rafmacalaba/data-use-mentions-extended huggingface dataset:
poverty measures in India to date.

Following now well-established practice for India and elsewhere, a household's standard of living is measured by real consumption expenditure per person. The underlying NSS data do not include incomes, though it can be argued that current consumption is a better indicator of living standards than current income.<sup>26</sup> Nonetheless, there are various “non-income” dimensions

> 24 Data from the earlier rounds are included in the graphs, though poverty measures for rounds 4 and 5, rounds 6 and 7, rounds 9 and 10 and rounds 11 and 12 are aggregated as survey-period-weighted averages.  Thus, for instance, the headcount measure for combined rounds 11 (for August 1956-February 1957) and 12 (for March-August 1957) is 7/13-th of the headcount index for round 11 plus 6/13-th of the headcount index for round 11.

> 25 Most of our regressions for changes in poverty are based on 40 observations; they exclude the 48th round for 1992, the year of the macroeconomic crisis that provided an impetus for economic reforms. Thus, effectively, the change in poverty between the 47<sup>th</sup> round (for July-December 1991) and 48<sup>th</sup> round is not included in either the pre-1991 or the post-1991 period.

> 26 For an overview of these arguments see Ravallion (2016, Chapter 3).

7
distinction among survey questions is whether respondents are asked about their aspirations without any constraints or limitations (Roy, et al., 2018; Ross, 2019; Favara, M., 2017).

This analysis examines three key dimensions (i) educational aspirations, which were assessed using the question ‘ _Imagine you had no constraints and could study for as long as you liked or go back to school if you have already left. What level of formal education would you like to complete?’_ ; (ii) occupational aspirations, determined through the question ‘ _When you are about 30 years old, what job or "dream" job would you like to be doing?’_ ; and (iii) migration aspirations, gauged by asking _‘Would you consider leaving your community to look for better job opportunities?’_

> 2 The ILO SWTS questionnaire (2009), Module 2; the World Bank Young Basotho's Aspirations and Challenges Survey (2019); and Young Lives, Round 4, Ethiopia (2013-2014).

> 3 <mark>World Bank. Ethiopia - High Frequency Phone Survey 2020-2023. Ref: ETH_2020-2023_HFPS_v13_M. Dataset downloaded from h</mark> <u>ttps://microdata.worldbank.org/index.php/catalog/3716</u> <mark>on January 2, 2024; Malawi National Statistical Office (NSO) (Government of Malawi). Malawi - High-Frequency Phone Survey 2020-2024 (HFPS-COVID-19 2020-2024). Ref: MWI_2020-2024_HFPS_v18_M. Downloaded from</mark> <u><mark>https://microdata.worldbank.org/index.php/catalog/3766</mark></u> <mark>on January 2, 2024; National Bureau of Statistics. Nigeria COVID-19 National Longitudinal Phone Survey (COVID-19 NLPS) 2020-2021, Phase 1. Dataset downloaded from</mark> <u>https://microdata.worldbank.org/index.php/catalog/3712</u
different impacts on labor-market outcomes.

The remainder of the paper proceeds as follows. Section 2 presents the methodology and Section 3 describes the firm-level data source used. Section 4 discusses stylized facts about exporters in Georgia. Section 5 concludes with the results of the analysis.

# **2. Methodology**

> 2 The share, rather than the level, of exports is used to capture the structure of firms’ sales (as only using levels would capture size effects).

> 3 Whereas an OLS regression can identify statistically significant correlations between changes in the structure of firms’ sales and employment and wage growth, we employ an instrumental variables approach to identify causal relationships. We use exogenous fluctuations in exchange rates combined with firms’ initial exposure to various markets as instrumental variables (see Cebeci, Lederman and Rojas 2013).

2
. In both Korea and the first crisis episode in Turkey in 1992-1996 (as well as in Russia though credit lags GDP recovery there), private credit far surpasses original credit levels before the crisis. Overall, of the 9 crisis episodes in our sample that were identified as 3S episodes in Calvo et al. (2006a), we are able to identify only 6 as potential miracles and 3 as non-miracles (Korea and the two Turkey crisis episodes) on the basis of macro statistics alone.

Second, we look at the existence of Phoenix Miracles at the micro level to examine if there is a recovery in aggregate sales without a recovery in aggregate short-term borrowing (according to the micro mechanism suggested by Calvo et al., 2006b). We analyze the financial

> 5 See also Calomaris, Klingebiel,and Laeven ( 2005), and Claessens, Klingebiel,and Laeven ( 2005) for  a discussion of the resolution of developing country crises.

4
6108, World Bank, Washington DC.

- Feenstra, Robert C. 2010. _Offshoring in the Global Economy: Microeconomic Structure and Macroeconomic Implications_ . Cambridge, MA: MIT Press.

- Feenstra, R. C. (2004). Advanced International Trade: Theory and Evidence. Princeton, NJ: Princeton University Press.

- Francois, Joseph, and Bernard Hoekman. 2010. “Services Trade and Policy.” _Journal of Economic Literature_ 48 (3): 642–92 **.**

- Francois, J., and O. Pindyuk (2012). “Explanatory Note: Consolidated Data on International Trade in Services.” Unpublished.

- Francois, Joseph, Miriam Manchin, and Patrick Tomberger. 2013. “Services Linkages and the Value Added Content of Trade.” Working Paper 6432, World Bank, Washington, DC.

- Francois, Joseph, Olga Pindyuk, and Julie Woerz. 2009. “Trends in International Trade and FDI in Services.” IIDE Discussion Paper 200908‐02, IIDE, Rotterdam, Netherlands.

- Francois, Joseph, and Julia Woerz. 2008. "Producer Services, Manufacturing Linkages, and Trade." _Journal of Industry, Competition and Trade_ , 8 (3): 199–229.

- Freund, Caroline, and Martha Denise Pierola, 2015.  “Export Superstars.” _Review of Economics and Statistics_ , Vol. 97 No. 5 (December), 1023‐1032.

23
human health and social work activities; arts, entertainment and recreation, activities of extraterritorial organizations and bodies. The remaining taxpayers are classified as unskilled. The share of skilled workers in our sample is 35.97%. In the EU-SILC 2021, where the information on skill level is provided, the share of skilled employees is 32.91%. Therefore, our proxy is close to the true distribution of skilled and unskilled workers in the Romanian labor force. However, the similarity on the aggregate level does not guarantee the similarity on the sector level. In EU-SILC data, we can identify high-skill workers in all sectors of the economy. Using administrative tax data, we can only use the sector as a proxy of skill level and thus assume that skilled workers do not work in some sectors.

**In this study, we utilize labor demand elasticities based on international research to model the potential impact of changes in the minimum wage on employment and wages.** We quantify the “disemployment” effect by examining the proportion of workers earning wages between the existing and proposed minimum wage who transition to a non-employment status with zero wages (referred to as "losers").

32
3|48.6|
|Percentage of seat km in newer aircraft|96.8|71.4|90.8|98.3|80.2|79.3|
|Registered carriers on EU blacklist|0|0|0|0|0|0|
|FAA/IASA Audit Status|Fail|No audit|Fail|No audit|No audit|No audit|
|Percent of carriers passing IATA/IOSA Audit|0|28.6|0|50.0|11.1|33.3|

Source: Bofinger 2008. Derived from AICD national database, downloadable from http://www.infrastructureafrica.org/aicd/tools/data

## **Challenges**

Like many African countries, Ghana continues to face significant safety and security issues in air transport. Ghana failed the FAA/IASA Audit and none of its carriers has passed the IATA/IOSA audit.

More broadly, West Africa lacks a clear air transportation hub to play the role that airports such as Addis Ababa, Johannesburg, and Nairobi are playing on the other side of the continent. Abidjan, Accra, Dakar, and Lagos each play a significant role with respect to their immediate neighbors, but connectivity between each of these zones is much more limited and as a result connections can be much more complicated.

# Water supply and sanitation

## **Achievements**

Ghana is one of only five African countries that have already achieved the MDG target for water supply. According to DHS survey evidence, the percentage of households with access to an improved drinking water source rose from 69 percent in the 2003 survey to 84 percent in the 2008 survey, exceeding the MDG target of 76 percent.

Compared with other low-income African countries, Ghana has a relatively large share of the population relying on utility water (private or public taps). In the mid-2000s, 25 percent of Ghanaian households reported access to utility water of some kind, well ahead of the
<!-- Start of picture text --> The figure is constructed based on data for establishments Census definition of formality slightly differs across the In Ghana, formal establishments are defined as those<br>Note:<br>In Burkina Faso, an establishment is considered formal it has a registration number (with mobile trade and mobile credit, tax In Cameroon, formal establishments are the ones that prepare a Statistical and Fiscal Declaration In Rwanda, an establishment is considered to operate in the formal sector<br>Establishments with missing employment data and state-owned are excluded.<br> Establishment censuses obtained from the statistical agencies of the select countries; see section 3.<br>Source: in the manufacturing sector. statistical offices of the sample countries. identification number) and uses SYSCOA as an accounting standard. (DSF) or those that do not prepare DSF but keep an operating account and a partial account of balance sheets. that are registered with the Registrar General’s Department (RGD) and keep formal accounts. if it is registered at Rwanda Revenue Authority (RRA) and maintains regular operational accounts.<br>Census definition Census definition Census definition Census definition<br>Employment share in informal establishments<br>Keep formal account Keep formal account Keep formal account<br>Keep formal(SYSCOA) or regular account<br>Employment share in formal establishments<br>Tax registeration Tax registeration Tax registeration<br>Keep formal account (SYSCOA)<br>100+ 100+ 100+ 100+<br>20 − 99 20 − 99 20 − 99 20 − 99<br>10 − 19 10 − 19 10 − 19 10 − 19<br>5 − 9 5 − 9 5 − 9 5 − 9<br>1 − 4 1 − 4 1 − 4 1 − 4<br>100+ 100+ 100+ 100+<br>20 − 99 20 − 99 20 − 99 20 − 99<br>10 −
**Figure 3: Total labor content of exports and domestic production, South Africa 2001-2011**

<!-- Start of picture text --> 2000 2005 2010<br>Year<br>Total LVAD Total LVAX<br>200000<br>150000<br>US$ Mil 100000<br>50000<br>0<br><!-- End of picture text --> _Source:_ Authors’ elaboration based on LACEX.

# **b. Jobs**

The slower growth in the labor value added of exports compared to domestic final output is mainly due to the fact that the export sector has been slowly shedding jobs. The LACEX data combined with South Africa’s Labor Force Survey data show that between 2001 and 2011, the total number of jobs supported by South Africa’s exports declined from 3.0 million to 2.9 million, despite positive growth in exports (10.3% annually) as well as the wages paid to produce exports (7.9% annually). This finding confirms previous literature that exports in South Africa have not been job-creating (Chinembiri 2010, Smet 2013).

The LACEX data allow us to consider not only the direct impact of exports on jobs but the indirect impact, by considering the backward linkages with the rest of the economy that exports support. In fact, the LACEX data combined with South Africa’s Labor Force Survey data highlight the importance of considering both the direct and indirect contributions for understanding how exports support jobs in South Africa: only two in five jobs generated by exports were generated directly in 2011. Failing to account for the indirect jobs presents only a partial view of how exports contribute to labor outcomes in South Africa and other countries throughout the world, which have become more important over time. The direct number of jobs supported by South Africa’s exports declined from 1.47 million to 1.15 million between 2001 and 2011, but the indirect number of jobs increased
few years, and there have been instances of this in the past (for example, literacy rate changed from 53% in 2014 to 89% in 2019 in Côte d’Ivoire), but these types of drastic changes are minimal in the countries and period we study. For example, Brazil’s illiteracy rate among adults remained somewhat stable at 7.95% in 2015 and 6.8% in 2018; Indonesia’s adult illiteracy rate changed from 7.9% in 2015 to 8.55% in 2020; Sri Lanka’s illiteracy rate changed from 10.5% in 2016 to 7.9% in 2019 ( <mark>UNESCO Institute of Statistics,</mark> 2020).

15 The GMD was also available in Egypt in 2019, but the variable pertaining to Internet usage is only available in the 2015 survey. 16 For Sri Lanka, see http://www.statistics.gov.lk/LabourForce/StaticalInformation/QuarterlyReports/4thQuarter2020 (last accessed December 4, 2021); For <mark>Türkiye</mark> , see https://www.tuik.gov.tr/ (last accessed December 4, 2021).

> 17 Egypt is the only country for which we are unable to find labor force survey data in the same time frame as our online surveys were conducted.

> 18 <mark>We present all the demographic variables from the online data across waves in appendix figures A.4.1 to A.4.6. The figures indicate that the demographics captured by the online survey data are stable across different waves. Therefore, to make comparisons with GMD, we could potentially use any of the online survey waves. We use the median-wave, wave-2, for comparisons.</mark>

12
(which administrative records may miss). Further, surveys can provide estimates when the size of the target population is unknown and present the opportunity to collect rich additional data. However, survey data is typically collected in less frequent intervals, representative at coarser administrative levels, and can be subject to measurement error (Danovaro-Holliday et al. 2021; Althubaiti 2016; Burton et al. 2009). In the absence of conclusive evidence in favor of either data source, the official WHO/UNICEF estimates of vaccine coverage have used an arbitration procedure whereby administrative data is used if the discrepancy with survey data is smaller than 10 percentage points and survey data otherwise as long as it is deemed “credible” (Burton et al. 2009; 2012; Brown et al. 2013). Other research and policy has preferred survey over administrative data for its purported independence and higher accuracy (Dykstra et al. 2019; Cutts et al. 2016; Sandefur and Glassman 2015; Lim et al. 2008; Gavi, The Vaccine Alliance 2022a) and in rarer cases (typically when researchers had some control over the quality of administrative records) used only administrative data or both data sources complementarily (Banerjee et al. 2010; Barham and Maluccio 2009; Banerjee et al. 2019).

Evidence on the potential size and direction of the misalignment between survey and administrative is scarce in the context of COVID-19 and focuses on the United States or Germany (Wolter et al. 2022; Bradley et al. 2021; Nguyen et al. 2021). These studies found survey estimates to exceed administrative data with some evidence for errors of representation and measurement in the survey data. To the best of our knowledge, ours is the first large scale study investigating this issue in the context of LMICs and testing a comprehensive range of survey design choices.

A third stream of literature is applied (typically microeconomic) research using survey and sometimes administrative vaccination data in LMICs to inform policy. In these studies, vaccine uptake is usually the outcome of interest,
Figure 1: Terrestrial species with maximum occurrence reports by population group <!-- Start of picture text --> @<br>120,000-<br>@<br>80,000<br>2 -<br>Oo<br>£<br>&<br>(s) e@<br>a @<br>®<br>40,000-<br>@ e v<br>@<br>O- @ iy eee?<br>1 2 3 4 5 6 7 8 9 10 11 12 13 14 «15<br>Population Group<br><!-- End of picture text --> economic incentives to maintain sustainable fishing stocks and prevent unlicensed incursions.

also provide secondary protection from uncontrolled bottom trawling and other practices that boundary shapefile from the Maritime Regions Geodatabase maintained by the Flanders Marine Institute (2019). We intersect this shapefile with occurrence maps for the 145,092 marine species Other things equal, the intensity of fishing activity within a species’ occurrence area may have a
literature. We also see that it matters for family planning. However, in this case its superiority over women taking power is a little less clear. Agreement on women’s power is not significantly better for the likelihood that women received assistance with their delivery.

Women taking power is associated with the best outcomes for girls’ stunting, wasting, and likelihood of receiving a full course of vaccinations. Moreover, two key outcomes linked with a _transformational_ or transgressive process of empowerment in stronger conflict with prevailing norms – women terminating a pregnancy and reporting of modern contraception – are most strongly linked to women taking power.

When compared to the case of husbands giving power, taking power is linked to women receiving better antenatal and prenatal care, reduced girls’ stunting, and a higher likelihood of receiving all four recommended vaccinations for children of both genders. However, our results on intimate partner violence present a cautionary note: contestation over rights in the household is strongly related to a higher prevalence of violence, and within that, the woman taking power is related to significantly higher emotional violence.

Further work is needed to explore the implications of this facet of power for outcomes not measured by DHS data. Most importantly, more research is needed to understand which interventions move the needle on her taking of power, versus the husband giving her power or couples agreeing. Crucially, recent evidence shows that initiatives to engage men in the process of expanding women’s rights can result in a host of beneficial outcomes, including the reduction of intimate partner violence (Doyle et al., 2018). However, the process of shifting and contesting 29
I POLICY RESEARCH WORKING PAPER 1867

# **Summary findings**

Using data assembled from the Demographic Health Surveys of over 50 countries and from the National Family Health Surveys of individual states in India, Filmer, King, and Pritchett create a new data set of comparable indicators of gender disparity. They establish three findings:

- As is by now well-known, the _level_ of gender disparities in health and education outcomes for girls in South Asia is the highest in the world.

* Even within South Asia, and within India or Pakistan, there are huge variations in gender disparity. _Differences_ in gender disparity among Indian states or among provinces of Pakistan are typically greater than those among the world's nations. The ratio of female to male child mortality in one Indian state (Haryana) is

worse than in any country in the world, although in another state (Tamil Nadu) it is lower than in all but three countries.

* Across and within the set of developing nations, gender disparity is not only a phenomenon of poverty. There is almost no correlation between per capita income and the gender disparities in health and education outcomes. So although _absolute levels_ of health and education outcomes for girls are strongly related to economic conditions, the _disparities_ between outcomes for girls and boys are not.

Understanding what causes such great gender disparity _within_ South Asia is the next pressing question for researchers.

This paper-a product of Poverty and Human Resources, Development Research Groupis part of a larger effort in the group to understand the determinants of gender differentials. The study was funded by the Bank's Research Support Budget under the research project "Explaining Gender Disparity in South Asia" (RPO 681-29). Copies of this paper are available free from the World Bank, 1818 H Street NW, Washington, DC 20433. Please contact Sheila Fallon, room MC3-638, telephone 202-473-8009, fax 202-522-11S3, Internet address sfallon@worldbank.org. January 1998. _(59_ pages) _The Policy Research Working Paper Series disseminates the findings of work in
is assumed to face average inflation to a set of representatives from the income distribution who face different inflation rates. In other words, inflation inequality should be included in the objective functions of the MP/SBP. Furthermore, episodes of rising inflation with a profound impact on households highlight the need for frequent and representative data collection. The Pakistan Bureau of Statistics collects price data on a weekly (Sensitive Price Index) and monthly basis (Consumer Price Index), but the data is only representative on the national level (and by rural/urban), which could hide a lot of heterogeneity in consumer prices beyond the national average. Increasing the number of markets could support more disaggregated price statistics, which also better reflect the experience of consumers. Moving forward, pro-active and data driven monetary policy making to support price stability objectives is imperative.</mark> <mark>Lastly, it is important for the government to continue efforts towards the introduction and continuation of targeted safety net measures to protect poorer households from the unequal effects of inflation, especially following shocks that effect food prices. This includes expanding existing programs under the BISP umbrella with clear targeting criteria, and adjusting the benefit levels through regular indexation.</mark> 12
” card that does not permit the account holder to overdraw the account. The account holder pays bills by purchasing money orders or by making electronic transfers from the account. There is no data yet on the success of these accounts, but they do appear to be well designed to meet the needs of many of the unbanked who wish to open starter accounts.

Banks are also making efforts to create cost-effective means for LMI individuals to obtain emergency loans ranging from $200 to $500. Traditionally banks do not make such small loans except through credit card advances or some other prearranged line of credit, which excludes people unable to pass a traditional credit-risk screening procedure. Many credit unions and banks offer deposit-secured credit cards to customers unable to meet traditional credit risk standards. In addition, many credit unions will make deposit-secured small-value loans. For example, if a depositor has $500 in his account, he can borrow $500 rather than withdraw the money. The deposit balance serves as the collateral. Many customers apparently prefer to borrow the money rather than withdraw it because they like the budget discipline that repaying the loan imposes upon them. Some credit unions have also begun to offer rapidly-disbursing unsecured small-value loans to customers who might not meet traditional credit risk standards. Typically they require that the recipient has used direct deposit for several months and the loans are repaid out of future direct deposits. Early reports from credit unions offering this service indicate that it is popular and profitable for the credit unions (Richter and Tan, 2002).

The development and marketing of automated “payroll cards” is another recent privatesector innovation that could benefit the unbanked.<sup>14</sup> Until recently employers had to pay their

> 14A recent report on payroll cards issued by the Office of the Comptroller of the Currency provides a nice overview of the type of cards on the market and their features (Frumkim et al, 2003).

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