rafmacalaba/data-use-mentions-extended huggingface dataset:
Policy Research Working Paper 11080

# **Abstract**

This paper examines rural non-farm employment in Rajasthan, India, using multiple surveys and administrative data. The analysis covers three key aspects: individual and district-level determinants of participation in non-farm activities, the relationship between non-farm employment and household welfare, and barriers faced by rural enterprises. The findings show that secondary education strongly predicts participation in non-farm activities, particularly in skilled service sector jobs. However, women and socially marginalized groups face significant barriers in accessing non-farm employment, especially in higher-paying occupations. Households with members in regular non-farm employment, particularly in services, show significantly higher consumption levels, while casual non-farm work yields welfare levels similar to agricultural labor. Rural enterprises face multiple constraints, with lack of local demand and limited access to credit emerging as key barriers to business performance. The results suggest that although non-farm employment can substantially improve household welfare, access to better-paying opportunities remains highly unequal. Policy interventions should ad-dress both human capital development and structural barriers to create more inclusive access to non-farm employment opportunities.

This paper is a product of the Agriculture and Food Global Department. 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 fdarko@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
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||||||2005:|MxFL|S II(un|til 200|7)→||||

For the household data we use the first two waves of surveys from the Mexico Family Life Survey (MxFLS) (Rubalcava and Teruel, 2006). The first wave of the survey in 2002 interviewed 3,353 rural households<sup>10</sup> in 75 different localities located in all regions of the country and was conducted between March 2002 and August 2002, with the majority of the information collected between April and June. The second wave of the survey was collected between 2005 and 2007 with the majority of the data collection occurring from May 2005 to September 2005. The follow-up survey interviewed 3,271 households in 112 rural localities.<sup>11</sup> Both waves collected detailed information on each household member including information on educational attainment, migration and anthropometric measures, and as well as on household

> 10 Rural households are considered to be those that lived in localities with less than 2,500 inhabitants.

> 11 Given that some households (or parts of households) had moved between the surveys, in Wave 2 the households are spread out over a larger number of localities.

12
broadly representative as it has expanded over time). The skew is shown by Bauchet and Morduch (2010) who calculate that the average operational self-sufficiency ratio (a measure of organizational efficiency) of institutions reporting to the larger, socially-focused Microcredit Summit Campaign database is 95 percent, compared to 115 percent for institutions reporting to the MIX Market. Scores above 100 percent reflect “operational self-sufficiency.”

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130|
|Ararat - Urban|72,294|10|10|100|
|Ararat - Rural|186,983|25|10|250|
|Armavir - Urban|82,953|11|10|110|
|Armavir - Rural|183,703|25|10|250|
|Gegharkunik - Urban|65,902|9|10|90|
|Gegharkunik - Rural|162,809|22|10|220|
|Kotayk - Urban|137,493|18|10|180|
|Kotayk - Rural|116,364|16|10|160|
|Lori - Urban|124,050|17|10|170|
|Lori - Rural|87,532|12|10|120|
|Shirak - Urban|133,620|18|10|180|
|Shirak - Rural|96,856|13|10|130|
|Syunik - Urban|90,205|12|10|120|
|Syunik - Rural|44,350|6|10|60|
|Tavush - Urban|49,859|7|10|70|
|Tavush - Rural|69,943|9|10|90|
|Vayots Dzor - Urban|16,160|2|10|20|
|Vayots Dzor - Rural|31,501|4|10|40|
|**Total**|**2,977,130**|**400**||**4000**|

_Notes_ : The population estimates at the stratum level are by the end of 2022 and match with the population statistics from the Statistical Committee of the Republic of Armenia. Refer to https://armstat.am/file/doc/99538403.xlsx for the urban population and https://armstat.am/file/doc/99538413.xlsx for the rural population.

> 19 It is preferred to use
<!-- Start of picture text --> 30<br>30 25<br>20<br>25<br>15<br>20 10<br>5<br>15<br>0<br>10 -5<br>-10<br>5<br>-15<br>0<br>Domestic Credit Growth (India) Exports Growth (India)<br>Domestic Credit Growth (Median of EM7) Exports Growth (Median of EM7)<br>2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016<br>2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016<br><!-- End of picture text --> Note: Central Statistics Office, and World Development Indicators. Data in the figures are for the respective calendar year. Credit growth is nominal.

# **3.2 Interstate Patterns of Growth during and after the GFC**

To further identify the characteristics of the slowdown after the global financial crisis, we analyze how economic growth across Indian states was impacted by the GFC.<sup>26</sup> Unsurprisingly, we see exactly the kind of economic cycle in economic growth, credit growth, investment, and manufacturing sector at the state level as is evident at the national level.<sup>27</sup> The average (mean as well as median) growth rates of all of these variables increased prior to the crisis, during 2004–08, followed by a correction that started with the global economic slowdown in 2007–08; and precipitated when the GFC took hold, with the collapse of Lehman Brothers in September 2008. While GSDP growth recovered in the post-crisis years, credit growth, investment, and manufacturing growth remained subdued.

We ask whether there were any specific state-level characteristics that correlated with the impact of the GFC on the states. We define the states
of minimum wage for the employees in the construction sector is 7,441 EUR). However, the imputed tax income data spike is significantly higher than that observed in EU-SILC data. The spike in the value of minimum wage may be seen as evidence that the minimum wage is effective in providing a floor constraining the value of wages. Without the minimum wage, the underreporting of income will probably be higher (minimum wage establishes a minimum value of

12 After applying censoring at income equal to €29,678, the mean survey income becomes €10,863 and the mean imputed tax income (tax data imputed into the survey) is €10,191.

13 The value of income at P90 in tax data is 19% higher than in the survey, and at P95, the income reported in tax data is 28% higher. At P99, income in tax data is nearly twice as high as in survey data (see Table 3).

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While the human capital variables did not have clear predictions, husband's<sup>schooling</sup> has an interesting impact on violence. A one year increase in the mean<sup>value of husband's</sup> schooling increases the risk of violence by almost four per cent. This suggests<sup>that the positive</sup> effects of schooling on violence - by raising the transfer the wife's family<sup>is willing to give and by</sup> raising the husband's gains to marriage, dominate the negative effect -<sup>increasing the husband's</sup> welfare after separation. None of the other variables have significant effects.

To think about the policy implications of these results, it is important to appreciate<sup>the</sup> extent to which most Indian women do not have options outside of marriage.<sup>Marriage, for</sup> women, is never a matter of choice but is almost entirely driven by<sup>social norms and the</sup> preferences of parents. Consequently, the burden of any adversity in the marriage<sup>market, or</sup> within a marriage after it has been arranged, is almost exclusively borne by<sup>the wife or bride. As</sup> other work has demonstrated, it is in this context that a shortage of grooms in<sup>the marriage market</sup> causes dowries to rise substantially. If it were possible for a woman<sup>to opt to marry at a much</sup> later age, or choose not to marry at all, or to divorce her husband if the marriage were unsatisfactory, dowries would not rise, though the number of single or divorced<sup>women might.</sup> Thus, providing opportunities for women outside marriage and the marriage market would significantly improve their well-being by allowing them to leave an abusive husband
# **_Question 2: What factors contribute to the high dispersion across the four dimensions of the SPI in low-performing countries and the slow convergence to the fully capable systems in place in high-performing countries?_**

Donor coordination in statistical capacity building is weak. A 2020 report by the OECD Development Assistance Committee (DAC) noted that “challenges relating to donor coordination and alignment with country priorities can often be explained by a combination of weak in-country demand for data and statistics, unclear priorities, along with tensions created by strong donor demand for specific data and statistics for program design, targeting, monitoring and results reporting.” Only half of DAC members make the country’s national strategy for the development of statistics the basis for their engagement. Donors are more likely to invest in point-in-time data sources, such as household surveys, that provide ready-to-use data quickly, with minimal cost overruns. Household surveys are not necessarily conducive to developing sustainable statistical capacity, however, because “the role of the NSO is often reduced to recruiting and fielding enumerations while questionnaire designs are standardized and analyzed by development agencies.” In addition, only 16 percent of low-capacity NSOs cited these surveys as a strategic priority.

Donors’ poorly coordinated and survey-centric approach to country support increases scores in one dimension of the SPI (Census and Surveys) but pays little regard to the other three dimensions. It also means that NSSs accept external support if it brings additional funding. As countries become better at understanding (and stimulating) user demands, they are more likely to increase domestic funding for their work, which should strengthen all four SPI dimensions.

# **_Question 3: Should capacity-building strategies better reflect the fact that many countries are providing too little data given users’ needs, as highlighted in Figure 4?_**

An important implication of our theoretical framework is the existence of a steady-state equilibrium of statistical capacity that is determined by the supply of and demand for data. This equilibrium shifts in response to changes in the demand for data or
imports and shuttle trade. We adjust for the CIS trade, so we are applying the MFN rates on all imports from the non-CIS. This slightly, but not significantly biases upward the rates we employ relative to collected rates.

**Export tax data.** Analogous to the import trade data, the Russian State Customs Committee publishes data on export volumes and values. Similar to the tariff data, the export

> 29 International Monetary Fund, ―Russian Federation: Selected Issues and Statistical Appendix,‖ 2002.

47
that 17% of the children in rural Indonesia are born weighing 2,500 grams or less. Approximately 30% of these children also grow up to be wasted (under 2 standard-deviations of the WHO reference population’s mean) and 19% to be stunted. We complement this description by looking at the weight-for-age and height-for-age z- scores for groups of children defined by the literacy status of their mothers/caregivers. Figure 2

> 6The child’s birthweight is based on recall by the mother and when possible verified using the birth registration card. The typical child was 3,106 grams at birth. Digital scales were used for weight measurement and tape measures were used for measuring respondent height. These were then compared to World Health Organization Child Growth Standards and WHO Reference 2007 composite data to assess whether respondents are stunted or wasted.

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# **IV. Methodology**

_Doing Business_ measures and compares 11 areas of business regulations, capturing their impact on firm establishment and operations. The reports attract a wide audience, including governments, private sector, NGOs, civil society organizations as well as academic and research communities. Media is one of the main avenues through which _Doing Business_ reaches its audience. To a certain degree, media coverage of the reports captures and shapes public opinion about domestic business climates, fostering a broader public debate about _Doing Business_ and its direct impact on local entrepreneurs and business climate. Media outlets can either veraciously portray _Doing Business_ data or distort the reports’ messages and findings in pursuit of a particular political agenda. The main objective of this paper, however, is to investigate whether local media coverage of _Doing Business_ spurs business regulatory reforms in the measured economies.

In order to test the set hypothesis, we first collected primary data on the global coverage of _Doing Business_ in the local media. Given the previous absence of such data, media-focused research primarily used freedom of press, state ownership of press and journalist abuse of Freedom House as well as relevant questions from World Value Surveys as the main input variables. Two search engines were selected for the collection of comparable media coverage data: Factiva and Google advanced search. These two domains have proven to meet the desired research criteria. The key search engine selection criteria included: access to a large comparable global database encompassing articles from a substantial number of local media sources; availability of reliable media article archives dating back to 2003; presence of search filers allowing to specify countries and time frames (months and years); ability to search for articles in local languages, including major local dialects; possibility to segregate results between the ones published by local and international media and existence of a user-friendly interface. Although more industrious, the concurrent use of two search engines was a deliberate undertaking. Having two similar novel data sets allowed for extra robustness checks, ensuring better accuracy of the novel data.

Google
Policy Research Working Paper 10957

# **Abstract**

While populations in low- and middle-income countries are exposed to some of the highest levels of air pollution and its consequences, the majority of economics research on the topic is focused on high-income settings where there is greater data availability. This paper compares and evaluates the three principal sources of air pollution data (regulatory-grade monitors, satellites, and low-cost monitors) in a Sub-Saharan African context in terms of the accuracy of measurements of inhalable fine particulate matter across spatial and temporal frequencies and their performance when studying policy impacts. Satellite data is closely aligned with data from the regulatory-grade monitors at lower temporal frequencies. The low-cost monitors underestimate the amount of fine particulate matter relative to the other data sources. Calibration, especially context-specific calibration, of the low-cost monitors’ data improves its alignment with other data sources. The paper uses each data source to evaluate the air pollution externality of mobility reduction policies using a difference-in-differences design and finds similar results, especially in terms of percent reduction. The paper considers policy makers’ constraints to air pollution monitoring in low-income settings and demonstrates that co-locating one regulatory-grade monitor in a network of low-cost monitors can capture the spatial variation of pollution across an urban area and achieve better accuracy than either of these data sources alone. This provides a framework for policy makers to generate the data needed to evaluate environmental policies and externalities.

This paper is a product of the Development Impact 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 smilusheva@worldbank.org and bridgeth@IADB.org. A verified reproducibility package for this paper is available at http://reproducibility.worldbank.org, click **here** for direct access.

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E.D. (2017). “Division of Workforce and Domestic Labor Among Same-Sex Couples.” In: Connelly R., Kongar E. (eds) _Gender and Time Use in a Global Context_ . Palgrave Macmillan, New York.

- Sayer, L. (2016). “Trends in women’s and men’s time use, 1965–2012: Back to the future?” In S. M. McHale, V. King, J. Van Hook, and A. Booth (eds.), _Gender and Couple Relationships_ (pp. 43–77). Geneva, Switzerland: Springer International Publishing.

- Suh, J. (2016). “Measuring the "Sandwich": Care for Children and Adults in the American Time Use Survey 2003-2012.” _Journal of Family and Economic Issues_ , 37: 197–211.

- Suh, J. and N. Folbre. (2016). “Valuing Unpaid Child Care in the U.S.: A Prototype Satellite Account Using the American Time Use Survey.” _Review of Income and Wealth_ , 62(4), pp. 668-684.

- Sullivan, O. (2011). “An end to gender display through the performance of housework? A Review and Reassessment of The Quantitative Literature Using Insights from The Qualitative Literature.” _Journal of Family Theory and Review_ , 3(1), pp. 1–13.

- Vickery, C. (1977). “The Time-Poor: A New Look at Poverty.” _Journal of Human Resources_ , 12(1), pp. 27–48.

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Identifying Urban Areas by Combining Data from the Ground and from Outer Space: An Application to India Virgilio Galdo, Yue Li, and Martin Rama

**Keywords:** urban extent; urbanization rate; subjective assessment; Google Earth images; georeferenced data; satellite imagery

**JEL Classification:** O1, O18, R1

Virgilio Galdo, Yue Li, and Martin Rama are with the Office of the Chief Economist for South Asia at the World Bank. The corresponding author is Yue Li. Her contact information is yli7@worldbank.org.

Skillful research analysis was provided by Maria Florencia Pinto, Sutirtha Sinha Roy, and Wenqing Zhang. Comments and suggestions by Gilles Duranton and by participants at the 8th European Meeting of the Urban Economics Association are gratefully acknowledged.

This research was funded by the World Bank and by the Department for International Development of U.K. as part of the Sustainable Urban Development Multi‐Donor Trust Fund.

The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the World Bank and its affiliated organizations, or those of the executive directors of the World Bank or the governments they represent.
in other languages and we screened French language studies for inclusion in the review. We did not conduct specific searches in the RePec database, nevertheless, it is worth mentioning that we did conduct electronic searches in the Econlit database that encompasses all RePec working papers. We did not conduct moderator analysis by all types of global region, only for those regions where we had sufficient observations to undertake

> 15 Studies were done in different countries, different years, and scale as some used administrative data and other small-scale RCTs.

> 16 For instance, a paper by Grimm and Paffhausen (2015) studies a similar issue but focuses only on employment outcomes. Their search was done after 1990 and only one paper from prior to the year 2000 (Fretwell et al, 1999) was found. This paper would not qualify to enter this review as it is designed to assess active labor policy in general (not SMEs specifically) and also includes assessment of self-employment, which is not covered by this review.

28
The late response of Ethiopia to AGOA preferences, and the importance of SEZs and FDI suggest that the binding constraint in this case was traditional country-level inadequacies, like poor transport infrastructure, high transaction costs, and lack of access to capital, that were partially addressed by SEZs. The future success of Ethiopian exports of apparel to the US will depend on how well learning-by-doing and other dynamic comparative advantage factors materialize for firms inside and outside the SEZs.

# **9. What explains the heterogeneous impact of AGOA on apparel exports across countries?**

Our analysis shows that AGOA had a differential impact on apparel exports across African countries, sub-periods, and sub-regions. While some African countries took advantage of the opportunities created by the US trade preferences, others failed to do so, and the durability of the AGOA impact varies across sub-regions. We consider some factors that could have contributed to such heterogenous effects.<sup>45</sup> We re-estimate Eq. (1), allowing the AGOA apparel term to enter by itself but also interacted with policies that could be linked to developing export capacity. We include average tariffs imposed by African countries on their own imports to capture ease of participation in international supply chains, the cost of starting a business as an indicator of the business environment for both domestic and foreign firms, internet access as a channel for knowledge about manufacturing and consumer tastes, and oil rents as an aspect of endowments that could affect competitiveness.<sup>46</sup>

> 45 Frazer and Van Biesebroeck (2010) found differential short-term impacts of AGOA on apparel and non-apparel across countries, but no meaningful correlations of those with measures of corruption, rule of law, or import tariffs imposed by African countries.

> 46 The variables differ across countries and over time. Tariff data are taken from Tet <mark>i (2020) described in the Online Appendix, the cost of starting a business is taken from the Doing Business database, while the number of internet users per 100 people