rafmacalaba/data-use-mentions-extended huggingface dataset:
to repay a loan. Despite limited financial record-keeping, three-quarters of borrowers can calculate the costs of the products and services they offer.

KUR borrowers range in age from the late teens to the elderly, with an average entrepreneur age of 40 years old. Thirty-seven percent of borrowers are female, and 63 percent are male. Borrowers have education levels roughly on par with the working age population in Indonesia; however, individuals with no formal education are under-represented and those with upper-secondary levels of education are over-represented among KUR borrowers. Most do not have formal business training and have instead developed business skills through learning by doing or through the support of friends and family with businesses. A more detailed description of KUR borrowers is provided at Appendix A.

# 2.4 Data

We use four types of data to explore how KUR works from the perspective of MSME borrowers who received KUR between 2015 and 2020. First, we use administrative data from the KUR program database to explore

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**MONGOLIA'S INFORMAL** SECTOR -

Appendix B: Methodologies and Descriptive Statistics

**36**

Remembering that Fi = Fm,x HmJ/Hi, and canceling out the Hmax, we have: <!-- Start of picture text --> H<br>F. ,<br>iH.<br><!-- End of picture text --> 105. This equation provides the basic adjustment for the population frequency. Figure 8 illustrates the frequencies of hours driven in a week, generated by the sample survey (labeled "sample"), and adjusted using the procedure outlined above (labeled "population").

106. The effect of the population adjustment is to reduce the mean average hours used as a taxi in a week from 37.1 to 17.8. As can be seen from Figure 8, the proportion of vehicles used less than, say, 20 hours per week is much larger after adjusting for the sample selection bias, consistent with the notion that many vehicles are driven as taxicabs only parttime.

<!-- Start of picture text --> Hours Used as a Taxi in a Week<br>Sample and Population Frequencies<br>40%<br>30%<br>20%<br>10% 9'\<br>0%<br>51)<br>hours per week 110<br><!-- End of picture text --> 107. In the preceding paragraphs we derived estimates related to the population of vehicles that are _ever_ used as taxicabs. **0%** We must also account for the fact that some vehicles are never used as taxicabs - **51)** such vehicles would not be sampled at all, and would therefore not be accounted for hours **per** week in the above population adjustment. Now **Figure 8** we address the issue of the true population _Source:
that in the short-run climate-related migration is mainly a domestic issue, the latent potential for large-scale, international movements is often referenced in public discourse (Lustgarten, 2020) although poorly studied and substantiated by empirical evidence.<sup>5</sup> In particular, there is an absence of rigorous evidence on the interconnection between internal and international migration in the medium- to long-term (Cirillo et al., 2022) and the linkages with different types of climate change occurrences (slow-changes _vs._ rapid-onset shocks or their cumulative effect). Datasets on international migrants (especially on flows) are rare and outdated and, even when available, they rarely include the type of information that can be used to reconstruct the chain of migratory events potentially triggered by distinct climate change events or to understand behavioral responses and impacts at the micro level. Recognizing that repeated droughts, floods, progressive warming, sea level rise and desertification are much more important as indirect (rather than direct) drivers of cross-border mobility yields new, context-specific empirical questions – and associated data demands – regarding the channels through which this indirect mechanism operates. This suggests a change of perspective is needed to overcome the traditional distinction between “survival” migration and economically-driven migration, and consider the continuum (World Bank, 2023) and related intermediate outcomes that can act as push factors in determining international movements.

> 4 The study of climate migration involves the use of a variety of approaches many of which can be simplistic as they do not account for any behavioral aspects, or they do only to a limited extent (e.g., exposure mapping, gravity modeling). More refined approaches, such as agent-based models, that build on statistical and econometric analysis to model the behavior of different decision makers to climate-induced changes are still scarcely utilized as they require data on migration and key determinants at the micro level.

> 5 See section 2.2 for a more detailed discussion on this issue.

3
in the census for 1,440 communities in Chiapas. Finally, we match information about school closures from the school census in the same year (2019).

This set of educational outcomes is particularly conducive for our analysis. Secondary school is a critical period for the educational outcomes of the disadvantaged population under study, as more then a quarter of the 12 to 14 year olds in Chiapas are out of school. Likewise, 13 percent of school-aged children are still illiterate. The year of the data collection in the census (2019, two full school years after the rollout of the _Plus_ modality at scale) is consistent with the length of exposure to the API program in the second experiment. These census-based outcomes cover the quasi-universe of the localities in Mexico and, unlike other survey-based or administrative test score measures, they are not subject to any censoring during the data collection due to school closures. This allows us to avoid the concerns about selection bias due to differential school closures induced by the program at scale (see Section 4.3).

We analyze the impact of the policy implementation of the program using the following linear regression model: where _Yj_ is a school-level outcome for school _j_ , while _Plusj_ takes a value of one if school _j_ receives a mentor during the government implementation of the _Plus_ modality, and zero otherwise. The vector **_X_** _j_<sup>_Criteria_</sup> consists of all the criteria used for the assignment of the program. The parameter of interest, _α_ 1, represents the effect of the program during the government implementation on the outcome of interest. As was the case for the exposure analysis discussed in the previous section and formalized by equations (4)-(5), to causally interpret the estimates we need the assignment of the program across communities to be _conditionally_ as good as random. In other words, conditional on the assignment criteria, schools that receive and do not receive the program at scale are similar in terms of unobserved characteristics. As before
(605):236–265.

- J-PAL, CEGA, and ATAI (2016). Make it rain. Policy Bulletin, Cambridge, MA: Abdul Latif Jameel Poverty Action Lab, Center for Effective Global Action, and Agricultural Technology Adoption Initiative.

- Jackson, C. K. and Mackevicius, C. (2021). The distribution of school spending impacts. NBER Working Paper No. 28517.

- Janzen, S. A. and Carter, M. R. (2019). After the drought: The impact of microinsurance on consumption smoothing and asset protection. _American Journal of Agricultural Economics_ , 101(3):651–671.

- Jensen, N. and Barrett, C. (2017). Agricultural index insurance for development. _Applied Economic Perspectives and Policy_ , 39(2):199–219.

- Jensen, N. D., Barrett, C. B., and Mude, A. G. (2017). Cash transfers and index insurance: A comparative impact analysis from northern Kenya. _Journal of Development Economics_ , 129:14– 28.

- Karlan, D., Osei, R., Osei-Akoto, I., and Udry, C. (2014). Agricultural decisions after relaxing credit and risk constraints. _The Quarterly Journal of Economics_ , 129(2):597–652.

- Kazianga, H. and Wahhaj, Z. (2021). Enhancing access to index-based weather agricultural insurance: a new marketing approach in Burkina Faso. AEA RCT Registry. January 13. https://doi.org/10.1257/rct.5180-1.0 .

26
types of indirect taxes—green taxes, custom duties, sales taxes and excise—in the CEQ analysis; however, the imputation of indirect taxes is restricted to the goods and services that are captured in the BLSS. Custom duty is applied on imported goods, while sales taxes and green taxes are applied on both domestic and imported goods. In 2017, excise is only levied on domestically manufactured alcoholic beverages (see Appendix for the applicable tax rates).

Since we use a household survey which only includes consumption by households, many goods and services with sales tax cannot be identified in the survey (for example, raw materials). In the BLSS, we can identify whether the food consumed is domestically produced or imported using the relevant question. However, unfortunately, this question was not asked for non-food consumption. We apply custom duty on imported

> 20 Furthermore, we also utilize information that describes the primary source income of the household.

> 21 Educational household expenses (up to Nu. 50,000) and donations are deducted from the taxable base of the highest-income individual in the household.

14
2009, April to June 2010, and August to November 2010.<sup>22</sup> The campaign also included print materials such as posters with reminders of key junctures in which to wash hands with soap, comic books, and brochures featuring a superhero cartoon character _(Super Jaboncin_ ) created especially for the campaign. Additionally, promotional events such as street parades, games, and local theater performances were conducted in public spaces, where _Super Jaboncin_ came to life to promote handwashing and the use of soap. The jingles developed for the radio spots were used as the events’ background music, ensuring that the target audience received the same messages from multiple channels. On average, the events lasted from two to three hours and had audiences of 100 to 1,000 women and children.

# **2.2 District-Level Intervention: Community Treatment**

The community (or community and school) intervention was conducted at the district level and consisted of:

- a mass-media plus DCC campaign;

- training of trainers of community-based agents of change such as teachers, medical professionals, and community leaders;

- capacity building and provision of educational handwashing sessions for mothers, caregivers, and children; and

- handwashing curricula in select primary schools.

With all these activities, the community intervention aimed to achieve an integral and sustainable change through different actors and channels.

The communications campaign included broadcast radio advertisements with the same messages and frequencies described in the province-level treatment, and print materials such as posters with reminders of key junctures in which to wash hands with soap. It also included print materials featuring _Super Jaboncin_ , the superhero cartoon character developed for the campaign. As part of the communications strategy, the community activities were intentionally tied to the handwashing promotional events. The events took place in different

> 22 According to the baseline survey held for this study, 79 percent of the households had a radio, CD, or cassette player (see Appendix 1 for more information on household assets).

9
**Figure 5: Nominal exchange rate against the USD, annual and monthly**

<!-- Start of picture text --> 30<br>30<br>25 28<br>26<br>20 24<br>22<br>15<br>20<br>18<br>10<br>16<br>5 14<br>12<br>0<br>10<br>Source: Data from NBE.<br>2001/02 2002/03 2003/04 2004/05 2005/06 2006/07 2007/08 2008/09 2009/10 2010/11 2011/12 2012/13 2013/14 2014/15 2015/16 2016/17 2017/18 Jul. 13 Nov. 14 Mar. 14 Jul. 14 Nov. 14 Mar. 14 Jul. 15 Nov. 15 Mar. 15 Jul. 16 Nov. 16 Mar. 16 Jul. 17 Nov. 17 Mar. 17 Jul. 18 Nov. 18<br><!-- End of picture text -->

**Figure 6: U.S. Real Effective Exchange Rate (REER) index**

<!-- Start of picture text --> 125<br>120<br>115<br>110<br>105<br>100<br>95<br>Source: US Federal Reserve.<br>Jan. 12 Apr. 12 Jul. 12 Oct. 12 Jan. 13 Apr. 13 Jul. 13 Oct. 13 Jan. 14 Apr. 14 Jul. 14 Oct. 14 Jan. 15 Apr. 15 Jul. 15 Oct. 15 Jan. 16 Apr. 16 Jul. 16 Oct. 16 Jan. 17 Apr. 17 Jul. 17 Oct. 17 Jan. 18 Apr. 18 Jul. 18 Oct. 18 Jan. 18 Apr. 18<br><!-- End of picture text
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 professionals and experts at the National Institute of Statistics and Informatics collected information on the main menus offered. For each restaurant, nutritional specialists observed the preparation of the most popular menu and recorded and weighted all ingredients. In addition, for a subset of restaurants, the ingredients were taken to the laboratory for further analysis. As a result, we can calculate exact, objective data on the quantity of calories, proteins, fat, carbohydrates, fiber, zinc, iron, beta carotene, vitamin A1, vitamin A, vitamin C and sodium. There appears to be no comparable restaurant study in the developing world.<sup>2</sup> Second, to make the best use of these nutritional data and to overcome the limitations of current diet quality indicators, we propose a novel index called _Proportional Difference of Relative Nutrient Intake_ (PDRNI) index. This index computes the relative difference between the _real intake of nutrients per menu_ and the _recommended intake_ . The focus is on the restricted nutrients (fat, carbohydrates and sodium) that are most likely to contribute to body overweight if consumed above the recommended intake (Scheidt and Daniel 2004).

Third, in contrast to smaller-scale studies, we can assess the links among nutritional

> 2 The trade-off of having such detailed information at the restaurant level comes from not having individual-level consumption data.

3
VAT and excise taxes are slightly progressive for women, mainly because of VAT. The VAT concentration curve for women (Figures 6b) is ambiguously progressive because it crosses the market income Lorenz curve; excise taxes are mildly regressive. Indirect subsidies are regressive for both genders, mainly because the wheat subsidy is so regressive (Figures 6a and 6b). This suggests that, although the wheat subsidy is meant to improve the welfare of the poor through price controls, richer consumers capture more of the total subsidy. The kerosene subsidy is also relatively progressive.

**Figure 6a: Concentration Curves for Indirect Figure 6b: Concentration Curves for Indirect Taxes and Subsidies, Men Taxes and Subsidies, Women**

<!-- Start of picture text --> 100 100<br>90 90<br>80 80<br>70 70<br>60 60<br>50 50<br>40 40<br>30 30<br>20 20<br>10 10<br>0 0<br>0 10 20 30 40 50 60 70 80 90 100 0 10 20 30 40 50 60 70 80 90 100<br>Cumulative proportion of the population Cumulative proportion of the population<br>Market income Kerosene Market income Kerosene<br>Wheat VAT Wheat VAT<br>Excise Population share Excise Population share<br>Source : Authors’ calculations; ESS 2018/19 data. Source : Authors’ calculations; ESS 2018/19 data.<br>Cumulative proportion of indirect subsidies Cumulative proportion of indirect subsidies<br><!-- End of picture text -->

# _Education_

Public spending on education is progressive in relative terms. There is no difference by gender on progressivity.

Disaggregating the results by level of education, regardless of gender, spending on primary education has been found to be progressive (Figures 7a and 7b). Importantly, poor boys are benefiting relatively more than other boys, and primary education has dramatically reduced poverty for girls.
policies revealed through their use as being quantitatively important?<sup>1</sup> How were these TTB policies used and not used during the global economic crisis of 2008‐2009? What is the exporter‐incidence of such imposed policies and how has this changed over time?

In section 2 I first define and construct two new measures of annual, product‐level stocks and flows of imported products subject to these TTBs to address some of the main shortcomings of previous research. First, prior research has typically been unable to construct comprehensive estimates for how much of a country’s imports were subject to TTBs at any point in time. Examining the “stock” of such trade barriers in place over was previously difficult due to the lack of data on both policy removals and the details of which Harmonized System (HS) imported products the new and previously imposed TTBs were affecting. As such, previous work focused almost exclusively on industry‐defined data covering annual counts of the initiation of _new_ investigations and the imposition of _newly imposed_ barriers – “flow” variables that also lacked a normalized (economics‐based) definition for what constituted a “product.” My measures overcome these difficulties through application to new and detailed data drawn from the World Bank’s _Temporary Trade Barriers Database_ . As such, its builds upon prior work documenting the global proliferation of antidumping (AD) use in particular (Prusa, 2001; Zanardi, 2004).

My first result is that there is significant heterogeneity as to the potential economic impact that developed versus developing economy TTB policies have on their trade flows. Most striking is how the divergence between these two groups of policy‐imposing economies is taking place over time.<sup>2</sup> Even before the global economic shock of 2008‐2009, the annual stock of imported products subject to such trade barriers imposed by major emerging economies such as Argentina, Brazil, China, India and Turkey 1 There is also the possibility that such policies are important even
the perspective of a production-demand framework based on data from 1960 to 1980 see Schultz, T.P. 1988 "Expansion of public school expenditures and enrollments: inter-country evidence on the effects of income, prices, and population growth," Economics of Education Review 7(2): 167-83.

> 2 The bulk of the data pertains to 125 countries around 1993, the latest year for which data on the most of the indicators used in our study are currently available or can be constructed, supplemented by data for 1975 for a smaller set of indicators and countries. These data come from a larger time-series database prepared by the Institute de Recherche sur l'Economie de l'Education (IREDU), Universite de Bourgogne, Dijon, France. The raw data come from various sources, including international organizations (e.g. UNESCO, the World Bank, ILO, and OECD), published and unpublished country and comparative studies, and doctoral dissertations. Data for all the indicators have been checked for consistency in their relation to each other, as well as across time. Where published data contain obvious inconsistencies they are replaced by data for a nearby year, or by simulations based on related data. Since the database was created, new data have become available, but rather than attempt to incorporate them we have decided simply to use what is already available in it.
” _Environmental health perspectives_ , 2016, _124_ (3), 281–289.

- **Ghanem, Dalia and Junjie Zhang** , “‘Effortless Perfection:’Do Chinese cities manipulate air pollution data?,” _Journal of Environmental Economics and Management_ , 2014, _68_ (2), 203–225.

- **Gibson, John, Susan Olivia, and Geua Boe-Gibson** , “Night Lights in Economics: Sources and Uses,” _Etudes_<sup>_ ́_</sup> _et Documents_ , 2020, _1._

- **Gkatzelis, Georgios I, Jessica B Gilman, Steven S Brown, Henk Eskes, A Rita Gomes, Anne C Lange, Brian C McDonald, Jeff Peischl, Andreas Petzold, Chelsea R Thompson et al.** , “The global impacts of COVID-19 lockdowns on urban air pollution: A critical review and recommendations,” _Elementa: Science of the Anthropocene_ , 2021, _9_ (1).

- **Goolsbee, Austan and Chad Syverson** , “Fear, lockdown, and diversion: Comparing drivers of pandemic economic decline 2020,” _Journal of Public Economics_ , 2021, _193_ , 104311.

- **Gourinchas, Pierre-Olivier, Thomas Philippon, and Dimitri Vayanos** , “The analytics of the Greek crisis,” _NBER Macroeconomics Annual_ , 2017, _31_ (1), 1–81.

- **Hamilton, James D** , “Why You Should Never Use the Hodrick-Prescott Filter,” _Review of Economics and Statistics_ , 2018, _100_ (5), 831–843.

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<!-- Start of picture text --> SERVICES < > ACTION/BEHAVIOR<br>al<br><q<br>s<br>oe<br>°<br>a<br>’<br>a=<br>z<br>9u<br><!-- End of picture text --> <!-- Start of picture text --> circle size by population served<br><!-- End of picture text --> <!-- Start of picture text --> SERVICES < > ACTION/BEHAVIOR<br>|<br>4<br>=<br>«<br>°<br>u<br><al<br>=<br>5ir<br>circle size by population served<br><!-- End of picture text -->
- _Firm Performance_ :  How do skills and skill deficits impact firm performance?  What do production function estimates reveal about the returns to employer investments in capital and different labor skill groups, and the effectiveness of alternative strategies to mitigate skill deficits?

- _Skills Supply_ :  How do employers assess the supply of graduates from higher education and TVET institutions, how responsive are education and training providers to the skills demands of employers, and what policy implications follow from these insights?

The remainder of this study is organized as follows. Section II provides a broad overview of the education level of the population of Tanzania and employers’ views of the adequacy of education and training for their workforce. Section III describes the data source and outlines the analytic framework used to address policy concerns regarding formal sector enterprise skills in Tanzania. It describes the key variables elicited in the Tanzania Enterprise Skills Survey and how they are used in the empirical implementation of the analyses. Section IV reports the regression analyses on the determinants of employer choices about skills mix, skill deficits and strategies to mitigate them, and their impacts on labor productivity. Section V reports on qualitative survey findings on where firms source their workforce and training programs. Section VI describes the policy implications that emerge from these results.

4