rafmacalaba/data-use-mentions-extended huggingface dataset:
Policy Research Working Paper 5764

# **Abstract**

Thousands of Moldovans emigrated for work abroad over the last few years following nearly a decade of economic stagnation in their home country. At about 30 percent of the labor force, Moldova’s emigrant population is in relative terms among the largest in the world. This study uses a unique household survey to examine the impact of emigration on wages in Moldova. The authors find a positive and significant impact of emigration on wages and the result is robust to the use of alternative samples and specifications. The size of the emigration coefficient varies depending on the sample and model specification, but the baseline result suggests that, on average, a 10 percent increase in the emigration rate is associated with 3.2 percent increase in wages. At the same time, there is evidence of significant differences across economic sectors in the estimated effect of emigration on wages. The authors speculate and provide some evidence that offsetting changes in labor demand, as revealed by information on employment growth by sector, may help explain some of the heterogeneity.

This paper is a product of thePoverty Reduction and Economic Management Unit, Europe and Central Asia Region. 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 author may be contacted at LBouton@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
of wellbeing and basic survival, living just above the extreme poverty line tells us little about people’s ability to participate in global prosperity. There is a shift towards broader and more relatively defined poverty measures, including measures referring to within-country inequities, as more relevant to the policy stakes – are people being left behind by global economic growth, or made able to meaningfully participate and benefit from it?

> <mark>between the first and last income per capita value for each period and country.  This value is multiplied by the country population weight. The country population weight is the result of dividing the country population of the year when the first available income per capita data point by the world’s total population.  We obtain the sum of the weighted CAGR of each country and period and the sum of the weights by group (BB, EM, OECD). Finally, we obtain the average population-weighted annual income per capita growth by dividing the sum of the weighted CAGR by the sum of the weights.</mark>

> 7 As reported in World Bank’s September 2020 PovcalNet update:

> https://blogs.worldbank.org/opendata/september-2020-global-poverty-update-world-bank-new-annual-povertyestimates-using-revised

> 8 Calculations based on Mahler et al (2021) updated poverty estimates accounting for the impact of COVID-19 but without including the effect of the 2022 global high inflation and the Ukraine conflict: https://blogs.worldbank.org/opendata/updated-estimates-impact-covid-19-global-poverty-turning-cornerpandemic-2021

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in Table 2. In column (1) we illustrate the total reference adult population in each year, computed using the household survey. In 2019 there were approximately 5.4 million adults over 20 yearsold in Honduras out of a population of over 9 million individuals. For that year, the merging point between the two sources was L465,000, the equivalent of the income of the top 0.6% highest-earning individuals in both datasets. Despite the fact that administrative data includes over 600,000 individuals for that year, our merging process led us to use fewer than 40,000 taxpayers to complement the income distribution obtained from survey data – this share ranges from 0.4% - 1% in the 2012-2019 period, and is significantly lower at 0.1 - 0.2% before that, when the availability of tax records is more limited.

> 12We recognize the limitations of this procedure as laid out in Blanchet _et al._ (2018). In future versions of this working paper we expect to also present results using alternative methods to complement survey data with tax records.

> 13The top decile of the adult population in Honduras represents 300,000 - 450,000 individuals, depending on the year. In some years, our entire sample of individuals in tax records is lower than those numbers, so we are only able to construct a smaller share of quantiles. In practice that does not impact our results, since we document that we never replace the survey below the top 1% level.

> 14 We provide more information on this adjustment in Appendix G.

> 15In Figure A.4, we illustrate these ratios across income levels for three years. We note that the ratio is not monotonic – since we collapse the tax data in quantiles and the survey data is sparse at high income levels, sometimes the ratio decreases as income increases and even dips below one. But the trend of more income in the tax data at higher levels is clear in all years presented,
the husband's satisfaction with the marriage. For the sake of comparison we also include the number of female children, even though their effect on the husband's satisfaction is less clear.

Outside options in the marriage market, ml and m2 are measured by ihe marriage squeeze ratio<sup>19</sup> -the ratio of the number of women to the number men at marriageable ages (defined as women aged 10- 19/ men aged 20-29). ml is measured at the year of the marriage while m2 is measured ten years after the marriage. m2 is measured with a ten year lag because we do not know the exact time when the violence occurred but our qualitative interviews suggest that most incidences of violence occur within the first ten years of marriage. Additionally, since the Indian census is conducted every ten years, a ten year lag permits us to obtain the value of the marriage squeeze ratio from the next period available in the census. For bothl m2 and m2 we use the census year closest to the year of marriage. We obtain the data from the census for Mysore district in Karnataka State - the geographic region within which these households choose their spouses20.

# **5. Econometric Results, Policy Implications and Conclusion**

Table I provides a few summary statistics about the community. The families in our sample are poor. The mean schooling of both women and men is very low, at 1.14 years for women and 1.46 years for men. The average annual income of the wife's parents is 5,506 rupees ($625 in PPP adjusted US dollars) while that of the husband's family is 6440 rupees (PPP $731), but note that the standard deviation of the wife's family's income is very large at 6572 rupees compared to 784 rupees for the husband's family income. One possible reason for this large variation is measurement error because we did not interview the parents of the wife directly, but
although the initiatives have led to rich academic papers and policy reports, they have not yet proven useful to inform occupational skills profiling, qualification frameworks, curricula, and other decisions about human capital investments.

_Occupational skills pilots in Vietnam and Indonesia_

**The SDS’s methodology also builds on previous efforts to profile occupations in Vietnam and Indonesia.** Both efforts piloted an adaptation of the O*NET content model to gather detailed skills information on in-demand occupations using surveys. In Vietnam, 7 occupations were selected for a survey replicating O*NET’s skills, tasks, and education and experience modules (Moroz, Nguyen, and Chu 2019). The questionnaire asked respondents questions about the importance of the 35 skills in O*NET’s skills module. Questions about a skill’s level of sophistication, which are included in O*NET, were omitted given the correlation between these measures (Handel 2016). The questionnaire also asked about the task and education and experience requirements of each occupation. Respondents included both workers in the selected occupations and “occupation experts” who were individuals with significant knowledge about a given occupation.<sup>8</sup> Workers and occupation experts were identified through capstone contacts given resource constraints. In Indonesia, a pilot (Indotask) adapting similar O*NET modules targeted 51 occupations (Alatas, Granata, and Posadas 2020). The pilot also asked about task requirements, education and experience requirements, and respondent characteristics. Both job incumbents and occupation experts were included as respondents. Respondents were identified through an earlier firm-based survey of occupational demand. A comparison of results between Indotask and O*NET showed significant differences in skills use for comparable occupations. Lessons learned from these pilots are reflected in the design of the SDS, and discussed in the methodology section.

# **Methodology**

**The SDS adapts existing skills surveys to the country context and the objective of obtaining a comprehensive but also detailed picture of occupations in Vietnam** . The SDS
17 to engage in extra-marital sex (table 10, column 5).

# **6 Conclusion**

We use data from Mozambique to test for disinhibition behaviors resulting from increased access to ART. The main hypothesis is that people may alter their sexual behaviors in response to a perceived decrease in the opportunity costs of contracting AIDS that results from expected access to ART. Such compensating behaviors, if large enough, could potentially offset some of the positive effects of increased access to ART. After controlling for individuals fixed effects, we find some suggestive evidence of disinhibition behaviors, consistent with prior literature on risk-taking in the USA and Europe, following the introduction of ART. We find that out of 24 estimated coefficients reported in tables 5-7, six coefficients that are statistically significant are consistent with disinhibition, while three of the statistically significant coefficients run contrary to disinhibition. If we take a less conservative approach and focus only on the sign of the point estimates, 19 coefficients are consistent with disinhibition and 5 coefficients run against disinhibition.

Our findings suggest that men and women responded differently to perceived changes in risk that occurs with greater access to ART. Men’s demand for risky sexual behaviors increased with the “false” belief that “AIDS can be cured”, and decreased with the “correct” belief that “AIDS can be treated but not cured”. Women’s demand for risky sexual behaviors increased only with the correct belief that “AIDS can be treated”. We do not have a straight explanation of the observed gender difference. One possible explanation may stem from the cultural context of Sub-Saharan Africa, which in general grants more autonomy on sexual choices to men than to women, so that in general it would be easier for men than for women
- Arnold, Jens M., Beata S. Javorcik and Aaditya Matoo (2011), ―Does Services Liberalization Benefit Manufacturing Firms: Evidence from the Czech Republic,‖ _Journal of International Economics,_ Vol. 85 (1), 136-146.

- Arnold, Jens, Aaditya Mattoo and Gaia Narciso (2008), ― Services Inputs and Firm Productivity in Sub-Saharan Africa: Evidence from Firm Level Data,‖ _Journal of African Economies_ ,‖ Vol. 17(4), 578-599.

- Baldwin, Richard.E., Rikard Forslid and Jan Haaland (1999), "Investment Creation and Investment Diversion: Simulation Analysis of the Single Market Programme," in R. Baldwin and J. Francois (eds.), _Dynamic Issues in Applied Commercial Policy Analysis_ , Cambridge: Cambridge University Press

- Balistreri, Edward J., Russell H. Hillberry and Thomas F. Rutherford (2011), ―Structural Estimation and Solution of International Trade Models with Heterogeneous Firms,‖ _Journal of International Economics,_ Vol. 83(2), 95-108.

- Balistreri, Edward J., Thomas F. Rutherford and David G. Tarr  (2009), ―Modeling Services Liberalization: The Case of Kenya,‖ _Economic Modeling_ , Vol. 26 (3),May,  668-679.

- Balistreri, Edward J. and David G. Tarr (2011), ―Services Liberalization in Preferential Trade Arrangements: The case of Kenya,‖ World Bank Policy and Research Working Paper No. 5552, January.

- Baranov, S.P. (2000), ―Compiling the disaggregated version of ―input-output‖ tables of the Russian Federation for 1995 year for consequent use as a basic data for building the general equilibrium model for the Russian Federation,‖ mimeo.

- Bourguignon, Francios, Jaime  de Melo and C. Morrison (1991), « Poverty and Income Distribution During Adjustment: Issues and Evidence from the OECD Project,‖ _World Development_ Vol. 19, 1485-1508.

- Bourguignon, F.
## **_Appendix Figure D5. Mauritius exports of apparel to the US by fabric origin_**

# Exports of Apparel to the US by Fabric Origin

<!-- Start of picture text --> 300<br>Using fabric or yarn N/A in<br>250<br>commercial qty (CITA).<br>200<br>Using fabric or yarn N/A in<br>150 commercial qty<br>(401/NAFTA)<br>100<br>Using foreign fabric (LDC<br>50 provision)<br>0<br>Using African fabric made<br>2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 from U.S. or African yarn.<br><!-- End of picture text --> Source: USITC-OTEXA.

Note: Exports are classified by tariff regime eligibility and by fabric origin by product-country-year.

## **D3) Case study on Ethiopian apparel exporting firms: trade preferences or domestic policy reforms?**

The raw country-product-year export data and the yearly impacts of AGOA clearly demonstrate that Ethiopia saw a late success in its apparel export growth to the United States. The effect of AGOA on apparel exports remains statistically significant after controlling for changes in exports to the European Union that occurred after AGOA came into force. To further verify that the boost in export to the US can be largely attributed to AGOA, we visited factories in Ethiopia and interviewed leading firms in the apparel sector. This section relies on information obtained from fieldwork in Ethiopia and testimonies of corporate executives.

Jay Jay Textile PLC was founded in 1971 in the Indian state of Tamil Nadu and operates production plants in Sri Lanka and Bangladesh. The company started its operation in Ethiopia in 2014 and began exporting to the US market in 2015. The main motivation to set up a factory in Ethiopia in 2014 was the establishment of the EPZ that addresses infrastructural challenges by providing land and factory
# Can we trust shoestring evaluations?

## Martin Ravallion<sup>1</sup>

_Development Research Group, World Bank 1818 H Street NW, Washington DC, 20433, USA_

**JEL:** C81, H43

**Keywords:** Baseline survey, retrospective data, recall error, poor areas, China **Sector:** POV

> 1 These are the views of the author alone and should not be attributed to the World Bank or any affiliated organization. This paper builds on a long-term evaluation developed by the author and Shoahua Chen at the World Bank, in collaboration with staff of the Rural Survey Organization of China’s National Bureau of Statistics, which implemented the survey data collection. The author is also grateful to Solveig Buhl, then of Deutsche Gesellschaft für Technische Zusammenarbeit (GTZ), for comments on the recall module developed for this paper, and help in field testing and refining the module. Funding for the study was provided by the World Bank’s Knowledge for Change Trust Fund. For their comments, the author is grateful to Kathleen Beegle, Gero Carletto, David McKenzie and Dominique van de Walle.
Center of the World Bank [...] from July 1974 to February 1976.” Not long after, and also at the Development Research Center, Sudhir Anand conducted his pioneering work on racial inequality in a developing country, using data from Malaysia’s 1970 Post-Enumeration Survey (Anand, 1983).<sup>16</sup> On the data front, Shahil Jain’s (1975) compilation of inequality measures for a number of countries was an important precursor to later efforts by the Bank to assemble and curate data on income distribution – a subject to which we will return.

As usual, these analytical developments at the World Bank did not take place in an intellectual vacuum. The early 1970s saw increased interest in issues of distribution in Economics, Philosophy, and in the Social Sciences more generally. John Rawls’s (1971) _A Theory of Justice_ was perhaps the most important philosophical challenge to utilitarianism in the Twentieth Century. Equality of opportunity was one of its key principles of justice, and it also proposed a very low tolerance for inequalities of any kind: they should only be tolerated insofar as they worked to the ultimate benefit of the worst-off. Within Economics, an early and illuminating attempt at linking long-run growth theory to the size distributions of income and wealth was provided by Stiglitz (1969). Atkinson (1970) placed the measurement of inequality on a sounder and more robust basis, which would provide the foundation for most of the work on measurement that followed, for decades.<sup>17</sup> Amartya Sen’s (1973) book _On Economic Inequality_ was both pathbreaking and influential, and his article in _Econometrica_ (Sen, 1976) first proposed that the measurement of poverty ought to explicitly incorporate an aversion to inequality. Some of the aforementioned work on inequality measurement and decomposition carried out at the World Bank during this time was influenced by – and in turn exerted its influence on – the work by Atkinson, Bourguignon, Kolm and Sen.

Inequality,
Policy Research Working Paper 11068

# **Abstract**

Using data from the World Bank Enterprise Surveys from 2006 to 2023, this paper studies the corporate ethical standards of technological digital oriented firms. The findings indicate that technology and digitalization positively impact the adoption of environmental and social standards. However, digital oriented technological firms show lower governance standards. These results are influenced by country culture, the burden of business regulation, and the perception of the courts as an obstacle to business activity. This underscores the importance of the broader society and the quality of the business environment in shaping how digital oriented technological firms adopt ethical standards.

This paper is a product of the Global Indicators Group, Development Economics. 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://www.worldbank.org/prwp. The authors may be contacted at dmare@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 by the Research Support Team
, Last 12 Months (USD PPP)|-2.58|(10.47)|[0.51]|10.17|(70.04)|1,422|
|Other, Last 12 Months (USD PPP)|60.20*|(36.76)|[0.33]|44.94|(231.61)|1,422|

**_Notes_** :

- The table shows the regression results on financial assistance using the 2021 in-person data. Each row is its own dependent variable. These outcomes were not pre-specified as they were added after the first-wave phone survey data were collected. UNHCR refers to the United Nations High Commissioner for Refugees; WFP refers to the World Food Programme; IP refers to the implementing partner.

- The independent variable of interest is the TOT treatment indicator, which is the predicted value from a first-stage regression of treatment implementation on treatment assignment.

- All values are in USD PPP and are winsorized at the top 1% of values in order to limit the influence of outliers.

- The regressions also have assessment month-by-year fixed effects, enumerator fixed effects, community-level controls (Irbid/Mafraq governorate and population quartile), and household-level controls (vulnerability-assessment quartile, shelter program, baseline number of children, baseline number of children plus adults, respondent gender, and respondent age). In the parentheses are robust standard errors clustered at the locality level. Regressions are weighted by the number of people interviewed in each household. Statistical significance represented by * (10%), ** (5%), and *** (1%). Q-values are calculated per Anderson (2008) and correspond to the outcomes in the table.

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Group 7:** Social status (ST, SC and Others). **Group 8:** Educational Attainment (illiterate; below secondary; secondary and HS; college and above). **Group 9:** Income groups (five income quintiles). **Group 10:** All 35 States and UTs. *Regression estimates underlying the Shapley decomposition are presented in the annex. Source: Authors’ own estimate based on NSSO data.

Our narrower definition of the status building role of women, as indicated by individual marital status and the number of children in the household, plays no significant part in explaining individual FLFP decision. However, the overall marital composition of women within the household, as compared to individual marital status including child care responsibility, contributes more than twice towards women’s labor force participation decisions.

Perhaps the most important finding of this analysis is that it highlights the preeminent role of household level labor diversification on the individual labor force participation of women. Estimation of the relative contributions of employment composition in a family explains more than 60 percent of the variation in FLFP decisions— both spatially and inter-temporally. As mentioned earlier, we consider three major components of employment in our analysis— the proportion of 30