rafmacalaba/data-use-mentions-extended huggingface dataset:
# **3.1 Estimation of consistent poverty lines**

To identify poverty trends, it is common practice to select a poverty line for a base year and project this line into subsequent years using an appropriate temporal consumer price index (CPI). Alternatively, the reference poverty line can be held constant by expressing all monetary variables, previously adjusted for spatial cost-of-living differences, at the base year's constant values. Thus, the temporal price index plays a crucial role in dynamic poverty analysis. In the context of Bhutan, there is evidence that the official CPI for Bhutan underestimates the inflation faced by the poor over the period at hand: inflation recorded by the true cost of living index, based on the ratio of the nominal food poverty lines, is 87 percent, while the official food CPI only records 39 percent inflation (Amendola et al. 2023). For this reason, in this section we develop an analytical framework for identifying the poverty trend with no reliance on the official CPI. The proposed method anchors the trend to the official food poverty line for 2022: this means that the endpoint of the poverty trend will be close to the official point estimates for 2022 (NSB 2022).<sup>2</sup> The method consists in calculating the change in the monetary value of a _fixed_ reference food basket, which can be interpreted as a basic-needs basket consistent with the consumption pattern of poor households in Bhutan. The cost of such a basket can be used as the basis for calculating a food cost-of-living index. As detailed below, the construction of such an index is equivalent to the calculation of a Laspeyres-type price index based on the consumption basket of poor households. The index is then used to “move” the 2022 food poverty line back in time, which provides an anchor for estimating a new upper-bound poverty line.<sup>3</sup> _h_ : h h h h 0 1 2 � JJ qq = �qq , qq ,∙∙∙,
. Earthquakes are the most commonly mentioned geophysical risk. In Dominica in particular, 70 percent of households indicates being exposed to earthquakes and 44 percent to volcanic eruptions. Households in Saint Lucia also commonly refer to the risk of earthquakes (62 percent). While these risks may not feature prominently in the EM-DAT, these results are in line with the monitoring of geophysical risks by the UWI Seismic Research Centre. According to the UWI Seismic Research Centre (2023), there were 186 earthquakes in the English-speaking islands of the Eastern Caribbean in the period from August 1, 2022, to July 31, 2023, alone. And the Volcanic Hazard Atlas of the Lesser Antilles<sup>12</sup> (Lindsay et al., undated)

> 11 Households were also asked about any ‘other’ perceived risks. In Haiti and Suriname, respectively, 4.5 and 10.7 percent of households reported this option. No households in other countries reported other risks.

> 12 See https://uwiseismic.com/downloads/volcanic-hazard-atlas-of-the-lesser-antilles/ (last accessed on May 8, 2024).

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# **Appendix A. Additional Tables**

# **Table S1. An Overview of the World Bank’s Statistical Capacity Index (SCI) in Selected Recent Studies**

|1|Angrist, Goldberg &<br>Jolliffe (2021)|_Journal of Economic_<br>_Perspective_|Global analysis|Measuring economic growth in<br>developing countries|Poorer countries have lower statistical capacity,<br>which can severely bias their reported<br>measurements of economic growth.|
|---|---|---|---|---|---|
|2|Anderson & Whitford<br>(2017)|_Review of Policy_<br>_Research_|100 countries|Technological attainment and<br>statistical capacity|Countries with greater levels of technological<br>attainment have greater national statistical<br>capacity.|
|3|Goren & Winkler (2022)|_Journal of African_<br>_Economies_|57 African<br>countries|Low-quality statistics, slave trades<br>and development|Replacing mismeasured GDP per capita by<br>nighttime light intensity per capita significantly<br>reduces the impact of the slave trade on<br>economic development by a factor of 2 to 4.|
|4|Hanson & Sigman (2021)|_Journal of Politics_|139 countries|Measuring state capacity in<br>political science research|The SCI is most strongly correlated with state<br>capacity compared to other indicators in<br>bureaucratic quality, public administration, law<br>and order ratings, or state fiscal capacity.|
|5|Henderson, Storeygard &<br>Weil (2012)|_American Economic_<br>_Review_|113 countries|Better measuring income growth<br>with night lights data|SCI can help provide more accurate estimates of<br>country income growth.|
|6|Hu & Yao (2022)|_Journal of_
’ in Malawi) is a contiguous piece of land under a specific type of tenure that can comprise multiple plots, defined by the types of crop grown.

> 9 The basic information document for the survey (https://microdata.worldbank.org/index.php/catalog/2939/download/47216) and Kilic et al. (2020) give more information on survey organization and implementation modalities for individual data collection under the IHPS. 10 We define improved walls to be made of burnt bricks and/or concrete (59% of sample), improved roofs to be made of iron sheets, clay tiles, and/or concrete (18% of sample), and improved floors to be made of smooth cement, wood, and/or tiles (41% of sample) and compute an ‘improvement index’ by adding dummies for each of the indicators and dividing by 3.

> 11 Evidence on formal rights suggests that, for agricultural land, individuals with formal rights are more likely to have the right to bequeath and sell, an outcome driven by men’s rights as there is no significant difference for women. Similarly, men with formal documents are more likely to have bequest and sale rights but there is no difference in the aggregate.

9
# **_3.3. Descriptive Statistics_**

The process of adaptation to cultural change is not independent of the individual characteristics that follow migrant repatriation. Therefore, a series of respondent and household characteristics were used to estimate the differences between returned migrants and non-migrants to account for changes in gender attitudes: demographic and socioeconomic variables (sex, age, religion, education, employment status, access to loan), and living conditions variables (number of children under 5 years old living in the household, household size, owning land or house, place of residence, and household wealth).

Table 2 reports the summary statistics of the covariate variables by types of respondents: returned migrants from Gulf countries and Saudi Arabia, as well as non-migrants. The average international returning migrant had lived abroad for about 11 years. Over 65 percent of the returning migrants were over the age of 45, over 90 percent were married, and a majority had completed secondary school. The average household size was between 4 and 5. Most migrants owned their own home, while less than 20 percent owned land. Nearly 30 percent of all migrants were from urban areas. Based on the PCA, most migrants belonged to the upper three quintiles of the Wealth Index, and nearly 50 percent of them came from North Kerala, i.e., from the districts of Kasaragod, Kannur, Wayanad, Kozhikode, Malappuram.<sup>8</sup> Summary statistics on gender attitudes by type of migrants, presented in Appendix A, indicate some differences across migrant groups, with those returning from Saudi Arabia exhibiting more extreme views about women’s economic participation, mobility, and role in preserving the honor of the household. For example, 20.3 percent of returned migrants from Saudi Arabia shared the view that women should not work outside the home if economic conditions are better, as compared to 17.3 percent of returned migrants from GCC countries. The corresponding figures for those thinking women took jobs away from men when they
than those in households with longer outages; the opposite is true in 2012. Women in households with more reliable electricity supply have lower labor force participation and 6.1 fewer hours a month of employment in 2005 than their counterparts. The difference in women’s labor force participation and hours of employment decreases slightly between 2005 and 2012 but the sign remains the same. In the next section we explore the relationship between hours of electricity and households’ welfare outcomes in more detail.

Anecdotal evidence suggests that many households have illegal connections especially in rural areas. IHDS reports both official and non‐standard connections. As a result, the access rate reported by IHDS is higher than that by official records. Since IHDS inquires about the mode of payment for electric connections and the amount of payment, we are able to estimate the percentage of non‐standard connections, which include those who reported having access to electricity but did not receive bills and did not make a payment or paid to neighbors. We find that about 15 percent connections were non‐ standard in 2005. The number reduces to 9 percent in 2012. There is also a strong correlation between non‐standard connection and service unavailability. Overall, households who are unofficially connected experience 12 hours of power outages per day, compared to 10 hours for those with official connections. This result suggests that illegal connections could make service availability worse, and thereby, adversely affects the effects of electrification. It should be noted that illegal connection could still be underreported by IHDS. If that is the case, then benefits of electrification based on IHDS data could also be underestimated.

# **IV. Estimation model**

A base model for estimating the impact of electrification is described by equation 1: where _Yit_ denotes the outcome variables of interest for household _i_ in year _t_ , such as kerosene consumption, income and expenditure, time spent on studies by children, and labor force participation by men and women. _Xit_ is a vector of household‐ and community‐level characteristics.
|Number of provinces|63|63|63|63|63|63|
|---|---|---|---|---|---|---|
|Arellano-Bond test for AR(1)||||-7.372|-6.495|-6.190|
|Arellano-Bond test for AR(2)||||2.990|4.226|3.693|
|Sargan test||||310.5|135.8|114.9|

Note: i) Authors’ estimation from VHLSSs using province FE model (columns 1 to 3) and GMM model (columns 4 to 6), ii) Robust standard errors in parentheses clustered at the province level, iii)*** p<0.01, ** p<0.05, * p<0.1.

48
(Décret No 2016-242/PRE, 2018).

The Council, which has a permanent mandate, meets at least once a month; if judged necessary the President may call a meeting at any time (Décret No 2016-242/PRE and Reform Committee Survey). The President of the Republic also acts as the President of the Council, with six additional members including ministers of Economy and Finance, Investments and Foreign Affairs, the Secretary General, the President’s Economic Affairs Advisor and the Ports and Free Zones Authority’s President. The President can appoint at least two other members but cannot exceed five and they each serve a term of three years. The President holds the right to revoke appointments and members can be reappointed following the end of their term (Décret No 2016-242/PRE, 2018). In their absence, the President may also be represented at the reform council meeting by another duly mandated member. The minutes are taken at each council which must be 19
given that those children who were not measured are different, and they may be systematically different in other characteristics besides age as well.<sup>35</sup> Furthermore, since only a few children (less than 2 percent of the sample) experienced a positive pre- _canícula_ rainfall shock, the coefficient estimates for positive pre- _canícula_ rainfall should be interpreted with caution (Table 11).

Bearing these caveats in mind, Table 12 summarizes the average relationship between weather shocks and height-for-age. The full results for the specification are included in Appendix 4. A positive rainfall shock is associated with lower height-for-age scores. This is true for both a positive annual and a positive wet season rainfall shocks. The coefficient estimate of around 0.5 points is non-trivial given that a z-score of -2 is indicative of stunting and the average height-for-age z-score for the children in the sample is -1.09.<sup>36</sup> The earlier results based on the MxFLS consumption data suggest that there is no correlation between a positive rainfall shock and non-health expenditures, and that households spend more on food. Yet, the height of children under three years of age is negatively affected after such a shock. Together, these results suggest that direct environmental effects are important and that an analysis of the impacts of weather shocks at the household level has serious limitations in terms of capturing the impacts of these shocks on certain individuals in the household.

The negative impacts of a positive rainfall shock during the prior agricultural year or wet season are consistent in both of the regional subsamples (Table 12). The biggest impact is from a positive rainfall shock during the wet season in the North. Children who experienced such a shock are 0.7 points shorter than children who experienced an average amount of rain. Negative rainfall shocks appear to have different impacts in the Centre/South regions than in the North. Children living in the Center/South region are taller if the prior agricultural year or wet season was at least
consistent measure of effective tax rates across multiple countries, relying on comparable data sources and definitions. The data cover 13 countries with varied income levels and population sizes in Africa (Ethiopia, Eswatini, Rwanda, Senegal, and Uganda), Latin America (Costa Rica, Dominican Republic, Ecuador, Guatemala, Honduras, and Mexico), and Eastern Europe (Albania and Montenegro). By using administrative data, we include all tax-registered firms, a much larger group than those covered by survey or financial data in developing countries.<sup>1</sup> Although tax reporting requirements are not homogeneous across countries, we harmonize the relevant variables used to define

> 1Tax return data miss the informal sector, but they still have much wider coverage than financial data which in most developing countries cover only the largest firms. Survey data often have poor coverage among the largest firms. Firm censuses, where they exist, cover all firms but rarely contain data on tax liabilities and profits.

1
distributional consequences of the increase (the impact on income inequality and the identification of the winners and losers). We aim to identify effects on the wage distribution if only the minimum wage policy changes, keeping everything else constant; therefore, this exercise aims to identify the potential impacts of the policy, and it is different from a forecasting exercise where the objective is to replicate the actual distributions, given many changes in the economic environment. This part of our research is based on the administrative tax data and the method previously used by Robayo-Abril et al. (2020) to provide an ex-ante evaluation of the impact of the several minimum wage increase scenarios on Romania's labor market outcomes. This approach enables us to estimate the broader economy-wide effects and the more granular micro-level consequences of different policy options.

# Methodology and Assumptions

**We rely exclusively on administrative tax data for the microsimulation.** The administrative tax data comprises a series of 12 monthly datasets. Considering that income evolves throughout the year, we work with one of the year's final months. Hence, we have opted to use data from November 2021. Notably, we exclude December 2021 due to the potential seasonality caused by annual bonuses during that month. Some additional robustness checks were performed using EU-SILC and matched administrative tax data, as presented later in this section.

**As mentioned above, the administrative tax data does not provide direct information on the skill level of the taxpayers.** Therefore, we use the employer's NACE sectoral code as a proxy for skill level. We assume that people working in the following sectors are skilled workers: information and communication; financial and insurance; professional, scientific, and technical activities; public administration and defense, education; human health and social work activities; arts, entertainment and recreation, activities of extraterritorial organizations and bodies. The remaining taxpayers are classified as unskilled. The share of skilled workers in our sample is 35.97%. In the EU-SILC 2021, where the information
because of a high occurrence of missing data and the data collection design,<sup>8</sup> our analysis is restricted to outcomes for which there are sufficient observations in terms of the ECT treatment. The structure of the survey and the issue of missing data also lead to highly unequal sample sizes across the different outcomes.<sup>9</sup> Therefore, our active sample ranges from 187 to 913 observations depending on the outcome of interest and the specification (i.e., cross-sectional or pooled cross-sectional estimation). Moreover, some of the child human capital outcomes were exclusively collected in Round 1 whereas others in Round 2, limiting the scope of the analysis to only one of the two rounds. These characteristics of the CIMS data limit the scope of the analysis presented in this paper. A discussion on the data and future efforts for data collection that could make the analysis more robust are discussed in Section 6.

The timing of the implementation of the ECT and of the CIMS data collection allow us to analyze two cohorts of beneficiaries: households that received the ECT before the first round of CIMS (hereafter referred to as ECT-R1 beneficiaries) and households that received the ECT after the first round of CIMS (hereafter referred to as ECT-R2 beneficiaries). The timing of the survey and the data collection (see Figure 1) allows us to analyze short-term ([0;3] months lapse between receiving the ECT and the survey) and medium-term ([3;7] months lapse) impacts of the ECT for ECT-R1 beneficiaries. We consider the impact of the ECT on ECT-R2 beneficiaries as a medium-term impact ([3;4] months lapse).

Table 2 shows that the ECT was mostly used for food (76 and 80 percent respectively in Rounds 1 and 2) and investing in an existing business (73 and 86 percent respectively in Rounds 1 and 2). The other

> 8 Part of the questionnaire was administered to all respondents (i.e., Basic
worse scores than they might otherwise have received simply because they are implicitly being compared with countries in which various aspects of govemance are likely to be much better.14 For example, representative surveys such as DRI or PRS assign moderate scores of 55/100

> 13 The straighfforward solution to this problem would be to rely on an ordered multinomial choice model with individual effects in the latent variable. HoWever, for such a model to be identified, it would again be necessary to assume that the variances of the errors are identical across indicators.

> 14 This problem may be particularly acute for polls of experts who consider a large set of countries at once, since in contrast to surveys of residents, experts are much more likely to be aware of relative comparisons of countries.

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# **IV. Main Results**

We find that informal workers do not have lower satisfaction with their jobs, nor lower selfreported health. After controlling for personal characteristics and work conditions, formal and informal workers have no systematic difference in job satisfaction. In terms of self-assessed health, formals and informals never show a systematic difference. On the other hand, we find a significant and growing wage gap between formal and informal workers, and a statistically significant association between informality, life dis-satisfaction, and household poverty among certain types of informal employment.

## **Informal employment and working conditions**

We first explore whether informal workers experience different work conditions. We answer this question making use of detailed information from three surveys. Our analysis includes the number of hours worked (from RLMS), whether the worker has a set or contracted number of hours (from the ESS), and whether the worker would like to work more hours (from the LiTS). Using number of hours worked, we define binary variables that are equal to one if the worker reports to have worked less than 20 hours per week or more than 50 hours per week. Additional measures of work conditions also include binary variables for whether a worker received paid vacations last year, whether the job was considered harmful or dangerous, and whether the worker is concerned about losing their job. The RLMS also provides subjective assessments on the worker’s satisfaction with the job’s work contract, growth opportunities and pay. Responses to these questions are recorded in a five-point scale, from absolutely dissatisfied to absolutely satisfied, which we use to define a binary outcome variable that equals one if the worker reports being not very satisfied or absolutely unsatisfied with her work contract or the job’s growth opportunities. A summary of unconditional means of these work conditions between formal and informal workers is illustrated in Figure 9.

On average, informal workers are more likely to work non-standard hours and have less stability in terms of work hours. Specifically, informal workers
39

# Table 4: Rank correlations on author data

||Publication<br>count<br>(_I_<sup>3</sup> =0)|Total citations<br>(_I_<sup>3</sup> =1)|_h_-index(_I_<sup>1</sup>)|Quadratic<br>Influence<br>Function (_I_<sup>2</sup>)|_I_<sup>3</sup> =0.5|Citations of<br>most-cited<br>publication|
|---|---|---|---|---|---|---|
|Publication count (_I_<sup>3</sup> =0)<br>|1.000||||||
|Total citations (_I_<sup>3</sup> =1)<br>|0.477|1.000|||||
|_h_-index (_I_<sup>1</sup>)<br>|0.376|0.678|1.000||||
|QIF (_I_<sup>2</sup>)<br>|0.479|1.000|0.677|1.000|||
|_I_<sup>3</sup> =0.5|0.554|0.991|0.696|0.991|1.000||
|Citations of most-citedpublication|0.399|0.991|0.660|0.991|0.967|1.000|

Note: The starting point was our database of 33,000 publications in EconLit with a health JEL code. Google Scholar citation data were obtained for as many as possible (80 percent) in June 2011. Each listed author was