rafmacalaba/data-use-mentions-extended huggingface dataset:
*|0.194 ***|0.533 ***|
||[0.04]|[0.13]|[0.06]|[0.15]|
|Y_2018 x Small|0.090 **|0.657 ***|0.102|0.533 ***|
||[0.03]|[0.14]|[0.07]|[0.15]|
|Y_2019 x Small|0.051 ***|0.706 ***|0.084 **|0.580 ***|
||[0.01]|[0.14]|[0.04]|[0.14]|
|Y2020 x Small|0.028***|0.733***|0.011|0.580***|
|_|<br>[0.01]|<br>[0.14]|[0.02]|<br>[0.13]|
|No. of observations|8,448|8,448|5,360|5,360|
|No. of clusters|53|53|44|44|
climatology input CHPclim outperformed other climatology data sets in data sparse regions and complex terrain (Funk et al., 2015). Furthermore, in an assessment of wet season statistics CHIRPS showed less bias than other rainfall sources and good correspondence with Global Precipitation Climatology Centre (GPCC) estimates.

Data and technical documentation are available for download from `https://data.chc.ucsb. edu/products/CHIRPS-2.0/` .

# **A.1.3 CPC Global Unified Gauge-Based Analysis of Daily Precipitation and Temperature**

NOAA’s Climate Prediction Center (CPC) Unified Gauge-based (CPC-U) data sets for daily temperature and precipitation do not incorporate remote sensing data in the estimation of weather variables. Instead, an optimal interpolation (OI) technique is used on gauge data for precipitation, and Shepard’s algorithm for temperature. CPC-U provides systematic global data sets for validation and climate monitoring. GTS is a primary input data source, with some national collections, but density is most sparse over Africa.

101
**MONGOLIA'S INFORMAL SECTOR** -

**Appendix B: Methodologies and Descriptive Statistics**

**37**

positive value. This suggests that the adjusted mode provides a clear upper bound for the percentage of vehicles that are never used as taxicabs. The mode, over the relevant range, comprises 14% of the adjusted population. Adjusting for the addition of the "zero" category, the predicted upper bound for the percentage of vehicles in Ulaanbaatar that are never used as taxicabs is 12%.89

# Value Added from Ulaanbaatar's Taxicabs

110. The Survey of Taxicabs sought to provide estimates of the average value added (earnings after subtracting the costs of fuel, garage, and repairs) when a vehicle is driven for a fixed period of time. Given that a large proportion of vehicles are used only infrequently as taxicabs, many drivers had difficulty estimating how much they would earn during an average eight-hour day, and instead provided answers for their typical day, regardless how many hours is in their typical day. We can therefore accept the sample average Tg 8,810 as a clear lower bound for the average value added for an average vehicle over an eight-hour day. Recognizing that full-time taxicabs are in a much better position to know the value added of driving continuously for an eight-hour day, it is believed that a better estimate of the average value added for an eight-hour day is Tg 13,100.

111. Having estimated the distribution of the frequency with which vehicles in Ulaanbaatar are used as taxicabs, and having estimated the value added by a typical taxicab on a typical day, we can estimate the total value added of taxicabs in Ulaanbaatar by finding the product of the number of automobiles in Ulaanbaatar, the percentage that are ever used as taxicabs, average hourly value added, and adjusted average number of hours used as a taxicab in a week. Multiplying this product by 52 weeks per year, yields a conservative estimate of 21.8 billion togrogs value added per year at current
1.5 times the poverty line.

Roberts, Sander, and Tiwari (2019) highlight the importance of classifying urban areas based on their functionality instead of mere population size in Indonesia. Following Duranton (2015), we defined the following four location categories: (1) _metro core_ , which stands for Jakarta or a district with the highest population density for other metros; (2) _urban peripheries_ , which are predominantly urban non-core districts; (3) _other urban areas_ that account for single-district metro (predominantly urban with _kotas)_ or non-metro urban (predominantly urban non-metro districts); and (4) _rural areas_ , which encompass the rural periphery (predominantly rural non-core district) or non-metro rural areas (predominantly rural non-metro districts).

# **Climate data: Flood risk index and SPEI**

To account for climatic and environmental shocks, we used two indicators: flood risk index and the SPEI. Those climatic variables are prepared at the subdistrict level.

The primary climatic stressor analyzed in this study is flood risk, given its potential threat to urban livelihoods. To capture the flood risk, we used the flood depth data provided by FATHOM in 2016. The flood depth is expressed in meters and computed <mark>at 3 arc-second (approximately 90 m) resolution and has a global coverage between 56°S and 60°N.</mark> The computation is based on pluvial data with a return period of 100 years (1-in-100 flood depth).<sup>6</sup> The 1-in-100 flood depth means <mark>a flood event that has a 1 percent probability of occurring in any given year w</mark> ithin 100 years. We classified the areas

> 4 Nonfood expenditures include household amenities (for example, refrigerator, TV, and telephone); housing; assorted items such as clothing, furniture, medical, ceremonies, education (tuition, uniform, transportation, boarding); and others. Regarding the housing expenditure, the actual monthly rent paid was
want to design and understand the impact of public policies on socio-economic well-being. For example, the World Bank uses household and individual characteristics from HBSs to prepare profiles of the poor, or estimate the bottom 40 percent at country, regional, and global levels. These individual and household characteristics are harmonized to enable crosscountry analyses and are used in all World Bank flagship reports on poverty, shared prosperity, and economic mobility, and in different briefs.<sup>6</sup>

> 6 For example, the World Bank produces regular Poverty and Shared Prosperity reports, which provide a global audience the latest and most accurate estimates on trends in global poverty and shared prosperity. The reports also provide in-depth research into policies and interventions that can make a difference for the world’s poorest. The World Bank also produces bi-annual Country Poverty and Equity Briefs (PEBs), which highlight poverty, shared prosperity, and inequality trends, and provides the context of poverty and equity conditions in more than 100 countries.

4
# _Pollution from Agricultural Chemicals_

The indiscriminate use of agricultural chemicals, such as fertilizers and pesticides, has contaminated ground- and surface water. Excess nutrient loading as a result of fertilizer run-off can lead to uncontrolled algae growth. Pesticide run-off has caused an increase in the numbers of dead fish (especially on the banks of the Kabul River in certain seasons). Pesticide residues are of particular concern because they are assimilated into the environment at a slow rate, and accumulate in fish and animal tissue. Increased intensities of nitrates in groundwater wells are converted into more toxic nitrites in the stomachs of adults and infants, and are known to cause blood disorders in infants. Other risks from agricultural chemicals include contamination of shallow wells used for drinking water in villages and cities, and pesticide residues on grain and vegetables products in markets.

Agricultural chemical use in Pakistan's irrigated agriculture has expanded rapidly over the past twenty years. The most serious agricultural chemical problem stem from the rapid increase in pesticide use, from less than 1,000 tons in 1980 to more than 20,000 tons in 1993. The most commonly used pesticide is insecticide, most of which is applied to the cotton crop. Pesticide use was initially stimulated by subsidies, discontinued in 1985, and by a major government and private sector campaign to induce small cotton farmers to use pesticides in the wake of the pest epidemic of 1983.

The widespread use of often dangerous pesticides on the cotton crop is associated with several potential health hazards, including contamination of workers who apply it (three quarters of producers use a back-pack sprayer and no protective clothing), harvesters (all of whom are women), soil and groundwater used for drinking, and consumers of agricultural products. Very few data are available to document the extent of these various health hazards. Jabbara and Mallick (1994) summarized evidence from blood tests that shows that as many of one third of cotton workers in Pakistan have been exposed to dangerous levels of pesticides. Other studies have noted unacceptable levels of pesticide residues
**Table 2. Results of the adjusted delta test**

||**G**<br>**Delta**|**asoline**<br>**p-value**|**C**<br>**Delta**|**oal**<br>**p-value**|**D**<br>**Delta**|**iesel**<br>**p-value**|
|---|---|---|---|---|---|---|
|**Unadjusted**|14.099|0.000|13.676|0.000|14.933|0.000|
|**Adjusted**|17.145|0.000|16.431|0.000|18.174|0.000|

_Source:_ Based on the adjusted delta test of Pesaran and Yamagata 2008 Next, we proceed by determining the order of integration for each variable. Variables are said to be integrated of order _d_ when they become covariance-stationary after taking _d_ differences of former observations. In simple terms, _covariance stationarity_ implies that the time series has finite moments over time; for example, the mean does not eventually diverge to infinity. Without this condition, it is likely that we need to account for regression coefficients becoming biased due to spurious correlation; for example, we may find a positive correlation due to two variables experiencing growth at the same time when there is no underlying relationship. Depending on the cross-sectional dependency (CD) structure within a panel data, we can use either first- or second-generation unit root tests for this. First-generation tests are appropriate under cross-sectional independence; otherwise, secondgeneration tests are appropriate. We determine which generation to use via Pesaran’s (2004) CD test. As one might expect with macroeconomic variables, cross-sectional
# **Introduction**

Pakistan is the fifth largest country in the world by population and home to over 53 million children under the age of eight (Pakistan Bureau of Statistics, 2017). Twenty million children are out of school (Ersado et al., 2023) and 77% of 10-year-olds are estimated to be unable to read and understand a simple, age-appropriate paragraph (World Bank, processed). Yet, little is known about young children’s school readiness or about the quality of their earliest educational experiences.

This study aims to fill this knowledge gap and documents the skills pre-primary-aged children can demonstrate and the quality of the classrooms they attend in South Punjab, Pakistan. The Punjab province is home to over half of the country’s population but there is widespread variation across the province in human development outcomes. As shown in **Table 1** , data from the most recent Multiple Indicator Cluster Surveys (MICS) study show that enrollment in early childhood education is far lower in South Punjab (27% of children enrolled) than in the rest of the province (36% of children enrolled) (Bureau of Statistics Punjab, Planning & Development Board, Government of the Punjab & UNICEF, 2018). Not surprisingly, the share of children developmentally on track is also markedly different – 52% of 3 and 4 year olds are reported by their parents as developmentally on track in South Punjab compared to 63% of children in the rest of the province (Bureau of Statistics Punjab, Planning & Development Board, Government of the Punjab & UNICEF, 2018).

_Table 1. Share of 3 to 4-year-old Children Enrolled in ECE and Share Reported to be Developmentally on Track_

||**%**<br>Mean|**Enrolled in ECE**<br>95% Confidence Interval|**% De**<br>Mean|**velopmentally on Track**<br>95% Confidence Interval|
|---|--
Fuller, B. 1985. Raising School Quality in D0velopinx Countries: **What** Investments Boost Learning? Washingtont World Bank, Education and Training Series, *EDT17.

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**Figure 2.12. The gender wage gap has decreased 10 percentage points since 2009.**

Average employees real wages, 2009-2019 <!-- Start of picture text --> 1,200,000 84%<br>82%<br> 1,000,000<br>80%<br> 800,000<br>78%<br> 600,000 76%<br>74%<br> 400,000<br>72%<br> 200,000<br>70%<br> - 68%<br>2009 2014 2019<br>Male Female Cambodia Gender wage gap<br>Gender gap women/men<br>Real Wages KHR 2019-2020 prices<br><!-- End of picture text -->

**Source:** Authors’ elaboration using data the CSES household survey.

**Figure 2.13. Agricultural and nonagricultural wages almost tripled between 2009-2019.**

Average real wages, 2009-2019 <!-- Start of picture text --> 1,200,000<br> 1,000,000<br> 800,000<br> 600,000<br> 400,000<br> 200,000<br> -<br>Agricultural wage Non-Agricultural<br>wages<br>2009 2014 2019<br>Real wages KHR 2019-2020 prices<br><!-- End of picture text -->

**Source:** Authors’ elaboration using data the CSES household survey.

Gender segmentation across sectors persists. Women remain employed in agricultural activities more than men. In 2019, men were more likely than women to work in construction (14.8% versus 1.3%), trade (10.7% versus 1.2%) and transportation (8.5% versus 1.0%). Men also show greater participation in public administration (5.2
to low-skilled positions (World Bank, 2019a). Finally, because online job advertisement is carried out by both private and public providers, even among online vacancies the true number and characteristics of posted jobs are not known. Kureková et al. (2015) stress that vacancies tend to occur in the presence of an unfulfilled demand or where employers have preferences for a selection process. Therefore, online vacancies are useful to learn about jobs for which employers face difficulties to fill through internal or informal search channels.<sup>15</sup> To examine which segments of the labor market are observed on job portals, we contrast findings from our vacancy analysis with other evidence from the Kosovar labor market using labor force survey data in Section V.<sup>16</sup> Despite their limitations, job portal data are a complement to other available data, especially to understand which profiles are in demand. For instance, Labor Force Surveys (LFS) are useful to analyze overall variations in employment across sectors and age groups, but these data have limitations in reliably and timely estimating job creation and the characteristics of jobs currently created. More importantly, LFS data reflect the stock of available skills in the labor force, while job postings directly express employer needs and the skills in demand.

> 14 World Bank calculation based on LFS 2017. Informality is defined here as workers without a labor/employment contract (legal definition in Kosovo).

> 15 Anecdotal evidence from counterparty discussions suggests that this is increasingly true in Pristina, the capital city of Kosovo.

> 16 The 2017 LFS is used to compare the characteristics of jobs on the portals with the characteristics of employment in the economy. STEP Employer survey data (World Bank, 2019a) are used to contrast our findings on skills.

- 9 -
We study performance on the EHEECE, the exam that directly determines eligibility for college or university.

In recent years, Ethiopia has embarked on a rapid expansion of access to education across all tiers through construction of primary and secondary schools as well as universities. The Ministry of Education reports that from 2000 to 2021-22, the number of primary schools increased from 11,780 to 36,492 and secondary schools from 424 to 3,636.<sup>5</sup> These expansions have also led to a gradual increase in the education access rate of female students from 20% in 2003/04 to 34% in 2017/18. The scale up of tertiary education is equally impressive, with the number of public universities increasing from 2 to 42 in the last two decades. Besides expanding access, the construction of new schools is also aimed at rectifying regional inequities in access to higher education institutions. Despite these efforts to expand access to education by building new schools, little attention is paid to equipping existing and new schools with air conditioning (AC) systems to regulate classroom temperatures. Fewer than 8% schools have any kind of climate control (World Bank Group,

> 4Many U.S. colleges, for example, require applicants from Ethiopia to submit scores on the EHEECE as part of their application. 5

> We refer to reports ESAA 2014 EC (2021-22 G.C) Final and ESSA 2003 EC retrieved from: https:// moe.gov.et/EduStat.

4
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- **Field, Erica M., Rohini Pande, Natalia Rigol
24 collected, we observe only a fraction of the citations that the patents will eventually receive. Older patents clearly would have less of a truncation problem, namely because they would have had the opportunity to receive a higher fraction of the total number of eventual citations, whereas the truncation problem is more severe for the more recent patents. Another possible source of bias with patent citation data is that the number of citations received by any one patent tends to increase or decrease with the total number of new patents being granted. In the case of utility patents, the number of patents granted has been steadily increasing since the late 1970s, and there is even a sharp increase toward the end of the 1990s. This would imply that the number of patent citations received would tend to be larger the more recent the specific year we are looking at.

Our data on the annual number of patent citations received by USPTO utility patents were constructed from data on individual utility patents obtained from Hall, Jaffe and Trajtenberg (2002). It spans the period 1975 and 1999.

# **Published Scientific and Technical Journal Articles**

Another measure of domestic innovation is the annual number of scientific and technical journal articles published by the residents of a specific country. The scientific and technical fields include the following: physics, biology, chemistry, mathematics, clinical medicine, biomedical research, engineering and technology, and earth and space sciences. While this indicator does measure domestic innovative activity, its does not focus only those innovations that have commercial value and thus economic production. Data on scientific and technical journal articles were obtained from the World Bank World Development Indicators.

# **Royalty Payments and Receipts**

Royalty and license fees are payments and receipts between residents and nonresidents for the authorized use of intangible, nonproduced, nonfinancial assets and proprietary rights (such as patents, copyrights, trademarks, industrial processes, and franchises) and for the use, through licensing agreements, of produced originals of prototypes (such as manuscripts and films). As such
.2 Firm heterogeneity

Models of monopolistic competition with ...rms of heterogeneous productivity predict selection into export markets in the presence of ...xed costs of trade. The reason is that the least productive ...rms do not generate pro...ts su¢ cient to cover the ...xed costs incurred, preventing entry into overseas markets. As illustrated by HMR, this has at least two further implications. First, the impact of a change in a trade barrier a¤ects both the amount a given ...rm exports, the intensive margin, and the number of ...rms that export, the extensive margin. The latter is a ...rm selection e¤ect. ‘Traditional’gravity equations con‡ate these two e¤ects, whereas HMR’s method allows for their decomposition. Second, for ...xed costs su¢ ciently high, no ...rms in a given country may ...nd it pro...table to export to a particular destination. This is o¤ered as an explanation of the ‘zeros’observed in bilateral trade data: many country-pairs do not appear to trade at all. This is a country selection e¤ect, and it induces bias in traditional gravity estimates. HMR propose a two stage estimation procedure to construct controls for both of these e¤ects. In the procedure described below, we use the elements of their approach that allow us to control for the e¤ects of ...rm heterogeneity and simultaneously account for MR using the Baier & Bergstrand (2009,

> country than a large country” (p. 177).

> 3 Furthermore, this method is especially demanding when considering about 100 countries and allowing for asymmetries in trade frictions. Bergstrand, Egger & Larch (2007) have shown that the system solution can yield complex numbers.

6