rafmacalaba/data-use-mentions-extended huggingface dataset:
.

The twin crises are likely to have impacted households across Iraq through different transmission channels. Even for households directly affected by the war against IS, the welfare of those displaced, their hosting communities, and those left behind will all be affected differently.

On one hand, the consumption of IDPs could have been reduced by a decrease in the quality or flow of services received from housing as well as the loss of immobile durable goods and assets. Additionally, among the displaced, those previously employed in the private sector will have almost certainly lost their jobs and livelihoods. In contrast, IDPs who held public sector jobs have in general continued to receive their salaries and pensions.

For families left behind and still living in the IS‐ affected governorates of Anbar, Nineveh, and Salahadin, anecdotal evidence and discussions in country suggest that their access to services, Public Distribution System (PDS) and other public transfers has been disrupted, and that distorted markets have led to a local increase in prices. Moreover, their labor income might have also been reduced because of the economic disruptions, the security situation, and because of ‘taxation’ by Islamic State. All of these households including the IDPs could also have suffered from a reduction in their private transfers

> 3 Source: IOM‐OIM DTM Data January to December 25, 2014.

> 4 Kurdistan region comprises of the three governorates of Erbil, Sulaimaniya and Duhouk. Based on official governorate boundaries, approximately 800,000 IDPs have moved to KR‐I. If districts under de facto KR‐I administration are included (in particular the IDP camps in Nineveh administered by the Duhouk governorate), the number increases to 1 million. This influx represents a significant addition to Kurdistan’s 5 million people.

2
country where crime is more or less severe. If these distributions of crime severity are correlated with the ethnic distributions of defendants and plaintiffs, then we may again falsely perceive in-group bias.

The rest of this section proceeds as follows. Subsection 4.1 presents the qualitative justification that judge assignment is as good as random (at least in the most recent years). Subsections 4.2 and 4.3 present quantitative evidence through balance tests that the random assignment assumption does in fact hold across the full time period for both gender and ethnicity, respectively. The econometric approaches for examining gender and ethnic in-group bias are described in detail in subsections 4.4 and 4.5, respectively. We also aim to examine whether judge gender slant in written opinions is correlated with outcomes for female defendants and plaintiffs. The approaches to these analyses are described in subsection 4.6. Finally, subsection 4.7 presents the specifications for examining the relationship between in-group bias and textual variables other than slant, for both gender and ethnicity.

# **4.1 Random Assignment of Cases to Judges**

To evaluate the existence of in-group bias, we exploit the quasi-random assignment of cases to judges. In Kenyan High Courts, cases filed in a court are categorized by court type and sent to the deputy registrar of the relevant court division (family, commercial and admiralty, labour and employment, constitutional, land and environment, or criminal). The deputy registrar then assigns the case to a judge based on the judge’s caseload and calendar, without considering case characteristics. This exogenous assignment is orthogonal to case characteristics such as the gender or ethnicity of the parties. Thus, this system produces as-good-asrandom assignment of plaintiffs and defendants to judges, conditional on court division. This is consistent with the World Bank Doing Business’ Index, which asserts that cases are in fact randomly assigned to judges in Kenya (World Bank 2021). Nonetheless, it must be noted that this randomized procedure may be a recent phenomenon.
workers. Although these new laws have been in place for ten and seven years, respectively, migrant participation remains low. The 2015 wave of the Rural-Urban Migration in China survey (RUMiC), for example, indicates that only 30 percent of migrant workers were enrolled in urban health insurance or pension programs.

What explains the slow progress in expanding migrant participation in urban social insurance programs? Earlier research has highlighted the following contributing factors: poor incentives for local governments to enforce laws, the possibility that employers try to avoid making contributions to employee social insurance accounts, and the lack of enthusiasm among migrants for participation, which may be due to the fragmented nature of the system and consequent lack of geographic portability of enterprise contributions (Meng and Manning, 2010; Meng, 2012; Giles et al., 2013; Gallagher et al., 2014). Posessing little or no prior experience with urban employee social insurance schemes, China’s migrants may lack full understanding of the potential benefits from enrollment and participation in these programs.<sup>2</sup> More importantly, given the complexity of the social insurance schemes (the costs, benefits, as well as enrollment procedures), which vary across regions and by type of job, migrants may find it difficult to maneuver through these complications and simply decide against participation.<sup>3</sup> Lack of knowledge about the benefits and costs of insurance or inability to figure out how to enroll may then interact with strong employer preferences for avoiding contributions to generate the current low levels of participation.

This paper exploits a field experiment to assess the extent to which lack of information about urban employee health insurance and pension programs contributes to low participation among rural migrants. The study utilizes the existing Rural-Urban Migration in China (RUMiC) longitudinal survey and a random selection of approximately 35% of respondents from the 2015 survey round who were provided detailed information regarding the costs and future benefits of participating in the health insurance and pension programs available in their respective cities.
, F. Dom ́ınguez-Castro, V. Slonosky, J. Cooper, M. Brunet, and S. Br ̈onnimann (2023). The global historical climate database HCLIM. _Scientific Data 10_ (1), 44.

- Maccini, S. and D. Yang (2009). Under the weather: Health, schooling, and economic consequences of early-life rainfall. _American Economic Review 99_ (3), 1006–26.

26
only sees part of the total benefit of training. Unless investment decisions are coordinated and decided jointly, inefficient levels of investment may arise. Furthermore, information problems and uncertainty in this investment in human capital may lead firms to invest small amounts in training even though the ex post average return is high. Even though under our current set up we cannot distinguish how much of the variability in returns across firms is due to heterogeneity and how much is due to uncertainty (as in, for example, Carneiro, Hansen and Heckman, 2003), we find an enormous dispersion in the ex post returns to training which may be suggestive of the importance of uncertainty. For example, in our base specification the 5th percentile of the distribution of internal rates of return is -16% and the 95% percentile is 66%. Finally, it is possible that firms would like to invest more in their workers but they are unable to do so because they are constrained (e.g., credit constrained). In that case, investments in training are likely to be suboptimal. Unfortunately we cannot verify empirically the importance of each of these different hypotheses.

# 5. Conclusion

In this paper we estimate the internal rate of return of firm investments in human capital. We use a census of large manufacturing firms in Portugal between 1995 and 1999 with unusually detailed information on investments in training, its costs, and several firm characteristics. Our parameter of interest is the return to training for employers and employees as a whole, irrespective of how these returns are shared between these two parties.

We document the empirical importance of adequately accounting for the costs of training when computing the return to firm investments in human capital. In particular, unlike 20
relevant and the average document length is well-over 20 pages.

10 The Basel Core Principles for Effective Bank Supervision are generally subdivided into 7 areas, (i) Objectives, autonomy powers and resources (BCP 1.1-1.6), (ii) Licensing and structure (BCP 2-5) (iii) Prudential regulations and requirements (BCP 6-15) (iv) Methods of on-going supervision (BCP 16-20) (v) Information requirements (BCP 21) (vi) Remedial measures and exit (BCP 22) (vii) Cross border banking (BCP 23-25)..

11 A counter argument is that Basel I is only intended for “internationally active banks” and hence may be considered to go beyond what would be required under the capital adequacy assessment for the BCPs. However, if Basel I is the minimum for larger, more diversified institutions, then in the context of a developing country, it seems reasonable that it should also be considered a minimum for smaller and more concentrated institutions. Many developing countries have implemented Basel I for all banks and, with stricter limits, reflecting this view. This is evident analyzing the World Bank, bank regulation database available on www.worldbank.org.

8
1.05|-0.44|
|IV|24.2|-0.43|-0.23|
|V|13.9|-0.12|-0.03|

_Source:_ Staff estimate from MOPH data.

_Restructuring User Fees._ The combination of recent worsening income distribution, reduced government health spending and price decontrols (resulting in higher prices for health care and other consumable) reduced utilization of health services, consequently worsening their health status particularly in poor provinces. The government is concerned about cushioning the poorest of the poor from further higher health costs stemming from changing age pattern of diseases and greater cost recovery in public health sector. Indeed, better targeting of public expenditure to improve access of the poorest to health facilities would depend on two policy instruments: reducing user costs associated with treatment and drugs, and improving the quality of care for those who actually gain access.

- 4The implied GDP elasticity of provincial government health expenditures varies from a low of -0.098 for Guizhou, the poorest province in China, to a high of 2.56 for Shanghai, the richest province.
a matched employer-employee data set covering all the plants operating in Portugal between 1985 and 1994. This data has worker level information on total labor costs per employee supported by the plant and on the schooling and experience of the plant’s workforce. I find strong evidence of MAR externalities and no effect of Porter or Jacobs externalities when pooling all the manufacturing sectors together. The results for the sector regressions show that concentration fosters employment growth in some sectors<sup>6</sup> . Sector competition and sector diversity have no effect on productivity growth in most of the manufacturing sectors<sup>7</sup> . Furthermore, my findings show that the results for productivity growth

> 4 One exception is Gao (2003) that finds no evidence that concentration fosters industry growth in China. However, he uses output growth has a measure of productivity growth.

> 5 They assume that the firm technology is Cobb-Douglas and estimate total factor productivity growth by obtaining an estimate for the Solow residual.

> 6 For food, beverages and tabacco, non-metalic and mineral products and basic metals there is evidence that concentration fosters productivity growth.

> 7 The only exceptions is chemicals, where local competition fosters productivity growth and non-metalic and mineral

4
**Figure 3.   Growth incidence curve for the share of villages with ICDS program, 1992-1998**

<!-- Start of picture text --> All India All India<br>7 7<br>6 6<br>5 5<br>4 4<br>3 3<br>2 2<br>0 10 20 30 40 50 60 70 80 90 100 0 10 20 30 40 50 60 70 80 90 100<br>w ealth percentile (All India) w ealth percentile (by state)<br>Poor Northern States Rich Northern states<br>8 8<br>7 7<br>6 6<br>5 5<br>4 4<br>3 3<br>2 2<br>1 1<br>0 0<br>-1 -1<br>-2 -2<br>0 10 20 30 40 50 60 70 80 90 100 0 10 20 30 40 50 60 70 80 90 100<br>w ealth percentile w ealth percentile<br>Southern states North Eastern States<br>8 8<br>7 7<br>6 6<br>5 5<br>4 4<br>3 3<br>2 2<br>1 1<br>0 0<br>-1 -1<br>-2 -2<br>0 10 20 30 40 50 60 70 80 90 100 0 10 20 30 40 50 60 70 80 90 100<br>w ealth percentile w ealth percentile<br>annual growth rate, %<br>annual growth rate, %<br>annual growth rate, %<br><!-- End of picture text --> _Source_ : NFHS I and II.

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<!-- Start of picture text --> »<br>0°- \ > ;<br>K View:<br>4 riety<br>10°S- Pret of Small occurrence<br>e ts, = ih mind S/ region<br>a’ a " x Top 5 count<br>ee es Q f Other count<br>aoe by Maca Ly . NA<br>~<br>70°W 6o°w 50°w 40°W 30°W<br><!-- End of picture text --> To summarize, the Brazil case illustrates the potential of the GBIF database for identifying protection opportunities offered by spatial clusters of small-occurrence region species, as well as the extent of existing protection for these species. From a global perspective, our overall results identify many countries with high spatial clustering where cost-effective small-occurrence region species protection In December 2022, 188 governments ratified the Kunming-Montreal Global Biodiversity Framework that commits participants to protecting 30 percent of the planet by 2030. Implementation with the limited resources available will require accurate identification of areas that are both critical for global biodiversity and suitable for cost-effective protection. This paper attempts to inform the identification process with new species habitat information from the Global Biodiversity Information Facility (GBIF). The GBIF’s previously-unmapped species, as well as improved estimates for species with existing maps. In the paper, we use recent advances in machine-based pattern recognition to estimate occurrence maps
suggest restoration of higher trust levels in the state in 1999, after progress in the transition to a market economy had been made - a transition that positively influenced individual attitudes toward paying taxes. The analysis of disaggregated data for Russian regions also shows significant regional differences in tax morale, reflecting self-interest and the degree of trust different regions have toward Moscow‘s institutions and policies. Looking at the distribution of tax morale scores in each of the three different years, the results indicate large differences between the percentage of individuals with a high tax morale (a score of 3) and those with the lowest scores across these years (see _Figure A3_ ). The deterioration in tax morale in Russia from 1991 to 1995 was strongly affected by a 39
) to have modem water services than advanced sanitation solutions, but coverage of in-house water taps and sewer connections appear to be virtually identical up to US$300 per household per month. In fact, there are two shortcomings in the LSMS data used for this analysis that cause this result in Figure 1.

First, _in-house_ water taps are just one form of private household water connection. In many types of dwellings, in-house taps might not be feasible or desirable to install, or households may not initially want to invest in indoor plumbing facilities. In these cases households could choose to install 7
evidence in either country that other policy supports preserved jobs significantly. This underscores the importance of designing and scaling policy support measures carefully to preserve viable firms and jobs in the face of large demand shocks.

We find that our model-based method predicts the level of further job losses in the winter of 2020 fairly well, based on a comparison of predictions with a COVID-period labor force survey for Jordan. Whereas it predicts the distributional impacts by gender, nationality, and educational attainment well, it fails to predict the differences by age group and wage level. Predicted and actual results show a greater rate of job loss for men employed in the formal private sector than for women and for those with less education. In addition, the rates of job loss by productive sector generally rank similarly to those observed, with some exceptions. We also document differences in the two countries’ performance in restoring formal permanent jobs versus other types of jobs (informal, temporary, self-employment) in the private sector. In Georgia, with its stronger export market presence and more flexible regulation of formal employment, formal firms were able to boost sales and hire full time workers back.<sup>54</sup> Moreover, they did so at a significantly faster rate than appears to have been the case for informal firms, for which there was no clear sign of such a formal job recovery. In contrast, in Jordan, formal sector jobs continued to decline through the fall and early winter, and at a faster rate than informal and temporary jobs in the private sector.

54 Other drivers of this difference could be policy measures to boost local demand or better containment of the virus; however, the evidence we present herein is not consistent with either explanation. Another key difference may be Georgia’s more educated workforce that is easier to train. However, this does not seem a likely explanation, since the rehiring rates are a function of a rebound in sales, rather than labor supply.

43
Policy Research Working Paper 6255

# **Abstract**

In 2009, buffeted by the great recession, Thai gross domestic product fell by 2.3 percent. Using monthly data from the socio-economic surveys of 2007–2010, this paper finds, after controlling for household variables, that real consumption per capita rose in 2009 relative to 2008 for most groups, including the poor, urban and rural households, men, women, and children. The losers were residents of Bangkok, especially those aged 20–29, and those working in sales and services. During the recession year of 2009, school enrollment rates did not fall, and durable goods purchases actually rose; households probably reduced their savings, and also benefitted from the lower food prices that prevailed in 2009. A simulation exercise based on the slowdown in growth of gross domestic product would have missed these effects, as would models based solely on readily-available data series. This points to the importance of country-specific policy analysis, rooted in timely local evidence, including household survey data.

This paper is a product of the Agriculture and Rural Development Team, Development Research 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 jhaughton@suffolk.edu and skhandker@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
1|Debt Reporting Metadata<br>from World Bank|
|**4**|Safely Managed Drinking Water|Dimension<br>1.5: Data use<br>by<br>international<br>organizations|SDG<br>6.1.1|Availability of Safely<br>Managed Drinking Water<br>data for use by JMP|
|**5**|GOAL 1: No Poverty (5 year moving<br>average of availability)|Dimension<br>3.1: Social<br>(SDG 1-6)|SDG 1|UN Global SDG Indicators<br>Database|

41
However, the characteristics of the balanced and the full sample (i.e., any firm that responded to a BEEPS survey in 2002, 2005, or 2008-9) are similar. One difference is that firms in the full sample come from countries with larger populations and that grew faster, while those in the balanced panel were more likely to be privatized and to be foreign owned (see Table 1). The full sample tips more heavily toward manufacturing firms, while the balanced panel tips more heavily toward trade. Finally, the balanced panel has a higher share of firms from countries with a pegged rather than a floating exchange rate regime. In practice, however, (unreported) regression results for the full sample were generally similar to those for the balanced panel.

# **B. Financial Crisis Surveys**

The Financial Crisis Survey was implemented by the World Bank in June and July 2009 in six countries: Bulgaria, Hungary, Latvia, Lithuania, Romania and Turkey. Firms that were part of the 2008-9 BEEPS were re-interviewed to see whether they were still operating and, if so, how they were coping with the crisis. Of the 2,501 firms in manufacturing, services, and retail trade that had been interviewed during the third round of the BEEPS survey between April 2008 and March 2009, 1686 were re-interviewed during the FCS.<sup>18</sup> The 2,501 firms in the third round of the BEEPS survey can be divided into four groups: (i) those that were still operating and were interviewed in the FCS; (ii) those that were still operating but were not interviewed during the FCS because enough firms had been interviewed, an interview could not be scheduled, or the firm manager refused to participate; (iii) firms that could not be located; and (iv) firms that had closed (see Table 2). We follow Ramalho et al. (2010) and classify firms as no longer operating if they fell into categories (
It is important to note that **the list of circumstances does not include all the circumstances that may be relevant in determining a child’s access to opportunities** . This is because the selection of circumstances, which defines the groups between which the equality of opportunities is examined, is necessarily limited by the information that is available from surveys. To consider just one example: conventional wisdom suggests that access to opportunities for a child may be influenced to some extent by the child’s ethnic group or tribe at birth. However, because ethnic and tribal affiliation is not included in the household surveys, this characteristic cannot be incorporated as a circumstance in the analysis. Information on the region where the child is located, wherever available, has been used as an extremely rough proxy to compensate for the absence of information on ethnicity. Similarly, the selection of opportunities is also limited to available information. For example, even when a timely record of vaccinations is critical for the health of children, this information is not provided by respondents in the household surveys.

Given that the list of circumstances cannot be completely comprehensive, the HOI that is computed using just the available circumstances would serve as a theoretical ―upper bound.‖<sup>6</sup> This means that adding the important circumstances currently missing would very likely _add_ to the penalty for inequality and drive HOI downward. In simple terms, the ―true‖ HOI, if one could obtain that, would not show a picture that is ―better‖ than what the HOI, based on limited information, would suggest.

Table 2 presents the coverage rate of opportunities for children of the relevant age groups for which the HOI is computed, and the incidence of circumstances in the population in each year for which a household survey is available. There is wide variation across opportunities as measured in terms of average coverage rates. Access to clean water for children under 15 years is widespread, but declining, during this decade; access to electric light is,