rafmacalaba/data-use-mentions-extended huggingface dataset:
on the socioeconomic conditions of the household, and employment questions are often asked with a lower age cut-off. The C8te d'Ivoire data set used in this study is a multipurpose household survey with national coverage, which recorded labor force participation for all household members aged 7 years and above.

The results of the case study confirm the validity of a multi-angled policy approach towards the elimination of child labor. In particular, the case is made for a gradual policy approach, whereby initially the combination of child labor and schooling is made more attractive, relative to only work. This presents a more realistic approach for poor households who are likely to select work options for their children, and avoids interventions which can make the child worse off.

# 2. Trends in Child Labor in C6te d'Ivoire in the 1980s

The investigation of the incidence and determinants of child labor in C6te d'Ivoire in this paper is based on the 1988 C6te d'Ivoire Living Standards Survey (CILSS). The CILSS was canvassed annually between 1985 and 1988 over a representative sample of 1600 households. The survey collected detailed information on employment, income, expenditure, assets, basic needs and other socioeconomic characteristics of households and their members. Over the four years, coverage and methodology of the survey were held constant so that 6
## **c. Operating Expenses**

<!-- Start of picture text --> 6.2 6.2<br>6.1<br>6<br>5.1<br>4.7<br>4 3.8<br>3.5 3.5<br>3.1<br>3.1<br>2.6 2.6 2.5<br>2.2 2.2<br>2 1.8<br>1.4<br>1.1<br>0.7 0.6<br>0<br>BhutanBulgariaSolomon IslandsSouth AfricaCroatiaEthiopiaGhanaUkraineKosovoIndonesiaUruguayAlbania KenyaRomania BrazilGeorgiaBurundiArgentina Peru<br>Percent of GDP<br><!-- End of picture text --> _Source_ : World Bank Infrastructure SOEs Database. _Note_ : Data are for 2009–18.

# **_4.2 Performance_**

SOE underperformance can turn into an important source of fiscal risk and macroeconomic instability, depending on the volatility and size of SOE losses. This section looks at three indicators of profitability to gain a deeper understanding of how infrastructure SOEs perform.

Figure 2 shows the return on average assets (ROAA) for all the SOEs in the sample, with and without adjusting for the operating subsidies they receive. This figure, and the following ones, reveals the high level of subsidies in infrastructure SOEs. The power sector is the least subsidized and the best-performing sector,<sup>6</sup> with and without subsidies, followed by airlines and airports (without subsidies). Railways is by far both the most heavily subsidized sector and the worstperforming one, with negative ROAA even after accounting for subsidies. This performance raises concerns about the sustainability and fiscal risk of railway SOEs. The figures also show that when the net income of the SOEs in our sample is adjusted for operating subsidies, ROAA becomes very negative.

> 6 In Sub-Saharan Africa, for instance
- Burivalova, Z., Bauert, M. R., Hassold, S., Fatroandrianjafinonjasolomiovazo, N. T. & Koh, L. P. (2015), ‘Relevance of global forest change data set to local conservation: case study of forest degradation in masoala national park, madagascar’, Biotropica 47(2), 267–274.

- Cacho, O. J., Milne, S., Gonzalez, R. & Tacconi, L. (2014), ‘Benefits and costs of deforestation by smallholders: Implications for forest conservation and climate policy’, Ecological Economics 107, 321–332.

- Cameron, T. A. & James, M. D. (1987), ‘Efficient estimation methods for” closed-ended” contingent valuation surveys’, The Review of Economics and Statistics pp. 269–276.

- Carson, R. & Groves, T. (2007), ‘Incentive and informational properties of preference questions’, Environmental and Resource Economics 37, 181–210.

- Carson, R., Groves, T. & List, J. (2014), ‘Consequentiality: A theoretical and experimental exploration of a single binary choice’, Journal of the Association of Environmental and Resource Economists 1, 171–207.

- Costedoat, S., Corbera, E., de Blas, D. E., Honey-Ross, J., Baylis, K. & Castillo-Santiago, M. (2015), ‘Consequentiality: A theoretical and experimental exploration of a single binary choice’, PLoS ONE 10.

- de Janvry, A., Gordillo, G. & Sadoulet, E. (1997), Mexico’s Second Agrarian Reform: household and community responses, 1990-1994, Center for US-Mexican Studies.

- De Janvry, A. & Sadoulet, E. (2006), ‘Making conditional cash transfer programs more efficient: designing for maximum effect of the conditionality’, The World Bank Economic Review 20(1
0419|-0556*|(0.0667)<br>|(0.0783)<br>|(0.0602)<br>|(0.0646)<br>|(0.0805)<br>|(0.0643)<br>|-0609**|-0440|
|<br>_(Chinn-Ito index)_|.<br>(0.296)|.<br>(0.299)|.<br>(0.307)|.<br>(0.296)|..|..|..|..|..|..|.<br>(0.302)|.<br>(0.294)|
|Remittances<br>_(% GDP received)_|0.0423<br>(00577)|-0.00331<br>(00805)|0.0294<br>(00572)|0.0540<br>(00581)|0.0146<br>(00593)|0.00263<br>(00841)|0.0190<br>(00565)|0.0234<br>(00571)|0.0934<br>(00766)|0.0281<br>(00587)|0.0759<br>(00741)|0.0259<br>(00626)|
|_,_<br>International Tourism|.<br>0.0419|.<br>-0.0119|.<br>0.0144|.<br>0.0415|.<br>0.0205|.<br>-0.00815|.<br>0.0336|.<br>0.0336|.<br>0.0188|.<br>0.0455|.
Figure 8. Policies to strengthen corporate balance sheets

# A. Potential output growth

# B. Long-term growth forecasts for fixed investment

<!-- Start of picture text --> Percent Percent<br>7 1998-2018 potential growth 12 EMDEs EMDEs excl. China World<br>6<br>5 10<br>4<br>3 8<br>2<br>1 6<br>0<br>4<br>2<br>World AEs EMDEs<br>C. Total factor productivity growth in D. Impact of supportive policies on potential<br>EMDEs output growth in EMDEs<br>Percent Percent Baseline Supportive policies<br>3.0 1998-2007 average 5.2<br>5.0<br>2.5<br>4.8<br>2.0 4.6<br>4.4<br>1.5<br>4.2<br>1.0 4.0<br>3.8<br>3.6<br>2013-17 2018-27 Impact<br>2010 2011 2012 2013 2014 2015 2016 2017 2018 2019<br>2003-07 2013-18 2019-27 2003-07 2013-18 2019-27 2003-07 2013-18 2019-27<br>2003-07 2013-17 2018-27<br><!-- End of picture text --> Source: Consensus Economics, Penn World Tables, UN Population Prospects, World Bank. A. Period average of annual GDP-weighted averages. Estimates based on production function approach. World sample includes 50 EMDEs and 30 advanced economies. AE = Advanced economies, B. 10-year-ahead forecasts surveyed in indicated year. Aggregate growth rates are calculated using constant 2010 U.S. dollar investment weights. Sample includes 23 advanced economies and 20 EMDEs. C. Shaded area indicates forecasts. GDP-weighted averages of production function-based potential TFP growth estimates. Sample includes 50 EMDEs.

D. Shaded area indicates forecasts. GDP-weighted averages of production function-based potential growth estimates. Sample includes EMDEs. Supportive policies assume
of the population of Myanmar (around 10 million people) had migrated, either internally or abroad (MAPSA 2024).

As economic and security prospects remain bleak, there may be sustained pressure on the population to migrate outside Myanmar. This may be particularly concerning in the case of highskilled workers that play a critical role in key professions and occupations in Myanmar, especially because of the low share of the population with higher education, relative to regional and neighboring peers (figure 1). High levels of emigration among the already limited numbers of high-skilled workers, such as medical professionals, educators, and engineers, can result in shortages in critical sectors of activity, which in turn can be detrimental to long-term development.

Figure 1. Educational attainment, Bachelor’s or equivalent / at least Master's or equivalent, population 25+, total (%) – Myanmar and selected regional and neighboring comparator countries <!-- Start of picture text --> 35<br>30<br>25<br>20<br>15<br>0.26<br>10<br>5 9.09<br>0<br>Bachelors Master's<br><!-- End of picture text --> Source: Authors’ calculations using World Development Indicators, for latest available year since 2010. *Data for population 25+ with bachelor’s degree or equivalent not available for Cambodia.

Against this backdrop, we attempt to answer the following research questions: (i) How much do high-skilled youth value the prospects of migrating abroad for undertaking work that is similar to their current jobs?

(ii) How would the emigration of high-skilled youth respond to prospects of political or economic stabilization? What form of stabilization – political, or economic – matters (more) for the emigration considerations of high-skilled youth?

(iii) Which individual characteristics determine migration responses to signals of political or economic stabilization?

5
Fama, Eugene F., and Kenneth R. French, 1992, “The Cross-Section of Expected Stock Returns,” _Journal of Finance,_ vol. 47(2), pp. 427-465.

- Furlong, F. T., and M. C. Keeley, 1989, Capital Regulation and Bank Risk-Taking: A Note, _Journal of Banking and Finance_ , 13, 883-891.

- Hart, Oliver and Luigi Zingales, 2009, A New Capital Regulation for Large Financial Institutions, University of Chicago mimeo.

Keeley, M. C., and F. T. Furlong, 1990, A Re-Examination of the Mean-Variance Analysis of Bank Capital Regulation, _Journal of Banking and Finance_ , 15, 69-84.

Koehn, M. and Anthony M. Santomero, 1980, Regulation of Bank Capital and Portfolio Risk, _Journal of Finance_ , 35, 1235-1244.

- Merrouche, Ouarda and Erland Nier, 2010, What Caused the Global Financial Crisis? Evidence on Drivers of Financial Imbalances 1999-2007, IMF working paper, August 2010.

- Nichols, Austin, and Mark Schaffer, 2007, Clustered Errors in Stata, Available via the internet at: http://repec.org/usug2007/crse.pdf.

Petersen, Mitchell, A., 2009, Estimating Standard Errors in Finance Panel Data Sets: Comparing Approaches, _Review of Financial Studies_ , 2009 22, 435-480.

Santos, Joao A. C., 2001, Bank Capital Regulation in Contemporary Banking Theory: A Review of the Literature, _Financial Markets, Institutions, and Instruments_ , 10, 41-84.

- Tong, Hui, and Shang-Jin Wei, forthcoming, The Composition Matters: Capital Inflows and Liquidity Crunch During a Global Economic Crisis, _Review of Financial Studies_ .

Viñals, Jose’, Jonathan Fiechter, Ceyla Pazarbasioglu, Laura Kodres, Aditya Narain, and Marina Moretti, 2010, Shaping the New Financial System, _IMF Staff Position Note_ , 10/15.

Whited, Toni M., and Guojun Wu, 2006, Financial Constraints Risk,
Policy Research Working Paper 10106

# **Abstract**

The information set from which individuals make their decision on vaccination includes signals from trusted agents, such as governments, community leaders, and the media. By implementing restrictions, or by relaxing them, governments can provide a signal about the underlying risk of the pandemic and indirectly affect vaccination take-up. Rather than focusing on measures specifically designed to increase vaccine acceptance, this paper studies how governments’ nonpharmaceutical policy responses to the pandemic can modify the degree of preventive health behavior, including vaccination. To do so, the paper uses repeated waves of a global survey on COVID-19 beliefs, behaviors, and norms covering 67 countries from August 2020 to February 2021. Controlling for the usual determinants, the analysis explores how individuals’ willingness to get vaccinated is affected by changes in government restriction measures (as measured by the Oxford Stringency Index). This relationship is mediated by individual characteristics, social norms (social pressure to conform with what most people do), and trust in government institutions. The results point to a complex picture as the implementation of restrictions is associated with increased acceptance in some contexts and decreased acceptance in others. The stringency of government restrictions has significant positive correlations with vaccine acceptance in contexts of weak social norms of vaccine acceptance and lower trust in government. In countries or communities where social norms are tighter and trust in government health authorities is high, vaccine acceptance is high but less sensitive to changes in policies. These results suggest that the indirect effect of government policy stringency is stronger among individuals who report lower trust and weaker social norms of vaccine acceptance.

This paper is a product of the Office of the Chief Economist, South Asia Region and the Office of the Chief Economist, Europe and Central Asia Region. 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.
the PAL transfer, especially when distributed in cash, led to an increase in the return to labor of young children and a higher probability of combining work and school attendance. The fact that children in inkind localities, despite the improved nutritional intakes, do not reduce their labor supply can potentially help explain why they did not experience any improvement in their test scores.

# **5.3 School quality**

As discussed above, children in our sample have access to three types of school service, that are very different in terms of quality and costs. Using the information from the Formato 911 for the school associated to the individual score, we test whether the two transfer modalities had an impact on the probability of attending a general school (vis a vis an indigenous or a community one), and characteristics that make up for most of the direct costs of school attendance: school distance from the community of residence, the sum of school contributions, material and uniform costs, and the student teacher ratio. Finally, we look at student-teacher ratio as a proxy for resource congestion.

20
socio-demographic variables for the household, heads of households, and children. Importantly, we also report descriptive statistics for child labor participation. The reference period for the child labor questions in the ERSS survey is the last 7 days before the survey date, and the age cohort refers to children 7 to 14. The labor module is answered by children aged 10 or older, while caretakers answer the questionnaire on behalf of children aged 7 to 9 years. With these caveats in mind, the child labor statistics emerging from the ERSS survey are similar (52%) to the number that emerges from our sample in the short rainy season.

# **3. Empirical Approach**

We measure the mean effects of the survey design assignment following two approaches. First, we report descriptive (mean) statistics by treatment assignment for child labor at the extensive and intensive margins for both 30-day and the 7-day recall periods. This variation in the length of the recall period would allow us to assess whether the child/proxy discrepancies in child labor statistics is due to recall decay bias. We present results for the pooled data and each season separately across boys and girls subsamples.

Next, we estimate survey design treatment effects for pooled specifications to maximize power and test whether information gaps between self- and proxy-respondents vary according to the gender of the child. Irregular and less predictable activities are difficult to monitor and therefore recalling the occurrence of events that are less salient or unusual is more costly for respondents (e.g., Bound et al. 2001). Thus, if work schedules for girls are less salient and more variable across the agricultural calendar, proxy respondents are more likely to focus on information that is less prominent, resulting in larger discrepancies of child labor reports. On the other hand, if farm work 13
): Morocco (1992,2004) and HCP Household survey (2007 and 2014).

Note: This table displays full and working sample means for several variables both pre and post Chikak divorce reform in Morocco. For the first three columns, we present full sample means pre and post reform. The remaining columns present working sample means for treatment and control groups. While the table shows means values for treatment and control groups post “treatment”, the empirical analysis employs a quasi-experimental framework that takes into consideration values for pre and post reform.

Tables 2, 3 and 4 display instructive descriptive statistics on the periods prior and post the introduction of the right to unilateral divorce. The main outcome variable is a dummy variable “currently working” which takes the value of 1 if the woman is employed at the time of the interview, and 0 otherwise. This variable is the most accurate representation of women’s labor market position. Between the pre and post reform periods the raw mean of women that declared being currently employed stagnated for The Arab Republic of Egypt 19
Summary statistics can be found in Table 1. Other control variables, namely, population and real GDP per capita (constant 2010 USD), are from the World Bank’s World Development Indicators.

|**Table 1: Summary Statistics - Panel **|**Obs**|**Mean**|**Std.**<br>**Dev.**|**Min**|**Max**|
|---|---|---|---|---|---|
|Firm Purchased Fixed Assets Y/N|26,172|0.42|0.49|0.00|1.00|
|Log of Amount Investment (+1)|26,187|4.24|5.38|0.00|26.33|
|Log of Amount Investment in Land and Buildings<br>(+1)|25,337|1.06|3.23|0.00|26.19|
|Log of Amount Investment in Equipment (+1)|25,712|4.06|5.25|0.00|26.33|
|Central government debt, % of GDP|26,187|39.33|28.14|0.55|336.22|
|Log of real GDP per capita|26,187|7.83|0.92|5.85|9.62|
|Log of age of firm|26,187|2.64|0.75|0.00|5.23|
|Log of Total Population|26,187|16.04|1.25|13.17|19.37|
|Log of size|26,187|2.74|1.14|-1.10|9.82|
|Direct exports 10
and total amount of spending to each country and/or subnational NUTS2 region is usually known well in advance before any actual spending takes place.<sup>29</sup> Second, is the _implementation step_ during the 7-year program which involves (i) some prepayments from the EU to member governments in advance of anticipated work to “provide liquidity” (for example, to provide an advance on a contract), (ii) work on the actual project, and (iii) the firm or government applying for _reimbursement_ from the EU as the work is done. The EU usually does not reimburse 100 percent of the costs (depending on the Fund) as the national government often has to make a copayment. The final step is the closure of the program, which involves the EU paying any remaining balances, conditional on the project being implemented satisfactorily. The closure of the program can take place years after the end of the program period. For example, the 2007–13 program was closed on 31 March 2017 (European Court of Auditors, 2018, p13).<sup>30</sup>

> 26 That is, suppose that 1% of observations are greater than a cutoff , and 1% are below (which implicitly defines and ). Then the winsorized data replaces the top 1% extreme observations with (rather than ii,tt 1HH 1LL dropping them) and replaces the bottom 1% of observations with XX . We call this 98% winsorized. Relative to dropping XX XX 1HH 1LL 1HH observations (an alternative approach), this winsorized data keeps the extreme observations in the sample but reduces XX XX XX 1LL their influence. We winsorized at the 90% level for NUTS2 data because it is more volatile than country-level data. XX 27 Other data we use for other regressions can be found in Online Appendix Tables A2.2 and A2.3.

> 28 There are also prepayments (payments to provide liquidity for future work), which further disconnects the timing of
access to fast-food outlets is linked to a rise in obesity (Powell et al. 2009; Larson et al. 2011; Currie et al. 2010). FAFH tends to be more calorie dense than foods prepared at home. Most consumers may be unaware of the high levels of calories, fat, saturated fat, and sodium found in many menu items and may underestimate actual calorie content (Burton et al. 2006). In particular, low-income and minority neighborhoods have disproportionately lower levels of access to healthier food sources and greater access to less healthy food sources (i.e. food deserts) (Bridle-Fitzpatrick 2015; Gibson 2011). Studies find significant associations between food environment, FAFH and weight gain (for example, see Kim et al. 2014; Seguin et al. 2016; Zeng and Zeng 2018).

Despite the growth of the literature on the effects of the food environment and FAFH, there are still significant research gaps (Steeves et al. 2014). In particular, a more detailed assessment of the food environment with regard to the (micro) nutritional quality of FAFH and the interplay of FAFH and excess body weight is needed for the design of better food environment interventions. The unique data set of this study includes micronutrients of most-consumed meals from a representative restaurant survey allowing us to shed light on this relationship at the population level in urban Peru. Among the different nutrients, we can identify the main drivers of poor nutritional quality and which combination of micronutrients are most likely to contribute to excess body weight when consumed above the recommended intake.

The present study differs from the current literature in three important ways. First, instead of using dietary recall data provided by interviewees on the frequency and quality of FAFH, which is prone to substantial measurement error, the study relies on detailed objective _nutritional information_ on the most frequently _consumed menus_ in the food environment of individuals. The detailed nutritional information is supplied by a representative sample of 1,605 restaurants in the Lima Metropolitan Area, among which nutrition
Policy Research Working Paper 10828

# **Abstract**

This paper reviews the main methods for small area estimation of welfare indicators. It begins by discussing the importance of small area estimation methods for producing reliable disaggregated estimates. It mentions the baseline papers and describes the contents of the different sections. Basic direct estimators obtained from area-specific survey data are described first, followed by simple indirect methods, which include synthetic procedures that do not account for the area effects and composite estimators obtained as a composition (or weighted average) of a synthetic and a direct estimator. The previous estimators are design-based, meaning that their properties are assessed under the sampling replication mechanism, without assuming any model to be true. The paper then turns to proper model-based estimators that assume an explicit model. These models allow obtaining optimal small area estimators when the assumed model holds. The first type of models, referred to as area-level models, use only aggregated data at the area level to fit the model. However, unit-level survey data were previously used to calculate the direct estimators, which act as response variables in the most common area-level models. The paper then switches to unit-level models, describing first the usual estimators for area means, and then moving to general area indicators. Semi-parametric, non-parametric, and machine learning procedures are described in a separate section, although many of the procedures are applicable only to area means. Based on the previous material, the paper identifies gaps or potential limitations in existing procedures from a practitioner’s perspective, which could potentially be addressed through research over the next three to five years.

This paper is a product of the Poverty and Equity 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 author may be contacted atisabelmolina@ucm.es.

_The Policy Research Working Paper Series