rafmacalaba/data-use-mentions-extended huggingface dataset:
Facilitate Movement of Traded Goods and Services**

Physical and digital connectivity and infrastructure and other measures facilitating trade flows at the border or behind help lower trade costs, thus facilitating the movement of traded goods and services and lowering effective distance to key markets. High transport costs remain key obstacles to GVC participation, according to surveys of developing country suppliers (OECD and WTO, 2013). Other findings suggest that unpredictable land transport hinders most Sub-Saharan African countries from participating in the electronics GVC (Christ and Ferrantino, 2011). Better infrastructure – including communication, electricity, roads, and power – and GVC participation in manufacturing are positively associated (Cheng et al., 2015).

Estimates of the ad valorem equivalent of transit delays highlight the huge potential for connectivity improvements to reduce trade costs. One day of delay in transit due to a different transport mode choice has an ad valorem equivalent of 0.6 to 2.1 percent, with trade in parts and components being the most sensitive (Hummels and Schaur, 2013). Similar magnitudes for the cost of a one-day delay in inland transit are suggested by Djankov, Freund, and Pham (2010). Similarly, research finds that logistics performance matters more strongly for trade in parts and components than for trade in final goods (Ansón et al., 2017).

Improving trade facilitation by streamlining border procedures boosts trade integration by lowering trade costs. Estimates suggest that one third of the observed increase in GVC trade—which focuses on the role of intermediates—over the 2015 to 2019 period can be attributed to improvements in trade facilitation (Shepherd 2022). These improvements focused on increased implementation of the WTO Agreement on Trade Facilitation, emphasizing the potential to move forward on trade facilitation measures in order to promote access to imported intermediates.

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towns far from urban centers. Figure 2 shows the geographic distributions of the natural cities with WBES firms. India alone contributes 8,100 firms, or 37% of the total sample, which were distributed across 207 natural cities.

Finally, an international ranking of universities and academic disciplines or majors is used to examine the relationship between firms’ propensity to undertake innovative activities and the presence of high quality universities and underlying academic disciplines. Specifically, the list of top 500 universities in Asia from the recent QS Asia University Rankings (QS 2019a) publication are mapped to natural cities.<sup>16</sup> Of the 500 top Asian universities, 248 are mapped into 99 natural cities. A dummy indicating the presence of top Asian university is set to 1 for these cities and 0 for the rest.

Unfortunately, the QS rankings of top Asian universities does not provide information on their majors and which ones contributed to their high ranking. To get a sense of the role that different majors might play in any linkages between universities and firms’ innovation, information from the QS ranking of universities around the world across five broad areas of study (QS World University Rankings by Subject; QS 2019b) is used.<sup>17</sup> The five areas are arts and humanities, engineering, life sciences, natural sciences, and social sciences and management. This global ranking is used to create dummies for the presence in our cities of universities with a top (globally) ranked major across the five areas. If the city has one or more universities ranked within the top 500 in a major study area, the corresponding dummy is equal to 1.

As may be expected, having a university with a top ranked major globally makes it very likely that a university is also be in the list of top Asian universities. Indeed, with the exception of eight Indian universities located in 6 natural cities, all other Asian universities included in the list of universities with a top major(s) globally are
45 Zhou, N., Hubacek, K., & Roberts, M. (2015a). Analysis of spatial patterns of urban growth across South Asia using DMSP-OLS nighttime lights data. _Applied Geography_ , _63_ , 292–303. https://doi.org/10.1016/j.apgeog.2015.06.016 Zhou, Y., Smith, S. J., Zhao, K., Imhoff, M., Thomson, A., Bond-Lamberty, B., ... Elvidge, C. D. (2015b). A global map of urban extent from nightlights. _Environmental Research Letters_ , _10_ (5), 54011. https://doi.org/10.1088/1748-9326/10/5/054011
total economic costs of smoking (Goodchild, Nargis, and Tursan d’Espaignet 2018). This study reports on a comparative analysis of the distributional impact of raising taxes on tobacco products in eight countries: Bangladesh, Bosnia and Herzegovina, Chile, Indonesia, Moldova, South Africa, the Russian Federation, and Ukraine.

This is a first attempt to carry out a cross-country comparative analysis on the distributional welfare effects of tobacco taxation using household consumption microdata and including a sample of eight countries. The study applies a standardized extended cost-benefit analysis (ECBA), and, to aim for methodological consistency, it relies on the same sources of data across the sample.<sup>2</sup> In line with the findings in the literature, the ECBA methodology allows for differentiated behavioral responses to the price changes in tobacco by examining decile-specific price elasticities of demand. It accounts for both the direct price shock on household budgets and the indirect welfare gains of rising cigarette prices, as the improved health outcomes derived from reduced smoking translate into lower medical expenses and fewer premature deaths among workers. Finally, it simulates medium-, upper-, and lower-bound elasticity scenarios to account for shorter- and longer-term consumption changes and welfare effects.

The results show that, in the short run, the direct price shock negatively affects lower-income households more than the more well-off peers. In most countries, this regressive effect is driven

> 2 The World Bank has published country-specific studies on the distributional incidence of tobacco taxation (see Fuchs and Del Carmen 2018; Fuchs, Del Carmen, and Genoni 2018; Fuchs, Del Carmen, and Mukong 2018; Fuchs and Matytsin 2018; Fuchs and Meneses 2017a, 2017b, 2018; Fuchs, Orlic, and Cancho 2019). However, these studies rely on country-specific data sources with some methodological variation.

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particularly among disadvantaged students – given the prevalence of false, deter-

> 4 The pre-registered analysis plan in the AEA RCT Registry is: Arias et al. (2017). "Can Grit be Taught? Learning from a field experiment with middle school students in FYR Macedonia." https://doi.org/10.1257/rct.2094-1.0.

> 5 Disadvantaged students, whether by income, gender, race, or ethnicity, often experience higher-than-average challenges and stress in academic settings compared to their peers (Schmader, 2010; Beilock et al., 2007; Murphy et al., 2007; Ben-Zeev et al., 2005; Steele and Aronson, 1995). As a result, the decline in grades that is generally true for all students in transition periods (in our case, the start of sixth grade in middle school) is more pronounced for students from disadvantaged backgrounds (Gutman et al., 2003).

> 6 See, for example, Sturman and Zappala-Piemme (2017).

> 7 See, for instance, Gopnik (2020) as well as Cote and Erickson (2015).

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from a survey designed and implemented in 2017; and, (iii) spatially disaggregated daily temperature and precipitation data from Indian Meteorological Department.

Each of these data sources is described below with additional details offered in Appendix 2.

# _2.1 Electricity consumption and prices data_

Administrative cycle-level billing data for residential consumers were collected directly from JVVNL. The data set contains a unique billing code identifier which is used to match households across survey and administrative data sets. The administrative data provides information on the total energy consumed during the billing cycle, the calendar dates on which the meter was read, the total energy charges and fixed charges, electricity duties, subsidies, and other charges included in the bill. However, it does not record the tier of the IBT schedule corresponding to the monthly consumption and the corresponding marginal price of electricity. These are backed out by calculating the energy price implicit

> 10 JVVNL is one of the three electricity distribution companies in Rajasthan. JVVNL serves approximately 40 percent of total demand for power in Rajasthan. The entire state of Rajasthan is divided into three distinct service areas which are served by each utility. As geographic areas are demarcated across utilities, there is no retail competition across utilities.

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# **I. Introduction**

Since 2000/01, the NISR (National Institute of Statistics of Rwanda) has conducted five rounds of the Integrated Household Living Conditions Surveys (EICV surveys), with which the poverty trend has been monitored officially. The poverty estimation methodology used in the first three rounds of EICV (EICV1, EICV2, and EICV3) was modified when estimating poverty rates for the fourth round of the survey, EICV4 (see NISR 2015 for details). Due to the methodological change, there has been a debate around the poverty trend between EICV3 and EICV4.

According to the NISR statistics published in 2015, the incidence of poverty declined between EICV3 (2010/11) and EICV4 (2013/14). That said, some researchers, like Reyntjens (2015), argue against it, claiming that poverty had been stagnant or even increased during this period. NISR reviewed these claims and published a detailed report in the following year, NISR (2016), whereby the declining poverty trend was corroborated using global best practices. Nevertheless, the debate continued, and unfounded claims about stagnation in poverty were published in online blogposts and media websites, creating confusion and muddying the primary purpose of welfare estimation and poverty monitoring, limiting timely and relevant policy making. This paper is an attempt to provide theoretical and empirical evidence to help take the next steps in resolving this ongoing debate.

To do this, we first describe the official poverty estimation methodology used in EICV3 and EICV4 in section II. Section III examines the comparability of these estimates using a detailed theoretical framework, which provides the ‘necessary’ conditions for making robust poverty comparisons over time. Applying the framework to EICV data shows a decline in poverty based on the international poverty line. Section IV discusses the poverty trend based on the international poverty line of $1.90 per day per capita. Section V discusses the importance of the various price indices used to arrive at comparable poverty estimates, and section VI revisits the debate on the poverty
# From Survey to Big Data: The New Logistics Performance Index

Jean-François Arvis, Daria Ulybina, and Christina Wiederer<sup>1</sup> JEL: F10, R40

> 1 The authors are all in the World Bank’s <mark>Trade and Regional Integration Unit (</mark> **<mark>ETIRI</mark>** <mark>) and</mark> can be reached at <u>jarvis1@worldbank.org, dulybina@worldbank.org, cwiederer@worldbank.org.</u>
leader if they were currently in a leadership position within the ejido – i.e., they were in one of the main elected positions of president, secretary, treasurer, or oversight committee. Surveyors asked first to speak with the president, but if the president was absent, they would speak with his designated representative. Community leaders are accustomed to such interactions and generally have systems in place for other council members to stand in for the president when necessary.

For the household survey, 10 households were randomly selected to be interviewed for the pro11
2004 to 2013 (Figure 2c). These monitoring boreholes belong to a network of some 1,250 monitoring wells across the entire country that have been managed by the Bangladesh Water Development Board (BWDB) since the early 1960s. We estimated depth to mean dry-season groundwater levels (i.e., maximum depth below ground level) using the ground surface as a reference level.

# **2.4 Demography, access to water supply, and social vulnerabilities**

Demographic data sets on population, poverty, tubewells, and access to pipe water supplies in Bangladesh at the upazila level are collated from a GIS database ( _The Bangladesh Interactive Poverty Maps_ ) published by the World Bank (2016). The country-level demographic database allows one to explore and visualize socioeconomic data at both Zila (district) and Upazila (subdistrict) level. The online GIS-based mapping tool enables an easy access to different types of indicators including poverty, demographics of the population, children’s health and nutrition, education, employment, and household access to energy, water, and sanitation services (World Bank, 2016). These maps (see maps in supplementary Figure S1) were constructed by combining three different data sources all of which are publicly available: (i) 2010 Bangladesh Poverty Maps, (ii) 2011 Bangladesh Census of Population and Housing, and (iii) 2012 Undernutrition Maps of Bangladesh (BBS/WFP/IFAD, 2012). Children’s health and nutrition data sets were produced by the World Food Programme (WFP) and are constructed based on data from the Child and Mother Nutrition Survey of Bangladesh 2012 (MICS) and the Health and Morbidity Status Survey 2011 (HMSS).

Upazila-level total population and percentage of poor population (i.e. percentage of the population that lives below the official national upper poverty line, which is based on household's poverty status assessed using per capita consumption) are shown in Figure S1. According to the 2011 National Population Census, conducted by the Bangladesh Bureau
by introducing a calorific-based approach to tackle the limitations of the existing literature. Instead of traditional weight-based measures such as metric tons or kilograms, we convert annual crop production into calorific content and subsequently aggregate the production and yield of all food commodities into single metrics. This aggregation accounts for heterogenous yield patterns due to changes in production composition, the transition from low-yield to high-yield crops and varieties as well as shifts in country and regional significance. Additionally, this approach provides an easy-to-implement, yet standardized and universal framework for analyzing and comparing yield growth at any level, from individual crops to commodity groups to global aggregates.

Using these calorific-based indices, we apply statistical methods to select the most appropriate model for charting the yield paths of commodities at global, regional, and crop-group levels. Production and calorific content data for 144 major crops covering the 1961-2021 period from the Food and Agriculture Organization (FAO) are included in the analysis. These crops combined account for approximately 98 percent of the world’s agricultural land area. The evidence suggests that the aggregate global yield index has not been subjected to growth deceleration over the past six decades. Thus, slow growth in certain commodities, regions, or countries, documented in the literature has been offset by accelerated growth in others.

The remainder of the paper proceeds as follows. The next section summarizes the literature on yield growth. Section 3 discusses the aggregate yield index, the modeling framework for evaluating yield growth, and the data. Section 4 presents the results. The last section concludes and discusses avenues for further research.

# **2. A Brief Review of Literature**

The literature assessing yield growth performance can be broadly delineated into three principal strands. One strand delves into yield growth from experimental data, serving as a tool for plant scientists to discern performance nuances and facilitate the selection of crop varieties (Crow 1998; Kiær et al. 2009; Reiss and Drinkwater 2018). The second strand focuses on evaluating the statistical distribution of yields, with the explicit objective of assisting
- Lancaster, Tony and Andrew Chesher (1983). An Econometric Analysis of Reservation Wages. _Econometrica_ , 51, pp. 1661-76.

- Le Barbanchon, Thomas, Roland Rathelot, and Alexandra Roulet. (2019). Unemployment Insurance and Reservation Wages: Evidence from Administrative Data. _Journal of Public Economics_ , DOI: 10.1016/j.jpubeco.2017.05.002

- Maani, S.A., and A.H. Studemund (1986). The Critical Wage, Unemployment Duration, and Wage Expectations: The Case of Chile. _Industrial and Labor Relations Review,_ 39(2), pp. 264–276.

- Petreski, B. and Davalos, J. (2019) Analysis of youth underemployment in North Macedonia, Montenegro and Serbia. PEP Working Paper. Forthcoming.

- Petreski, M. (2019) Remittances and labour supply revisited: New evidence from the Macedonian behavioural tax and benefit microsimulation model. _Migration Letters_ . Forthcoming.

- Prasad, Eswar E. (2003). What Determines the Reservation Wages of Unemployed Workers? New Evidence from German Micro Data. IZA DP No. 694.

- Schmieder, Johannes F, Till von Wachter, and Stefan Bender, (2016). The Effect of Unemployment Benefits and Nonemployment Durations on Wages. _The American Economic Review_ , 106(3), pp. 739-77.

- Shimer, Robert and Iván Werning, (2007). Reservation Wages and Unemployment Insurance. _The Quarterly Journal of Economics_ , 122(3), pp. 1145-1185.

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type of infrastructure or a relatively narrow range of infrastructure indicators, we consider a wider range of infrastructures (altogether 13 types of infrastructures). We group them into three categories – physical, social, and financial – infrastructure. Each of them is represented by an index that is built using principal component analysis (PCA) over annual stocks of relevant infrastructures. The physical infrastructure index includes road, rail, power, and telecommunication indicators. The social infrastructure index includes education and health infrastructure indicators. The financial infrastructure index covers access to finance and financial institutions. We use the latest panel cointegration and GMM systems to account for state-specific heterogeneity and endogeneity and empirically examine the potential factors determining these three types of infrastructure indices across states. The possible factors include economic factors (e.g., gross regional products or GRP and the ratio of gross capital formation to GRP), financial factors (e.g., interest rate, yields on bond markets, foreign direct investment, etc.), demographic and cultural factors (e.g., population density, cast structures, rate of urbanization, etc.), political/institutional factors (e.g., alignment 3
Assessing the cost effectiveness of the _Jefes_ program requires comparing the program costs to the value associated with the income redistribution under the program.

_PROBECAT program in Mexico_ : Revenga, Riboud, Tan (1994) evaluate the effects of shortterm vocational training in Mexico provided by the PROBECAT program, which was offered to more than 250,000 unemployed people. Program participants were selected according to an eligibility index that gave weight to factors such as the number of economic dependents, whether the individual attained a basic level of education, whether the individual was unemployed for less than 3 months, and prior work experience. Also, to be eligible, individuals had to be within the age range of 20 and 55 and be registered at the unemployment office. The impact analysis is based on longitudinal data on PROBECAT trainees combined with a separate dataset on a control group of unemployed people who did not join PROBECAT, drawn from national labor force surveys, which survey individuals for 5 quarters. Women were 49% of the trainee group but only 33.8% of the comparison group. The average female trainee was 29 years old and 46% were married. Women were less likely than men to have completed secondary education (grades 10-12).

The key outcomes analyzed in the study are employment, monthly salary, and number of hours worked. Impacts of the program on the length of unemployment spells are assessed using a Cox proportional hazards model, estimated on the treatment group and on a subgroup of controls predicted to have a high probability of participating in the program based on their characteristics. Potential drawbacks of the analysis are that participants and controls were given different surveys, so that measurements across surveys may not be comparable, and the control sample was relatively small. On average, program trainees found jobs more quickly (program participation reduced unemployment spell by 1.9 months for females and 2.5 months for males). Subgroup analyses reveal that the positive program impacts in terms of shortening unemployment spells were concentrated on trainees older than 25 and those with
in employment, based on data from the 2015 Turkish Household Labor Force Survey.<sup>10</sup> We also collected vacancy information from newspapers and online job portals for a period of 3 months, and we filter out occupations that tend to recruit explicitly one gender (e.g., administrative assistants).

Second, we select occupations that have a large pool of vacancies in the online job portal: the four occupational clusters that we select represent around 65 percent of the total vacancy ads in the online job portal for the selected locations.

Finally, we aim to select clusters that use different socioemotional skills in their daily tasks, based on the classifications in O*NET and the organizational psychology literature. More information on this aspect is given in Section 2.2.

# _Job vacancies_

We collect the vacancy ads and make our applications using the largest online job portal in Turkey, which has around 75,000 registered companies and 24 million CVs.

We use two criteria for selecting vacancies. The first criterion is that the minimum required work experience did not exceed 3 years. We focus on early-career candidates because socioemotional skills, especially in the form of extracurricular activities, are arguably more salient in CVs for early-career candidates. On the other hand, for more mature candidates, aspects of job experience (such as tenure, progression, and gaps in work history) may be strong signs of socioemotional skills that make other signals less salient but that are harder to manipulate in an audit study experiment.

The second criterion in vacancy selection is minimum required level of education. Here, we mostly focus on higher-skilled jobs that require a university degree. However, for vacancies in the sales cluster, we also apply for jobs that would consider candidates with high school degrees.

In addition, we took into account whether we have recently applied to a job with the same employer. If this is the case, in order to avoid detection, we wait at least 4 weeks until we apply to another job with this
yield growth patterns at the global, regional, and commodity levels. These patterns are discussed in the following sections.

# **3. Methods and Data**

Indices have been used in several contexts within commodity markets, such as the aggregation of various commodity prices into a single index and the construction of aggregate agricultural productivity indices. A critical issue in the aggregation process is the selection of appropriate weights. For instance, the weights used in the World Bank’s commodity price indices are based on the export values of emerging markets and developing economies (World Bank 2024). For agricultural productivity studies, weights are typically based on values derived from FAO international crop prices, measured in Geary-Khamis dollars per ton, also known as “international dollars” (Prasada Rao 1993). Numerous studies have employed FAO-based aggregation, including Adamopoulos and Restuccia _— 5 —_