 2-digit ISIC industries depending on the degree of informational and contractual complexity. The financial structure is captured by the share of foreign bank assets in total bank assets in the country. The dependent variables are the number of exporters; the average foreign sales of exporters; the entry rate of exporters; the exit rate of exporters; the turnover (entry+exit) rate of exporters. All regressions include FinDev*ExtFin, Bank Concentration*ExtFin, country-year fixed effects and industry-year fixed effects, where FinDev is measured as all credit over GDP to control for total financial development and Bank Concentration is used to control for the concentration of the banking sector. Regressions in panel A also include ExtFin*Credit bureau coverage. Credit bureau coverage is the percentage of adults covered by credit bureaus in the country. Regressions in panel B also include Foreign Bank*ExtFin and Rauch*Rule of Law. The Rauch indicator of contractual complexity is defined in Section 3.3. The rule of law index is from the Worldwide Governance Indicators. Regressions in panel C also include Foreign Bank*ExtFin and Rauch*Strength of legal rights. The strength of legal rights is from Doing Business. Credit bureau coverage, rule of law, and strength of legal rights are demeaned by the sample average. Robust standard errors, clustered at the country-year level, are in parentheses. ***, **, and * denote statistical significance at the 1%, 5%, and 10% level, respectively.
<!-- Start of picture text --> The African distribution of consumption expenditure over time<br>logarithmic scale, population-weighted<br>©<br>me 4<br>/ Nc Be<br>© Tf IN<br>5 ie s<br>2D We: ‘‘<br>By : ‘\<br>QDi : \<br>E\<br>:\<br>lo) ae . ———2s =<br>fe) oO oo (=) (=i) oOo x x x x a Me me, oe x x x<br>wo oO oO Oo (ouJ ene) oO N oO w+ Oo OO epee} io .O ©<br>a —- ON oO ww TM bo! = IN oO wrno<br>annual PPP-adjusted 2011 USD<br>—— 7908 mr ABER re B08 =<br><!-- End of picture text --> <!-- Start of picture text --> African Lorenz curve<br>~ 4Lorenz curve = & Lorenz curve (zoomed) a 3<br>8 c f 8 Whe<br>2.0 a fle & th /<br>ia} ; Ko) “4<br>£2 ra r‘@ s28 4Whee 8<br>G<br>~. of ff ~ 9G YZ il<br>Pay Fi LE a £e Ye 5<br>Bo 4 a "2 4<br>| 4a 8 | 7<br>oO Oo Oo lo}<br>0 4 4 6 8 1 0 .05 fl 15 iz<br>Cumulative population share, p Cumulative population share, p<br>—— 1993 ===" 1998 sees eeeess 2003 —— 2008, —— — Equality<br><!-- End of picture text -->
Table 3. Explaining relative concentration between high-skill and low-skill and change in relative concentration <!-- Start of picture text --> Rel conc Rel conc ∆RC<br><!-- End of picture text -->

||Rel conc|Rel conc|∆RC|
|---|---|---|---|
||(OLS)|(Heck)|(Heck)|
|Lagged diasp|-0.502|-0.514|-0.008|
||(5.87)***|(9.67)***|(16.05)***|
|Col. links|-4.635|-4.619|-0.040|
||(4.68)***|(10.69)***|(9.93)***|
|Language|0.338|0.321|-0.004|
||(0.84)|(1.09)|(1.58)|
|Log(dist)|0.266|0.269|0.006|
||(1.24)|(1.69)*|(3.78)***|
|Schengen|-0.193|-0.180|0.002|
||(0.50)|(0.36)|(0.49)|
|Constant|5.607|-3.240|-0.037|
||(0.29)|(1.19)|(1.60)|
|Mills||-0.405|-0.873|
|||(1.07)|(2.44)**|
|Observations|3920|5730|5730|

<!-- Start of picture
foreign ownership may come with foreign values and culture that tend to be more favorable for women’s employment. Women may be particularly sensitive to the law and order situation and the prevalence of crime as criminals tend to target women more than men (Glaeser and Sacerdote 1999; Islam 2013).

Based on the discussion in the previous paragraph, we control for the following variables: a dummy variable equal to 1 if the firm has one or more female owners and 0 otherwise; proportion of firms’ ownership that is with foreign individuals or companies ( _Foreign Ownership_ ); a dummy variable equal to 1 if the firm experienced losses due to crime, theft and disorder and 0 otherwise ( _Crime Losses_ ); and a measure of the quality of courts based on a question in the ES on how severe is the (lack of proper) functioning of courts as an obstacle for firms’ current operations (on 0-4 scale). Like for exports, we use cell averages at the country-ES round-industry level of the responses to the question on courts’ functioning ( _Courts Obstacle_ ).

The remaining firm-level controls are intended to capture recent investment by the firm in physical capital and various aspects of the business environment as experienced by the firm. The assumption here is that recent investment and business environment are likely to impact firm efficiency and therefore its ability to compete in international markets. If the share of female workers also happens to vary systematically with the quality of the business environment, our main results for the relationship between exports and female workers could suffer from omitted variable bias problem. For recent investment, we use as a control a dummy variable equal to 1 if the firm purchased fixed assets during the last year and 0 otherwise. For the business environment we control for hours of power outages experienced by the firm in a typical month in the last year ( _Power Outages_ ); a dummy variable equal to 1 if the firm was inspected by tax officials during the last year and 0 otherwise ( _Firm Inspected_ ); and severity level (
(The Isolated State) in Beziehung auf Landwirtshaft und Nationalökonomie”. Pergamon Press, New York. English translation by Wartenberg C M in 1966, P.G. Hall, Editor.

World Bank (2014) Doing Business Survey Ethiopia.

World Bank (2015a) Ethiopia Urbanization Review, Working Paper No. 100238. World Bank (2015b) Competitive Cities for Jobs and Growth: What, Who and How.

34
a test was implemented in a large population in Niger. The test displayed appropriate reliability and validity in both the baseline and follow-up sample. The baseline cognitive score is correlated with both nutritional status and stimulation practices, suggesting sensitivity to factors known to be associated with cognitive development.<sup>27</sup> We report results with the scores normalized based on an international norm.<sup>28</sup> Cognitive scores are measured as z scores for children aged 6-42 months at the time of the follow-up survey.

_Socio-emotional development (Final outcome domain #3)_ . We build a z score for an index of socioemotional development based on the strength-and-difficulties questionnaires for children aged 24-59 months at the time of the follow-up survey. The overall score aggregates sub-scales on emotional problems, conduct problems, hyperactivity, peer problems, and pro-sociality. The overall scale is scored so that a higher score indicates that a child has less socio-emotional difficulties.

Finally, we measure a range of _secondary outcomes_ at the household level to analyze additional mechanisms (Section 6). First, to complement the analysis of dietary diversity among children, we document results on food security at the household level based on the food consumption score. We also consider the brachial perimeter for breastfeeding women. Second, we document changes in household consumption (separately for total, food and non-food consumption), as well as the share of food in total consumption. Third, we document impacts on assets (separately for the number of household durable goods, household productive assets, as well as a livestock index expressed in tropical livestock units) and savings (whether households participated in a rotating savings groups, and the amount contributed over the last week). Lastly, we measure impacts on human capital variables for older children and household members, including school enrollment, attendance, illness and health service utilization for older children and adults, as well as use of contraception and recent pregnancies among women aged 15-49.

> score can be transformed into a normed score based on
the General Transit Feed Specification (GTFS) format (see Figure 2 for the minibus network).<sup>9</sup> These data were compiled by the Digital Matatus consortium comprising University of Nairobi, Columbia University, Massachusetts Institute of Technology, and Groupshot (Klopp et al. 2015; Williams et al. 2015). The GTFS data were processed using a Dijkstra algorithm, which provided times to reach any minibus station from any other in the urban area.<sup>10</sup> Travel times to reach the closest minibus station were computed based on a straight-line distance or ‘as the crow flies’ from the center of each grid cell.

> 8 The distributions of commuting time do not substantially differ between informal and formal residential areas. In Nairobi, most households spend less than 1 hour for commuting (one way). Half of the household heads in Nairobi spend 30 minutes or less getting to their workplaces. No substantial difference is observed in the mean commuting time among households with different consumption quartiles and within/outside informal residential areas.

> 9 GTFS data are a common format for public transportation schedules and associated geographic information. They are a collection of multiple comma-separated values (csv) files that describe transit routes, stops (including geographic coordinates), travel times between stops, and a number of other public transit properties.

> 10 Dijkstra’s algorithm is an algorithm for finding the shortest path between two nodes in a graph that may represent, for example, road networks.

7
immediate consumption boom following the distribution of reinsertion allowances.<sup>9</sup> As a corollary, the price effect and the externalities generated by investments of DDR money should be marginal except if investments were concentrated in specific domains. The in-kind allowances, which were distributed as part of the reintegration package, are likewise expected to have a positive but small impact on consumption in the long run.

In accordance with this line of reasoning, we propose to test the following hypotheses:

- _Hypothesis 1._ Reinsertion allowances received by demobilized combatants had a positive impact on the levels of consumption and investment of their household.

- _Hypothesis 2._ The short-run impacts on consumption of beneficiary households were short-lived. The impacts on investment lasted in the long run

- _Hypothesis 3._ Nonbeneficiaries were also indirectly affected by the program. This indirect impact depends on the main occupation of households.

- _Hypothesis 4._ Higher demand for normal goods induced a price increase in the short run.

By testing these hypotheses, we contribute not only to the scarce literature on the impact of demobilization programs, but also to the literature on the impact of cash and in-kind transfer programs on beneficiaries, nonbeneficiaries and prices.

# **3. Empirical Analysis**

# _3.1. The Data_

The empirical analysis draws on different types of data. The first dataset consists of a panel of households. The second dataset is a community questionnaire. The third dataset consists of administrative data from the National Commission for Demobilization, Reinsertion and Reintegration.

The Panel Dataset. The first dataset constitutes a two-round household survey undertaken in Burundi. The first round is a QUIBB/CWIQ survey that is representative at the provincial level<sup>10</sup> collected in February 2006. The survey was requested by the Ministry of Planning and designed by the World Bank. Data collection was coordinated by the University of Burundi. The CWIQ Survey Technology has been applied in different African countries for the purpose of generating standardized indicators of poverty and welfare
The WALN sample is the most educated (26% have any higher education) while women in Benin are the least educated (69% have no education at all). Overall, the educational attainment of women in the land samples reflects national averages, while women in the business training samples have above-average education for their respective countries. For example, 73% of women completed at least secondary school in the Ethiopia DOT sample, while only 11% reached secondary education in the country overall (DHS 2021).

Women in our sample live in relatively large households, spanning from an average of 4.3 members in Ghana to around 7 in Benin (in line with respective national averages). The share of women that report being a household head varies across datasets, ranging from 61% of women in the Ethiopia WALN sample to close to zero in Benin and Rwanda.<sup>13</sup> Women tend to be younger than their spouses, spanning ten years younger in Ethiopia DOT to five years younger in Rwanda, which is in line with regional marital patterns (Hertrich, 2017). Importantly for our analysis, this age gap means that most women will eventually become widows. Most women in our sample are married to their partners, with the lowest rates in Ethiopia DOT (57 percent) and the highest rates in Benin and Ethiopia WALN (where virtually all women are married to their partners).<sup>14</sup> The number of children at baseline is lowest in the Ghana sample at approximately 1.5, medium for Ethiopia DOT at approximately 2, and high in Benin and Rwanda at over 3 children per women.<sup>15</sup> For Togo, we do not have a variable on the total number of children the woman has given birth to, so we instead focus on the number of children under five who live in the household (0.6).

The three business training samples of entrepreneurs (Ethiopia DOT, Ethiopia WALN,
passive management.

While the effect of distance on performance has been extensively studied in the literature, the role that active management plays on the investment strategies of foreign asset managers has received little attention. A growing number of empirical studies use complete transaction records within a country, and compare foreign-managed versus domestic-managed funds. Some of these studies provide support in favor of the superior skills of domestic investors (Hau, 2001; Choe et al., 2005; Dvoˇr ́ak, 2005), others document that foreign investors outperform locals (Grinblatt and Keloharju, 2000; Seasholes, 2004; Barber et al., 2009), and some find no differences in performance (Seasholes and Zhu, 2010). Despite using comprehensive transaction level data, most of these studies do not distinguish within each group (foreign or domestic), whether one investor is making all the poorlyperforming trades or if the trades are performed by different investors.<sup>1</sup> In other words, these studies do not account for within group heterogeneity that might explain portfolio returns, and what they estimate is an average performance gap between locals and foreigners.

We investigate the issue of style and distance using a unique transaction data set from the Colombian Stock Exchange. The advantage and novel aspect of the data is that for all the transactions in the market between January 2, 2006, and January 29, 2016, we have an investor identifier on both sides of the transaction which allows us to track each fund or individual over time. Given the panel structure of the data, we are not only able to compare average performance between foreign and domestic investors, but we can also study the extent to which performance is related to investor/fund characteristics, such as style and fund flows. Despite the vast segment of the literature that focuses on investors who are separated by borders, to the best of our knowledge, we are the first to use information on active management together with complete transaction history to analyze the relative skill and performance of foreign