rafmacalaba/data-use-mentions-extended huggingface dataset:
|||Manufacturing|
||Annual<br>Manufacturing|||Annual<br>Manufacturing|82-86 to 94-98|Emp. ≥ 10||
|Colombia|survey (EAM)|82-98|Emp.≥10|survey (EAM)|||Manufacturing|
||||Emp ≥ 1|Business register|95-00 to 96-01|Emp ≥ 1|All|
|Estonia|Business Register|95-01||||||
||Fiscal register|||Fiscal register|92-96 to 97-01|Emp>1|All|
|Hungary|<br>(APEH)|92-01|Emp ≥1|<br>(APEH)||||
||Manufacturing|||Manufacturing|90-95|Emp. ≥ 10||
|Indonesia|survey|90-95|Emp.≥10|survey|||Manufacturing|
|||83-93 (3|||88 & 93|Emp ≥ 5|Manufacturing|
|Korea(Rep.)|Census|<br>years)|Emp ≥5|Census||||
|Latvia|Business register|96-02|Emp ≥ 1|Business register|96-01 97-02|Emp ≥ 1|All|
|Mexico|Social security|85-01|Emp ≥1||||All|
|Romania|Business register|92-01|Emp ≥ 1|Business register|95-98 to 96-99|Emp ≥ 1|All|
||||||92-97 to 97-01|Emp>1|All|
|Slovenia|Business register|92-01|Emp ≥1|Business register||||
|||86-91 (2|||86-91 to 91-96|Emp ≥ 1|Manufacturing|
|Taiwan(China)|Census|<br>years)|Emp ≥1|Census||||
||Annual Industrial||Emp ≥ 15, sample|<br>Annual Industrial|<br>95-99 to 96-00|Emp ≥ 5||
percent in upper part.

**Future Work:** Potential areas for future work in understanding the importance of gender in the labor market include:

- **<u>Identifying the sources of the unobserved portion of wage gaps.</u>** To improve wage equity, particularly as education attainment rates converge, it is necessary to better understand those factors that cause persistent wage gaps.  Labor market data that are commonly collected are not sufficient, since they do not include information on the most likely causes of the observed gap:  differences in actual, as opposed the generally measured potential level of labor market experience, differential accumulation of human capital due to differential school experiences, the role of household responsibilities, occupational choice decisions, labor turnover, differential preferences by gender, skill obsolescence and employer preferences, to name a few.

- **<u>The role of the informal sector</u>** <u>.  The differential participation rates in these sectors begs the</u> question of whether the attractive characteristics of informal sector work for women can be (or need be) replicated in the monitored and more protected formal sector.  This requires a better understanding of the motivation for informal sector work – an area that sociologists have much to teach economists

- **<u>Labor legislation.</u>** There is virtually no discussion of the incentives created for employees and employers via labor legislation.  However, anecdotal evidence suggests that sex-specific labor legislation actually creates incentives to discriminate against women (with parallel, but much fewer, distortions for men).  A more careful consideration of the laws in order to even the cost between male and female workers, could improve equity in labor markets.

25
**Table 13.2 Explaining Social Norms – Males only sample**

||(1)|(2)|(3)|(4)|(5)|
|---|---|---|---|---|---|
||**PNB Index -**<br>**HH Roles**|**PNB Index -**<br>**Public Space**|**SNE Index -**<br>**HH Roles**|**SNE Index -**<br>**Public Space**|**Sanctions**<br>**Index**|
|Respondent’s age in years,|0.00|0.00|0.00|-0.00*|-0.00|
|squared|(0.00)|(0.00)|(0.00)|(0.00)|(0.00)|
|Years of education, derived from|-0.00|-0.01|0.00|-0.02* (0.01)|-0.05|
|education level|(0.01)|(0.01)|(0.01)||(0.03)|
|Indicator for respondent having|-0.01|0.10* (0.06)|-0.04|0.01|0.40|
|childyounger than 5years|(0.02)||(0.04)|(0.06)|(0.33)|
|Respondent lives in urban area|-0.01|-0.01|-0.09|-0.06|-0.96*|
||(0.05)|(
429,688|<br>88,037,289|||
|**Ungheni**|48,112,320|69,825,832|83,891,369|155,504,589|||
|**ATU Gagauzia**|78,529,620|96,334,319|144,924,656|198,653,872|||
|<br>**Total **|**3,271,928,674 **|**3,024,556,233**|**2,546,498,882 **|**4,263,943,313**|**709,864,711**|**803,200,975**|

Notes: * - allocated at the national level Source: authors’ calculations using Moldova BOOST data.

# **3. Methods, data, and key modeling assumptions**

# **3.1. Construction of the main income concepts**

This paper employs the CEQ framework for fiscal incidence analysis to evaluate the impact of fiscal policy on poverty and inequality in Moldova. In order to do this, the methodology requires allocating taxes and benefits (both cash and in-kind) to individuals from a representative sample of the population in a household survey (here, the Household Budget Survey for 2017), such that one can compare incomes before taxes and transfers with incomes after taxes and transfers (Lustig, 2018) and (Figure 5). Because for each separate income concept it is possible to compute statistics such as the poverty rate, or inequality indices, comparisons across different income concepts thus allow for an assessment of marginal contributions of individual taxes and expenditure programs to poverty and inequality alleviation. In addition, because each program and tax is allocated to households in the survey sample, this also allows for insight into the incidence of various taxes and programs across different population groups
<!-- Start of picture text --> Figure 4: Mean Survival Time based on Fixed Costs by Sector<br>Construction<br>Retail<br>Other Services<br>Manufacturing of Food and Beverages<br>Manufacturing of Metals and Fabricated Metal Products<br>Other Manufacturing<br>Manufacturing of Textiles, Apparel, and Leather Products<br>Manufacturing of Machinery, Computing, and Electrical ...<br>Manufacturing of Chemical, Plastic, and Mineral Products<br><!-- End of picture text --> <!-- Start of picture text --> 16 20 24<br>Weeks<br><!-- End of picture text --> <!-- Start of picture text --> 28 32 36 40<br><!-- End of picture text --> <!-- Start of picture text --> 0 4 8 12<br><!-- End of picture text --> <!-- Start of picture text --> Note : Data is extracted from the World Bank Enterprise Surveys. Number of Observations: 6,345<br><!-- End of picture text --> _Note_ : Data is extracted from the World Bank Enterprise Surveys. Number of Observations: 6,345 The differences across countries between the average and median survival time persist (Figure 5). While the median business in Turkey is estimated to run out of cash in 9 weeks, businesses on average have the means to survive for about 20 weeks, or nearly twice as long. Results for other countries are more similar: in both Kazakhstan and Ukraine the median and the average firm will run out of cash in about 10 weeks.

<!-- Start of picture text --> Figure 5: Mean Survival Time based on Fixed Costs by Country<br><!-- End of picture text -->

*
growth. Second, we also consider that economic institutions are endogenous, and that institutional change depends on the economic interests of those groups with political power. Third, we take from their work the notion that the degree of power of the ruling groups depends on the internal consistency of the group and the resources on which their power is based. AJR (2001, 2002) use the colonialist experience of 70 developing countries to show the importance of institutions for economic development. They show that these institutions have been persistent over the last centuries, originally formed by the colonial power who established settler colonies with broad-based market-oriented institutions or extractive colonies with institutions aimed at extracting natural resources and subjecting the populations, depending on natural conditions encountered by the original colonizers. They also show that colonization was an exogenous shock to these societies, which actually led to a reversal in economic development in many countries (AJR, 2002). Similarly, we conjecture that the transition in the early 1990s was an exogenous event, which led to a change in the economic paradigm. As extensively discussed in the literature, there was a rapid destruction of institutions that served to support socialism; the building of new institutions, however, was a much slower process, and, as we will discuss in the following section, a disparate process across the different transition economies, which were subject to the same (or at least a similar) institutional framework during socialism.

# _2. Measuring Institution Building_

Figure 1 shows the disparity in institution building across the 24 transition economies in our sample. We use an indicator compiled by EBRD that averages scores for enterprise reforms, competition policy, banking sector reform and reform of non-banking financial institutions, with values between one and four. While not an indicator of institution development, this variable 15
# **2.2 The Upper Secondary Education System in Mexico**

Mexico, like other middle-income countries, has reached almost universal enrollment rates in primary and lower secondary (grades 7 to 9), but its education system still faces important challenges, especially in high school (grades 10, 11 and 12). For instance, more than 35 of every 100 students who enroll in high school will never graduate. Among those who graduated from high school in 2015, more than half got insufficient achievement levels in math according to the national standardized test, PLANEA. Many of the students dropping out or finishing high school but with insufficient skills come from poor or marginalized households, replicating or even exacerbating existing inequalities. Therefore, upper secondary education dropouts and low achievement levels have important implications for Mexico's long-term economic growth and income disparities.

The upper secondary education or “educación media superior (EMS)” system in Mexico has 4.9 million students, typically between 15 and 18 years old, in grades 10th, 11th and 12th. EMS is offered by four different providers: 1) the federal government (accounting for 21.8 percent of total enrollment), 2) the state governments (47.4 percent), 3) publicly-financed autonomous universities (12.3 percent), and 4) private schools. EMS offers three types of degree programs: general, which prepares students for higher education; technological preparing students both for the labor market and higher education; and technical, which emphasizes technical and vocational education.

According to official statistics from the National Institute for the Evaluation of Education (Instituto Nacional para la Evaluación de la Educación, INEE) in 2015, only 67.3 percent of students graduated on time, usually three years after enrolling in EMS. On-time graduation rates vary across types of degree programs, with general schools showing the highest rate (69.2 percent), followed by technological schools with rates very close to the national average (67 percent) and technical schools
owned businesses, and their relatively higher (compared to male-owned firms) returns from producing or selling under contract and from security payments have narrowed the productivity gap. It is important to note that a sizeable portion of the productivity gap is explained by the location fixed effects or is unexplained by the covariates in the data.

The study builds on the few others that have explored gender gaps in labor productivity among informal firms. Many of these studies have documented gender gaps in informal firms in rural areas (Nagler and Naude, 2017; Rijkers and Costa, 2012). In contrast, this study examines informal firms in largely urban areas. Nagler and Naude (2017) use household enterprise data in rural areas for four Sub-Saharan African economies - Ethiopia, Malawi, Nigeria, and Uganda and find that enterprises owned by women are less productive than those owned by men. Rijkers and Costa (2012) similarly find gender gaps for rural informal enterprises in Ethiopia, Bangladesh, Indonesia, and Sri Lanka. However, with the addition of control variables, half the gender gap disappears in Ethiopia, and no gender gap is observed in Bangladesh and Sri Lanka. Some studies are also region-specific. Bruhn (2009) explores the gender gap in productivity in 9 economies in Latin America and the Caribbean, with 3 economies - Mexico, Peru and Bolivia including data on informal firms. The study finds that female-owned micro and small enterprises are less productive than male-owned enterprises in Mexico (9 percent) and Peru (16 percent) but not in Bolivia. Hallward-Driemeier (2013) explores the gender gap in 19 Sub-Saharan African economies using enterprise modules of various labor force surveys as well as surveys of micro-enterprises that are assumed to be all informal. The study finds that female-owned enterprises are 50 percent less productive than male-owned enterprises. The corresponding gap is 6 percent for the formal sector, implying that the gender gap may be much larger in the informal than formal sector. However, the gender gap in the informal sector narrows considerably after including controls. Finally,
2|1.9|2.1|
|Senegal|3.7|3.6|3.7|3.7|3.5|3.6|3.7|3.7|
|Sierra Leone|4.5|9.1|4.6|4.9|13.2|5.2|4.5|4.6|
|South Africa|5.3|5.2|5.3|7.3|6.0|6.6|5.5|5.1|
|Swaziland|9.5|9.1|9.3|13.9|10.9|11.9|9.7|9.0|
|Tanzania|3.0|3.3|3.1|1.9|5.8|3.1|3.4|2.9|
|Togo|3.1|3.1|3.1|3.6|3.3|3.5|3.1|3.1|
|Uganda|2.4|1.9|2.4|—|3.6|3.6|2.6|2.3|
|Zambia|5.4|6.3|5.5|8.3|5.4|7.8|5.7|5.4|
|Median|3.3|3.0|3.1|3.7|3.4|3.6|3.3|3.1|

_Source_ : World Bank staff calculations using household survey data. _Note_ : Only households with positive expenditures on electricity are analyzed. In Ghana, South Africa, Uganda, and Zambia, freely provided electricity is excluded. — = No households with positive cash expenditures on electricity.

Because the amount of cash available is an
, Bustos, and Ponticelli, 2023; Acevedo et al., 2023; Rude and Robayo-Abril, 2023; Aguilar-Gomez et al., 2022). However, there is a lack of comprehensive understanding regarding climate risk in the overall region in the present context. We contribute to addressing this gap by choosing various natural hazards across different countries in the region. The paper's main contribution is the analysis of vulnerable households' coping and adaptation mechanisms at the micro-level.

The paper is structured as follows. The next section presents the conceptual framework and the methodology. Section 3 describes the data, and section 4 presents the results. Section 5 summarizes the main findings and presents a final discussion.

# **2. Measuring vulnerability to poverty including natural hazards in LAC**

# **Methodology**

Building on the definition of vulnerability, we propose a model to measure vulnerability to poverty, including natural disasters and exposure in the region. Although a household's vulnerability is an ex-ante condition and not directly observable until the adverse shock occurs (Ravallion, 1988; Chaudhuri, 2003), it is possible to summarize it as the probability of the household's welfare falling below a minimum standard in the future.

> 2 Hurricanes are a type of tropical cyclones in the Atlantic Ocean. From now on, we will refer to cyclones instead of hurricanes to follow the terminology of the aggregate natural hazard datasets used in the analysis. Following, ThinkHazard! methodology, cyclones, tropical storms, hurricanes, and typhoons, despite their distinct names, all describe the same hazard: a non-frontal storm system characterized by a low-pressure center, spiral rain bands, and strong winds. Thus, we decide to use the term cyclones to encompass a broader scope of this hazard.

4
the arrival of tourists.

Using a comprehensive list of determinants, the empirical analysis reveals that STP can do better in terms of the number of tourist arrivals, but it has a good performance in terms of expenditures per tourist. Using a hedonic model of tourist arrivals and expenditures per tourist, STP has a lower number of tourists in 2016 than what would be otherwise predicted with the model, but spending by tourists is larger than what the model finds.

The empirical analysis confirms the importance of improving air connectivity in the island. STP can receive more tourists because it has a low ratio of tourists-to-population and land area, however, flight demand meets supply as measured by seats sold on incoming flights. Therefore, the country needs to increase air connectivity. STP ranks low in centrality indexes in networks using flight data. Its major flight origin is Lisbon, which means that many of the European tourists need to fly to Lisbon first. As connections reduce utility and propensity to spend at the destinations, STP might benefit greatly from having connections to central hubs. A simple exercise simulating a connection to London reveals major changes in centrality. The tourism elasticity with respect to the seat availability on the flights is of the order of 0.1.

17
Before discussing some conceptual principles guiding the definition of the deprivation mapping (see Section 3.2), we present in the remainder of section 3.1 what this mapping looks like in our illustration.

Table 1 defines our deprivation mappings for the baseline and preferred designs. Consider first our baseline design. We begin with the monetary dimension. In Nigeria, the monetary aggregate is defined as the market value of consumption. In 2019, the national poverty line was $1.93 per person per day in 2011 PPPs (see page 19 of World Bank, 2022b). The national monetary line was thus almost equal to the World Bank’s extreme poverty line, which is $1.9 per person per day (2011 PPPs). The deprivation mapping for the baseline design assumes that an individual is extremely monetary deprived if her consumption is below the national poverty line, otherwise she is not monetary deprived. Given that an extreme deprivation automatically confers (multidimensional) poverty status, this assumption is equivalent to the one used by the WB’s MPM, which automatically classify as (multidimensionally) poor individuals who are below the extreme monetary line.

We succinctly describe the non-monetary deprivations used in the baseline design. In the health dimension, individuals are extremely deprived in three cases: they suffer from a heavy disability, they are an underweight woman between 15 and 49 years old (age-window and gender for which we have data) or they are a stunted child.<sup>1</sup> In turn, individuals who are not extremely health deprived are moderately health deprived in two cases: they suffer from a mild disability, or they suffer from severe over-weight (obesity). In the security dimension, an individual is extremely security deprived if her household has been victim of an insecurity event with “physical” consequences or if she lives in a district where at least a quarter of the households have been victim of an insecurity event with “physical” consequences. In turn, an individual who is
|17.5|7.7|4.4|7.9|6.1|6.2|6.0|10.2|34.1|13.1|8.1|13.6|10.0|15.4|12.2|
|OPEC-12|12.1|9.8|13.1|7.7|5.4|7.8|5.8|5.8|5.7|8.2|19.0|8.7|7.5|15.0|13.0|17.2|13.3|
|WTO-50|16.4|13.5|17.7|8.2|5.4|8.3|5.2|4.9|5.6|10.7|23.7|10.4|9.8|14.7|13.1|16.4|12.9|

Note: The product categories are defined as BEC on food & beverages in Section 1 where food primary (111) and food processed (112); industrial products in Section 2 where industrial primary (221) and industrial processed (222); capital goods in Section 4 where capital goods (441) and parts & accessories (442); transport equipment in Section 5 where automobiles (551), other transport equipment (552), and parts & accessories (553); consumer goods in Section 6 where durable goods (661), semi-durable (662), and non-durable (663). Data are based on the latest year available in applied rate from country.

Sources: UNCTAD TRAINS databases.

12
br>43%|<br>45%|43%|43%|<br>40%|
|Togo|30%|<br>26%|<br>23%|33%|<br>27%|<br>30%|54%|49%|<br>43%|
|Guinea|26%|<br>29%|<br>25%|27%|<br>25%|<br>23%|45%|44%|<br>37%|
|Benin|36%|<br>31%|<br>27%|45%|<br>36%|<br>37%|60%|59%|<br>59%|
|Kyrgyz Republic|25%|30%|31%|45%|45%|48%|54%|62%|66%|

We eventually chose WorldPop for our population layer. The computational process underlying the WorldPop data is fully transparent (Stevens et al., 2015), and the model is considered to be the most accurate and robust among the currently available data sets (World Bank, 2016). In addition, to maintain global comparability and methodological simplicity, we rely on the GRUMP (Global Rural-Urban Mapping Project) data set for urban-rural delimitation, as in (World Bank, 2016). Note that WorldPop uses roads as a factor to model population distribution, so there is an endogeneity in our analysis which could lead to an overestimation of rural accessibility. However, WorldPop is still the data set with the lowest concentration of population in rural areas and thus the one that gives the lowest rural accessibility in most countries (Table 1). These caveats call for high caution in the interpretation of the results presented here, and for further 3
valuation of attributes of cookstoves, including durability, fuel reduction, smoke reduction, and amount of time saved by using new clean, cooking technology. The overall goal of the survey was to determine features of clean cookstoves that were well-liked by communities in order to help implement sustainable cooking practices in rural Ethiopia, with the hopes of reducing the harmful health and environmental impacts of traditional cooking methods. We use the choice experiment survey on preferences for attributes of clean cookstoves conducted in Ethiopia in 2013 and repeated in 2016 to analyze the temporal stability of preferences.

The unique setting of having a repeated choice experiment and an RCT allows us to also study technology adoption and how preferences and willingness-to-pay for improved cookstoves evolve with use and experience. There is a large economics literature on technology adoption (see Marra et al. 2003 and Conley and Udry 2010) and a smaller but growing literature on adoption and learning with regard to cookstoves (see Ruiz-Mercado 2011 and Miller and Mobarak 2014).

At the same time, it has been found that the Mirt stoves save fuelwood (Gebreegziabher et al., 2018) and that it may reduce household air pollution (Bluffstone et al. 2018). Therefore, the second focus of this work is to evaluate the degree to which such experience with such outcomes causes users to shift their preferences and change their demand for attributes.

Therefore, our research questions become _Q1: Are the preferences for cookstoves elicited from choice experiments stable over time?_ _Q2: How do users’ preferences and willingness to pay for cookstove attributes evolve after extensive experience with the Mirt stoves?_ The combined RCT and repeated choice experiment setting allows us to use a difference-indifference framework to analyze the results from the choice experiment, the first instance of a difference-in-difference choice experiment analysis that we are aware of. We use the control group to evaluate stability of preferences and the treatment group to evaluate the degree to which experience with the Mirt stove shifted user preferences and attribute values.

Results show that the willingness to pay for stove attributes of