rafmacalaba/data-use-mentions-extended huggingface dataset:
regulations (Figure 5, left panel) and the broader index using all seven variables. To compute the index we use alternatively the first principal factor of the informality variables and a simple average (both normalized to take values between 0 and 100), with results being very similar across the two.

More than 80 percent of micro and small businesses in Ecuador operate somewhere on the “informality continuum,” complying with some rules but not others. There is a relatively high level of compliance with tax-related regulations (over 70 percent of firms report to have a RUC and to request receipts systematically) and, to a lesser extent, with municipal licenses (54 percent). Among those firms who are required to be incorporated by a public notary or appear in the official firm registry, compliance is also relatively high: 77 percent comply with incorporation and 63 percent with registration rules. On the other hand, labor regulation compliance is notably lower. On average, firms affiliate only 20.5 percent of their employees with social security, and the rate of compliance is substantially lower for smaller firms. Moreover, most firms (over 70 percent) affiliate zero employees and a smaller percentage (less than 20 percent) affiliate all their employees with virtually no firms in between (Figure 6). Likewise, an average firm provides written contracts to just 13.1 percent of its employees.

**Figure 6: Distribution of firms by percent of employees affiliated with IESS**

<!-- Start of picture text --> 0 .2 .4 .6 .8 1<br>Share of employees affiliated with IESS<br>Source: EMES<br>80<br>60<br>40<br>Percent of firms<br>20<br>0<br><!-- End of picture text --> As expected, the level of compliance varies systematically across size, with micro firms below average and small and medium firms above. For instance, 72
appear to be high degrees of tailoring to country context and concentration of funds in fewer sectors are associated with stronger outcomes. In doing so, we use newly available data on project characteristics and draw on methodological advances at the intersection of causal inference and econometrics with machine learning. To our knowledge, this is the first attempt to quantify the importance of project contextualization to development effectiveness.

Our findings have actionable implications for the system through which the World Bank and other development institutions evaluate project performance, by offering a cautionary tale against the over-reliance on project ratings as impact metrics. It also has implications for the design and staffing of these projects.

> 3The same class of models that power all state-of-the-art translation, search engines, AI text generators, as well as most plagiarism detectors.

1
In the case specifically discussed here, the Mogadishu High Frequency Survey Pilot, the team opted to use segmentation as a compromise between preparation time, ease of implementation, and the time and complexity necessary for the weight calculations. The implementation was generally successful despite a number of difficulties in the field. Teams occasionally encountered high‐level security threats and exploitative rent‐seeking from local leadership. The complexity of the survey protocols, including the sampling design, slowed the implementation of the survey. Also a substantial number of observations had to be discarded because the interviewed points did not fall within the boundaries of the selected segments or because interviewed households did not appear on segment listing forms. Regardless of these challenges, however, it was possible implement a complex and yet rapid, high‐quality survey in one of the most challenging urban contexts known to date.

20
decades, allowing us to study the process of structural transformation and the evolution of gendered labor market outcomes over a long period of time. The six economies span a wide income spectrum (Figure OA.7 in the Online Appendix) and cover around 25-30% of the world population. For Indonesia, we complement the IPUMS census data with the SAKERNAS labor force survey to extend the time coverage of wage data to 2018. For India, we use survey data from the National Sample Surveys (NSS), the Employment-Unemployment Survey (EUS), and the Periodic Labor Force Survey (PLFS) up to 2018.

**Sector and Occupation Classification.** We define three market sectors – agriculture, manufacturing, and services – by assigning the more detailed industry codes from IPUMS and the labor force surveys to these three categories. The categorization follows the literature (Herrendorf et al. (2013); Herrendorf and Schoellman (2018)) and is outlined in Online Appendix C, Table OA.6. We define a fourth sector as the “home sector” to which we attribute unemployed and inactive individuals, following Hsieh et al. (2019).

At the occupation level, we use 1-digit ISCO codes. We aggregate the top three ISCO codes, which results in the following seven occupation categories: (1) professionals, (2) clerks, (3) service workers, (4) skilled agricultural workers, (5) crafts and trades workers, (6) plant and machine operators, and (7) elementary occupation workers. To minimize measurement errors arising from small sample sizes in specific occupation-sector-gender cells, we impose two restrictions. First, we consider only two occupations within the agriculture sector: skilled agricultural workers and elementary occupations.<sup>7</sup> Second, we model the occupation of “skilled agricultural workers” only in the agriculture sector and we assign all workers in that occupation to the agriculture sector. More information is provided in Online Appendix C.

**Construction of
effective in the struggle against fiscal procyclicality of the general government because of the application of subsidiarity principle. Indicators of fiscal decentralization generally refer to the fiscal composition ratio established by the IMF’s Government Finance Statistics Yearbooks (see Blume and Voigt (2008) and Blume et al. (2009) for more details). Instead of establishing arbitrary thresholds for the fiscal ratio, we focus on indicators of political decentralization (PD) established by the Database of Political Institutions provided by the World Bank Group. Namely, we focus on (i) whether there are contiguous autonomous regions; (ii) whether local governments and legislature are elected; (iii) whether state/provinces governments and legislature are elected; (iv) whether states/provinces have authority over taxing, spending, or legislating; and (v) whether the constituencies of the upper house members are the states/provinces. We focus on the period 2009-2015 (2016 not available yet in data) to evaluate the efficiency of post-crisis policies. The correlations (Table C.3 and Figure C.3) show that the closest proxy of fiscal decentralization (i.e. the authority of states/provinces over spending, taxing or legislating) is negatively correlated with fiscal procyclicality, suggesting that decentralization may be a tool to mitigate the procyclicality bias.

20
The loans were rolled out at Wasasa’s branches in the cities of Adama and Assela, in the Oromia region of Ethiopia. The psychometric-appraised, uncollateralized loan product was branded as a “WEDP-X” loan and was advertised to women entrepreneurs participating or interested in WEDP in those cities. WEDP-X was advertised via flyers at the “One-StopShop” offices where WEDP clients register and access advice and services. One-Stop-Shop staff were trained to highlight these flyers to prospective clients. The flyers and staff script specified that if a woman wanted a loan for her business but lacked collateral, she could take a 45-minute tablet-based test to enable the MFI to know her better, and then potentially be offered an uncollateralized loan with the features mentioned above.

# **3 Experimental design**

The application and baseline survey process took place on a rolling basis from April 2018March 2020.<sup>6</sup> Women entrepreneurs presented themselves at Wasasa branches in the cities of Adama and Assela if and when they wished to apply for a loan. The full application process was explained to women before they applied for a WEDP-X loan, including that only half of those women who qualified for the loan would actually receive the loan due to the need to test a new product, and that this would be determined by computer-randomized assignment.

As soon as a woman decided to apply, she completed the psychometric test on a tablet, in private, then and there at the Wasasa branch office. A short additional baseline survey was then administered to her by MFI loan officers working at the Wasasa branch, also on a tablet. The psychometric test data was synced to a server, which calculated the psychometric credit score in real time. The score was then sent through to the branch computer and viewed by the loan officer. Applicants scoring above the cut-off were told they were potentially eligible for the loan, and invited to submit documentation and schedule a business appraisal. For

> 6The baseline survey was concluded earlier than planned due to the COVID-19 pandemic. Ethiopia saw
# **3.2 Breakdown by size**

To break down the number of firms by employment size, we develop a method that leverages complementary information from the WBES and census microdata from Ghana, Burkina Faso, Cameroon, and Rwanda. We also use a representative survey for Kenya. These data sources are combined in a framework that links the proportion of different firm sizes to key moments of the firm size distribution.

Using the five-worker threshold for micro firms, as per WBES size classification, figure 2 suggests that the proportion of micro firms will vary depending on the shape of the distribution. The economy of Cameron will have more micro firms (88%) than Ghana (80%) but fewer than Rwanda (93%). It is natural, then, that Ghana has a larger share of small firms (those employing between 5 and 20 workers),which is reflected in the larger grey shaded area between the reference point 5 and 20 in figure 2. In general, a firm size distribution that looks more like Ghana’s will yield a higher proportion of small firms than a firm size distribution that looks more like Rwanda.

Figure 2: Firm Size Distribution and Size Brackets: from establishment census data <!-- Start of picture text --> Firm Size Distribution and Size Brackets<br>Burkina Faso (2016) Cameroon (2009) Ghana (2014)<br>.8 .8 .8<br>.6 .6 .6<br>.4 .4 .4<br>.2 .2 .2<br>0 0 0<br>5 20 100 5 20 100 5 20 100<br>Average firm size Average firm size Average firm size<br>Rwanda (2014) Rwanda (2017) Rwanda (2020)<br>.8 .8 .8<br>.6 .6 .6<br>.4 .4 .4<br>.2 .2 .2
Policy Research Working Paper 6366

# **Abstract**

The extent to which local communities benefit from commodity booms has been subject to wide but inconclusive investigations. This paper draws from a new district-level database to investigate the local impact on socioeconomic outcomes of mining activity in Peru, which grew almost twentyfold in the last two decades. The authors find evidence that producing districts have better average living standards than otherwise similar districts: larger household consumption, lower poverty rate, and higher literacy. However, the positive impacts from mining decrease significantly with administrative and geographic distance from the mine, while districtlevel consumption inequality increases in all districts belonging to a producing province. The inequalizing impact of mining activity, both across and within districts, may explain part of the current social discontent with mining activities in the country, even despite its enormous revenues.

This paper is a product of the office of the Chief Economist, Latin America and the Caribbean Region; and Development Economics. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http:// econ.worldbank.org. The author may be contacted at jrigolini@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
Policy Research Working Paper 9266

# **Abstract**

In Kosovo, employers report significant skill shortages, which limits firm growth and job creation. To understand the labor market dynamics and employer needs in real time, this paper analyzes the content of job postings using data from major online job portals from 2018. The findings show that the skills that are most in demand are socioemotional skills (especially related to extraversion), foreign language skills, and computer skills. The importance of these skills is transversal, cutting not only across occupations and industries, but also universally demanded in all education fields. The need for these skills is expressed more often and more explicitly in postings for jobs requiring higher levels of experience. Moreover, job platforms are used almost exclusively for filling high-skill occupations, especially in Kosovo’s capital city, Pristina, whereas many low- and medium-skill jobs and jobs outside the capital are filled through informal channels. Overall, online data can be a useful tool for policy makers and other stakeholders to help align career services, training programs, and educational curricula with the skill needs of firms in real time.

This paper is a product of the Social Protection and Jobs Global Practice. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at amarguerie@worldbank.org, sbrodmann@worldbank.org and brancatelli@econ.uni-frankfurt.de.

_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.
# Using Mobile Phone Data to Reduce Spread of Disease<sup>_∗_</sup>

Sveta Milusheva JEL Classication: H51, I15, J18, I18, O15 Keywords: Health, big data, epidemics, mobility, public policy, mobile phones

> _∗_ I am grateful to Andrew Foster, Jesse Shapiro, and Daniel Bjorkegren for their continuous guidance on this project. I would like to thank Victor Alegana, Girija Borker, David Glick, Morgan Hardy, Arianna Legovini, Emily Oster, Nick Ruktanonchai, Bryce Steinberg, Andrew Tatem and William Violette for valuable feedback. I appreciate the comments from participants at the World Bank ABCDE Conference, the NEUDC Conference, the PopPov Conference, the Population Health Sciences Workshop, the PAA Conference and the Brown microeconomics lunch seminar. Thank you to the Bill & Melinda Gates Foundation (grant OPP1114791) and the NICHHD (grant T32 HD 7338-29) for nancial support. Anonymous mobile phone data have been made available by Orange and Sonatel within the framework of the D4D-Senegal challenge. I thank Philippe Guinot and Yakou Dieye, PATH and the National Malaria Control Program for providing the data on malaria incidence and helpful feedback.
for each combustion power plant, we compute the count of the population 65 or older residing within 50 km by multiplying the all-age population counts, described in the data section, by the fraction of the population 65 or older. Information on the fraction comes from World Bank (2023a) and is available at the country year level. Accordingly, this calculation assumes that the age distribution is uniform within countries.

In the fourth step, we derive counts of premature deaths at the plant-month-year level by multiplying the variables described in steps one to three. For ease of presentation, we aggregate this count of premature deaths to the LAC by year level.

Last, to account for uncertainty in our estimate of excess air pollution, in the first step, we draw our coefficient from a normal distribution with a mean equal to the estimated coefficient (1.55) and a standard deviation equal to the standard error (0.31). We then repeat 1,000 times steps one to four, taking a new draw each time.<sup>11</sup> Figure 6 plots the evolution of drought-induced premature deaths in LAC. The spread of the box plot displayed each year results from the uncertainty in our estimation of excess PM2 _._ 5 concentrations and the observed FHD. The figure reveals the scale of the cost for LAC, with median premature deaths per year ranging from 3,681 to over 10,610. In Figure A2 in the appendix, we show that using the CRFs from Liu et al. (2019) leads to median premature deaths per year that are in the order of 503 to 4,987. The CRFs from Liu et al. (2019) have the advantage of being derived for Chile and Mexico but have the disadvantage of not being causal CRFs.

Another important consideration is that our counts of premature deaths could underestimate the actual number of deaths if groups with lower socioeconomic status are disproportionately exposed and vulnerable to PM2 _._ 5. There are several reasons why exposure
respondent. However, the latter could just be picking up a spatial autocorrelation in income measurement errors, giving spurious social effects.

The measurement of comparison-group welfare also poses a problem. In the nearuniversal approach in the literature, the researcher must make an _a priori_ judgment about the relevant comparison group. Yet this can vary greatly from person to person. It has been argued that ―... comparisons are most salient if individuals perceive the reference person or group as in some way similar to themselves‖ (Kahneman and Varey, 1991, p. 140). But that is based on the individual’s own judgment, given idiosyncratic informational and social factors that a researcher would have a very hard time observing in any systematic way. Neither psychological nor economic theories of relative deprivation offer much insight into what constitutes the relevant comparison group. The researcher must make some potentially strong identifying assumptions.

There are also concerns about survey design and implementation effects, including sensitivity to how questions are asked and the context. It is known that precisely how, and in what circumstances, one asks subjective questions matters to the results. In survey data for Britain, Taylor (2006) finds that those interviewed on a Friday report significantly greater job satisfaction and less mental stress than those interviewed mid-week, controlling for other observed factors. Also for Britain, Conti and Pudney (2011) find that seemingly small changes in how questions on satisfaction with work were asked led to large changes in the answers obtained, particularly for women. Moreover, they find that the measurement errors are not ignorable, in that the distortions influence findings on the determinants of job satisfaction. They also find evidence of a ―put a good show for the visitor effect‖ (Conti and Pudney, 2011, p.1093)— whereby there is an upward bias in reported welfare in open oral interviews relative to when the questionnaire is completed in private—and a ―not in front of the children effect‖ (p.1093), whereby there was another upward
economies—but these economies can only price 49 percent of CO2 emissions from energy use (OECD, 2021).

> 2 There are also a number of studies investigating the effects of natural disasters on temporary (transient) poverty (e.g., Sawada and Takasaki, 2017). Our study, in contrast, focuses on chronic poverty as a result of climate change.

> 3 Other studies mostly focus on a country-specific context. See also Karim and Noy (2016) and Hallegatte _et al._ (2020) for recent reviews of the literatures on climate change, natural disasters, and poverty. Furthermore, since we analyze poverty and inequality using the same source of official household survey data, our estimates are consistent (and more comparable) than estimates that are based on different data sources.

4
.80|2.74|3.32|3.03|
|Number of Days Eating<br>Vegetables Last Week|3.91|5.03|4.47|2.11|2.67|2.39|
|Number of Days Eating<br>Fruits Last Week|1.20|1.71|1.45|0.74|1.08|0.91|
|Number of Days Eating<br>Proteins Last Week|4.24|5.24|4.74|1.26|1.99|1.63|
|Number of Days Eating<br>DairyLast Week|4.00|5.04|4.52|1.99|2.53|2.26|
|Number of Days Eating Fats<br>Last Week|6.76|6.97|6.87|5.05|5.46|5.25|
|Number of Days Eating<br>Sugars Last Week|6.64|7.00|6.82|5.25|5.69|5.47|
|Share Living with Improved<br>Water|0.347|0.561|0.454|0.177|0.332|0.254|
|Share with Access to<br>ElectricityNetwork|0.674|0.877|0.776|0.000|0.010|0.005|
|Share Relying on Solar<br>Energy|0.000|0.044|0.022|0.444|0.657|0.550|
|Share Relying on Generator<br>Energy|0.005|0.050|0.027|0.120|0.349|0.235|

Notes: This table compares variables common to both the November 2017 WFP mobile phone survey and the
Policy Research Working Paper 5916

# **Abstract**

This paper validates a recently proposed method to estimate intra-generational mobility through repeated cross-sectional surveys. The technique allows the creation of a “synthetic panel”—done by predicting future or past household income using a set of simple modeling and error structure assumptions—and thus permits the estimation of lower and upper bounds on directional mobility measures. The authors validate the approach in three different settings where good panel data also exist (Chile, Nicaragua, and Peru). In doing so, they also carry out a number of refinements to the validation procedure. The results are broadly encouraging: the methodology performs well in all three settings, especially in cases where richer model specifications can be estimated. The technique does equally well in predicting short and long-term mobility patterns and is robust to a broad set of additional “stress” and sensitivity tests. Overall, the paper lends support to the application of this approach to settings where panel data are absent.

This paper is a product of the Poverty, Equity and Gender Unit, Latin America and the Caribbean 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://econ.worldbank.org. The authors may be contacted at rvakis@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or