rafmacalaba/data-use-mentions-extended huggingface dataset:
These proxies allow us to differentiate two channels through which exposure to mass violence may influence fertility: replacement effects (where women choose to have children in the post-conflict period to compensate their lost children from during the conflict period) and marriage market effects (where a relative shortage of men to women creates a ‘bottleneck’ for women to get married). It is important to note that the conflict proxies do not necessarily identify victims of targeted genocidal violence. Rather, these proxies indicate individuals and age groups that were likely to be exposed to conflict-related violence. Given that the 1994 genocide occurred within a time span of just about 100 days, the duration or timing of conflict exposure is of less importance in the Rwandan genocide.
; William Jack and Tavneet Suri. 2019. "Fintech and Household Resilience to Shocks: Evidence from Digital Loans in Kenya." NBER Working Paper 25604.</mark> <mark>Blumenstock, Joshua; Callen, Michael; Ghani, Tarek. 2018. “Why Do Defaults Affect Behavior? Experimental Evidence from Afghanistan.”</mark> _<mark>American Economic Review</mark>_ <mark>108 (10): 2868-2901.</mark> Boston Consulting Group, 2019. “CICO Economics in Indonesia.” July 2019. https://connect.bcg.com/cicoeconomics/6-cico-economics-in-indonesia_aug-2019-2/ <mark>Breza, Emily; Kanz, Martin; Klapper, Leora. 2020. “Learning About a New Financial Technology: Evidence from Payroll Accounts.” World Bank Policy Research working paper XX.</mark> <mark>Brown, J. R., Cookson, J. A., & Heimer, R. Z. (2019). Growing up without finance.</mark> _<mark>Journal of Financial Economics, 134</mark>_ <mark>(3), 591-616.</mark> <mark>Burgess, R., & Pande, R. (2005). Do rural banks matter? Evidence from the Indian social banking experiment.</mark> _<mark>American Economic Review</mark>_ <mark>,</mark> _<mark>95</mark>_ <mark>(3), 780-795.</mark> <mark>Burlando, Alfredo, Mike Kuhn and Silvia Prina. 2021. "Too Fast, Too Furious? Digital Credit Speed and Repayment Rates." Working paper.</mark> <mark>Buri, Sinja; Cull, Robert; Gine, Xavier; Harten, Sven; Heitmann, Soren. 2018a. “Banking with Agents: Experimental Evidence from Senegal.” Policy Research
A natural consequence of these patterns is that host countries may end up with high concentrations of high‐skilled immigrants in particular occupations. For example, immigrants account for some 57 percent of scientists residing in Switzerland, 45 percent in Australia, and 38 percent in the United States (Franzoni et al. 2012). In the United States, 27 percent of all physicians and surgeons and over 35 percent of current medical residents were foreign born in 2010. Immigrants also accounted for over 35 percent of recent enrollments in STEM fields, with very high proportions in specific areas like Electrical Engineering (70 percent), Computer Science (63 percent) and Economics (55 percent) reported by Anderson (2013). In the United Kingdom in 2014, the _Guardian_ newspaper reported that the National Health Service (NHS), the world’s fifth largest employer, employed workers from some 200 countries worldwide and 26 percent of NHS doctors were not originally British citizens.<sup>6</sup> The global migration of inventors and the resulting concentration in a handful of countries have been particularly well documented. Kerr (2016) reviews the literature and we focus here on patent records taken from the World Intellectual Property Organization (WIPO) database. Miguelez and Fink (2013) calculate that the global migration rate of inventors in 2000 stood at 8.6 percent, at least 50 percent greater in share terms than the average for high‐skilled workers as a whole. Figure 4 builds on WIPO global patent filings from 2001‐2010. The United States has received an enormous net surplus of inventors from abroad, while China and India have been major source countries. Some countries like Canada and the United Kingdom are major destinations but still experience a negative net flow due to even larger emigration rates for inventors, usually to the United States.

Similarly striking levels of immigrant concentration are evident in sports, where global outliers in terms of talent and income are the norm. Spectators in the English Premier League, the most popular and profitable
may well create spatial poverty traps. Evidence of such poverty traps has been found in Southern China in areas across the border from Vietnam.<sup>24</sup> However, little is known about what role the institutional arrangements for social protection might play in fostering the conditions for spatial poverty traps.

In the future, local authorities and the mass organizations should have less discretion in defining who is poor. The advantages of decentralization come at a disadvantage of horizontal inequity. There is a clear tension here that the government must consider in designing the HEPR. One way to deal with this issue is by redistributing and ensuring correct allocations across areas based on standardized information about needs, performance, and outcomes. This requires a highly disaggregated national data base on indicators of living standards that is comparable over time and updated frequently. The collection of panel data-which follows the same households and communities over time-can be used to test and monitor the performance of interventions. Provided panel data exist, models are available for evaluating how well the safety net performs dynamically including how well it protects against poverty distinguished from how well it promotes out of poverty.<sup>25</sup> Information on who the poor are and monitoring of who makes claims, who receives benefits, levels of social relief disbursements and outcomes needs to be strengthened. Attention must be given to the design of rules for implementation at the local level, taking account of incentive effects while exploiting the greater capacity of local communities to know who is poor. The rules should be standardized nationally. In addition, criteria for eligibility should be transparent and widely publicized. Making the lists of selected beneficiaries public may then help to overcome political maneuvering.

27
Crump, Richard K., V. Joseph Hotz, Guido W. Imbens, and Oscar A. Mitnik, 2009, Dealing with Limited Overlap in Estimation of Average Treatment Effects, _Biometrika_ , 96: 187-199.

Cunha, F., J. J. Heckman, L. Lochner, and D. V. Masterov. 2006, Interpreting the Evidence on Life Cycle Skill Formation, In _Handbook of the Economics of Education_ , Volume 1, edited by E. A. Hanushek and F. Welch, 697-812, Elsevier, North-Holland, Amsterdam, Holland.

Glewwe, P. and M. Kremer, 2006, Schools, teachers, and education outcomes in developing countries, Ch.16, _Handbook of the Economics of Education_ , Vol.2, edited by E.A. Hanushek and F. Welch, Amsterdam: Elsevier B.V.

Jensen, R., 2010, The (perceived) returns to education and the demand for schooling, _Quarterly Journal of Economics_ , 125 : 515-548.

Hanushek, E.A., 2006, School Resources, Ch.14, _Handbook of the Economics of Education_ , Vol.2, edited by E.A. Hanushek and F. Welch, Amsterdam: Elsevier B.V.

Heckman, J., 1979, Sample Selection Bias as a Specification Error, _Econometrica_ 47: 153–61. Hirano, K. H., G. W. Imbens, and G. Ridder. 2003, Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score, _Econometrica_ 71: 1161-1189.

Hoxby, C., 2000, The Effects of Class Size on Student Achievement: New Evidence from Natural Population Variation, _Quarterly Journal of Economics_ , 116: 1239-1286.

Khattri, N., C. Ling, and S. Jha. 2010, The Effects of School-Based Management in the Philippines: An Initial Assessment Using Administrative Data, Policy Research Working Paper No. 5248, World Bank, Washington D.C.

Lanzona, Leonardo A., 1998
the parameters of our models to minimize prediction loss functions that balance false positives and false negatives. Depending on the use case, calibrated predictions can be generated that strike the appropriate balance between false positives and false negatives dictated by the application at hand. We acknowledge, however, that putting this principle into practice is a difficult task. While specifying a loss function that trades off false positives and false negatives is mathematically straightforward, setting the appropriate weights requires careful deliberation of the human and economic implications of competing errors, both of which are subject to considerable uncertainty.

Combined, the results show that statistical models can provide new and attractive forecasting capabilities in various ways, including an improved ability to detect new crisis outbreaks for a specified tolerance for raising (false) alarms; calibrating error types to take the costs and benefits of specific interventions into account; increasing lead time for preventive action by forecasting further into the future, and updating predictions continuously using readily-available, verifiable and open high-frequency data. Realizing these benefits will require close coordination between statistical modeling work and policy dialog, to ensure that the design of warning systems is tailored to the policies they are intended to inform.

20
and leading to effective transparency or effective market access (van der Marel and Shepherd, 2019).

In sum, the measures that would fall within an MNP TFiS agenda would be “(a) regulatory in nature..., targeting the operations of the services business as opposed to market entry across the board, and (b) go beyond the mere fact of transparency by effectively operationalizing it and by allowing stakeholders to obtain meaningful outcomes. One additional element in this respect is how regulatory procedures are mapped so that deficiencies can be prevented in the preparation, adoption and application of regulations (Molinuevo and Sáez, 2014). If the procedures for regulatory adoption and implementation are secured, it enhances the likelihood that policy makers improve the quality of the regulation and avoid any arbitrary modification of the administrative practise afterwards.” (van der Marel and Shepherd, 2019, op. cit.)

# **3. Regulatory barriers to Mode 4 trade**

In this section, we undertake an analysis of measures that seem excessively restrictive in their regulatory role as applicable to MNP and thus primarily constitute barriers to Mode 4 trade. The data on these Mode 4 measures, publicly available online, have been put together by the OECD for 45 countries as a part of their STRI database. These data include 27 measures (across 29 sectors and sub-sectors) of which 24 measures entail a Yes/No answer and the remaining three<sup>3</sup> measures include quantitative information. The information is available for the years 2014 to 2017, but given the coverage of issues and the non-variability in responses over time,

> 3 These pertain to limitations on duration of stay for (i) contractual service suppliers (CSSs); (ii) independent service suppliers (ISSs); and (iii) intra-corporate transferees (ICTs).

6
.0|7.9|X|6.1|4.8|
|Asia||2.6|1.1||7.5<br>|4.9||2.9|3.8|
|Latin America<br>Developmng<br>counity sampleg|,<br>jI,<br>V|2.4<br>2.2|1.5<br>1.2|**7**<br>2|<br>7.3<br>8.5|4.7<br>6.1|,|2.7<br>4.7|2.3<br>4.1|
|**OECD countries**|**25**|<br>2.9|1.9|i,|5.5|4 4|1|.71.6||
|Total sample|.|**2.5**|**1.5**||7.3|54||3.7|3.2|

_Source: Forearly 1980s Hellerand Tait, 1983;forearly 1990's Annex A-3, Annex A4._ _*Note that the datafor the early 1990's are limited to the Heller and Tait sample.They are therefore differentfrom those for the largersample in this stufdy. N represents the number of countries in the sample._

- Among developing regions, the reduction in relative government employment took place in Africa and Asia. In Asia, this reduction was partly offset by growth in local government. In LAC, an equally impressive reduction in central personnel is almost entirely explained by a vast shift from central to local government. In Africa, total government employment fell in the 1980s both relative to population and slightly in absolute terms;
# 4. Conclusion and Recommendations

**In this paper, we review existing energy poverty indicators in the academic literature, white papers, and policy reviews and then explore the employability of these indicators in Bulgaria's case.** Energy poverty is a complex concept that lacks a common definition and is multidimensional by nature. It involves multisectoral and multilevel approaches. Based on these factors, measuring energy poverty is complex, and there are many different approaches to its measurement. In the work at hand, we review existing approaches and then explore their applicability to the concept of Bulgaria based on data availability and quality.

**We show that Bulgaria's energy poverty incidence rate fluctuates significantly by definition.** The 10 percent measure deviates significantly from the other expenditure-based indicators, resulting in an approximately five times larger incidence rate. This could be related to the measurement issues and the criticism raised in the literature about this indicator. The rest of the monetary measures fluctuate between 9 and 13 percent. The incidence rates of consensual measures are slightly larger, varying between 11 and 47 percent.

**Our evidence demonstrates that the monetary poor and energy poor only partly overlap.**<sup>44</sup> By construction, the monetary poor are also energy poor in the low-income-high-cost measure. If they report energy expenditure shares above the national median, this is not necessarily true for the rest of the measures. We find that, depending on the measure, only 1 to 12 percent of the population is affected by monetary and energy poverty. This has important implications for the targeting of policy interventions. As the monetary and energy poor only overlap partly, traditional social protection strategies might not target those who are energy poor, and additional policy instruments should be implemented when governments try to tackle energy poverty.

**In addition, we show that different subsets of the population face different dimensions of energy poverty.** This means that the government might want to include a different population set for interventions that target
Policy Research Working Paper 7994

# **Abstract**

It is theoretically ambiguous whether growth of cities matters more to the rural poor than growth of towns. This paper empirically examines whether growth of India’s secondary towns or big cities mattered more to recent rural poverty reduction, noting that data deficiencies have made this a difficult question to answer previously. Satellite observations of night lights are used to measure urban growth on the extensive and intensive margins in the context of a spatial Durbin fixed-effects model of poverty measures for rural India, calibrated to a panel of 59 regions observed four times over 1993–2012. The expansion of lit area had greater effect on the rural poverty measures than did intensive margin growth in the brightness of light from urban areas. For India’s current stage of development, growth of secondary towns may do more to reduce rural poverty than big city growth, although the theoretical model suggests that cities may eventually take over from towns as the drivers of rural poverty reduction.

This paper is a product of the Poverty and Equity Global Practice Group. 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 rmurgai@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
(CSSs), independent service suppliers (ISSs) and intra-corporate transferees (ICTs). In addition to excessively restrictive regulation and heterogeneity in legal requirements and practices, these service suppliers are also constrained by “red tape” associated with the implementation of domestic tax and regulatory policies. In fact, both academic research and business surveys suggest that these associated costs may be a multiple of merchandise import tariffs without generating any revenue for the government and reflect a combination of the real resources that must be allocated to meet administrative requirements and the uncertainty and unpredictability associated with border clearance processes (Hoekman, 2016).

Apropos to Mode 4 trade, most of these associated costs center around different facets of applying for a business visa – the visa fees, the number of documents required, the visa processing times – as well as the lack of predictability and certainty associated with getting the visa, which is completely at the discretion of the visa officer. Immigration authorities have unfettered discretion to assess whether a service supplier falls into the committed definitional category. There is no predictability or certainty or objective criteria on the basis of which entry can be granted. Thus, while the existing low and shallow level of GATS commitments on Mode 4 trade is a concern in itself in terms of market access, a problem also lies in the implementation of these low and shallow commitments.

An additional problem for service suppliers accessing multiple markets is the heterogeneity in regulation, the most pressing example of which is the differences in the number and types of documents required to apply for a business visa (see Section 4 for details) or differences in 4
A detailed look into the task statements of green occupations detected through our dictionary and text analysis but not in the O*NET GEP confirms that these occupations have green task content, even those with the lowest GTI. For example, Home appliance repairers with a GTI of 3.2 have the task ‘ _conserve, recover, and recycle refrigerants used in cooling systems_ ’, or Real estate brokers with a GTI of 5.2 have tasks such as ‘ _review property details to ensure that environmental regulations are met’_ ’, or Molecular and cellular biologists with a GTI of 4.7 have a task ‘ _conduct applied research aimed at improvements in areas such as disease testing, crop quality, pharmaceuticals, and the harnessing of microbes to recycle waste_ ’.

# Reliability test #2: Correlation between the GTI and green skills intensity

Since relying on occupational classifications can be rather static because they are not constantly updated, the second reliability test compares the GTI against a similarly constructed green skills intensity index (GSI) after applying the text analysis methodology to an occupational skills database in the same country. The assumption is that green skills are needed to perform green tasks, and therefore the two indexes should be positively correlated. Recall that the green dictionary is not a list of tasks but of green terms, so the dictionary should be able to pick up skills containing green words. For example, the term ‘environmental’ can pick up the task ‘reporting on the environmental impact of existing and proposed construction’ in the task database and also the skill ‘environmental testing’ in the skills database. It is important to note that merely applying the dictionary to the skills database will not capture all the skills needed to perform a green job since these will be more comprehensive than just skills with green words.

This reliability test is carried for two countries: the U.S.—a high-income country with rich data—and Indonesia—a middle-income country with some data. For the U.S., we use
|741|741|741|741|741|731|
|Within R2|0.063|0.060|0.091|0.071|0.068|0.097|0.84|
|Unconditionalmean(wave1)|3.94|3.76|0.47|0.38|0.36|0.05|0.35|

Panel union fixed effect model estimates. Standard errors in parentheses are bootstrapped (300 replications); * p<0.12 * p<0.10, ** p<0.05, *** p<0.01.

Dependent variables: col (a): stock of savings of the wife (in log); col. (b): a dummy equal to one if wife has savings, col. (2) and (5) correspond to savings entrusted to informal or formal institutions, col. (3) and (6) to savings kept at home. In col. (7): Share of the total stock of savings entrusted to informal or formal institutions Sample: monogamous unions in the two waves. F;: predicted failure probability estimated by a Cox survival model stratified by the polygamy status of the husband’s father (see Table 1).

All regressions include union fixed-effects ? Controls not shown: time (in months) between the two survey waves and its square ? Controls not shown: time, time squared, dummies for the deceased father of each spouse, household size, relative cell size, share of dependents

* Controls not shown: time, time squared, dummies for the deceased father of each spouse, household size, relative cell size, share of dependents, all step-1 controls (see Table 1) interacted with time

In col. 7: we additionally control for the total level of savings in log Data source: PSF Survey, waves 1 and 2 (2006-2007 and 2010-2012)
from January 2015 in half-day sessions over a period of 15 to 20 days, so that entrepreneurs could complete the training while continuing to attend to their businesses.

From January to March 2016, approximately one year after the treatment group were offered the training, the research team resurveyed the 799 entrepreneurs. Follow-up I survey was conducted with 729 female entrepreneurs who were tracked out of the entrepreneurs already interviewed at baseline. An additional follow-up II survey for 726 entrepreneurs was administered in February-March 2017, approximately two years after the training. The panel of firms with data collected across the three survey rounds is 680 firms. The follow-up survey questionnaires elicited business performance, business practices plus additional entrepreneurial and psychological characteristics of the female business owners. The main results in this paper are an intention-to-treat (ITT) estimation, i.e. the impact of being offered training.

# **3.1.2** **_PI/BSED study_**

For the PI/BSED training experiment, the impact evaluation team drew upon the WEDP registration database of clients in Addis Ababa only and randomly assigned 2,001 women entrepreneurs to the different treatment arms. The research team randomly assigned WEDP clients into a treatment group who were offered the PI training (747), a treatment group who received BSED training (757) and a control group (497) who were not offered training for at least one year.<sup>7</sup> From the registered WEDP clients in Addis Ababa the research team excluded all those who were already part of the overall WEDP program impact evaluation and those who had reported that they already received some form of business training in the registration database. The research team randomly selected the original 2,000 names from the WEDP registration database in Addis Ababa using Stata in November 2015 when the random sampling for the experiment was initiated.

> 7 Since the survey firm faced issues with locating all the women in the original WEDP registration list, the survey firm was provided with replacement names and instructed to survey