rafmacalaba/data-use-mentions-extended huggingface dataset:
child dependents (18 years or younger) in their household.

We start our analysis with an examination of the overall male/female closure gap using: where _Yijt_ is the outcome of interest for firm i in country j at time t (seven waves of data where a random sample of business owners on Facebook were sampled each month). _Femaleijt_ is a dummy variable equal to 1 if the business owner is female; 0 if male. _Xijt_ is a set of controls for firm and entrepreneur characteristics, _δr_ indicates region-of-the-world fixed effects and _εijt_ is the error term.<sup>27</sup> Equation 1 allows us to explore the time path by examining the gender gap in business during COVID-19 at the time of each survey wave for the six 2020 survey waves separately before we proceed in pooling the waves. We always present wave 7 collected in 2021 as a cross-section. We allow for general heteroskedasticity and use robust Eicker-Huber-White (EHW) standard errors throughout our analysis.

The main data are a repeated cross-section of firms. As discussed below, there is not much variation in the effects across rounds, so in equation 2, we pool the data for 2020 and add time fixed effects: where _Yijt_ is the outcome of interest for firm i in country j at time t. _Femaleijt_ is a dummy variable equal to 1 if the business owner is female; 0 if male. _Xijt_ is a set of controls for firm and entrepreneur characteristics, _δr_ indicates region-of-the-world fixed effects, _αt_ are time fixed effects in the form of the survey wave dummy variables. _εijt_ is the error term.

Next, we proceed to estimate the effect of school closures. To do this, we add the UNESCO school closure data and interact school closure with female business ownership:

> 27Country fixed effects are not included since there is low variation in the school closure policy across time for each country.

16
following example of part-time work: a low-skilled woman employed as a house cleaner, who must commute to a neighborhood with high socioeconomic status. Before the free rides program, she has a time-consuming commute on foot. This leads to an

> 17We use the PoI section data to identify husbands and wives, and the InP section data to determine individuals’ average monthly wages between January and March 2021, the three months prior to the scheme’s implementation. After matching data from these two sections, 21% of the observations did not respond to the income survey, raising concerns about potential selection bias. However, over 70% of those who failed to report income did so because interviewers were unable to reach the households during the designated time span. Among the matched sample with income observations, about 99% of the households reported the husband’s wage as being higher than or equal to the wife’s. In these households, husbands’ wages are, on average, twice as high as those of their wives.

> 18Fletcher, Pande and Moore (2017) show that the types of jobs Indian women report wanting vary by age, but are primarily of a part-time nature, reflecting the demands of other household responsibilities, particularly in the context of marriage and childbearing. 73% of women willing to take a job prefer regular, part-time work while only 22% report wanting regular, full-time work; the remaining 5% want a mixture of only occasional full or part-time work.

14
Policy Research Working Paper 6398

# **Abstract**

In this paper, the effect of proximity to multinational exporters on the creation of new export linkages (the extensive margin of trade) is debated. Using panel data from Chinese customs for 1997–2007, the capacity for Chinese domestic firms to begin exporting new varieties to new markets is shown to respond positively to the export activity of neighboring foreign firms. These spillovers are shown to be product and country specific. This conclusion is robust to fixed effects and instrumental variable specifications that control for both supply and demand shocks that could bias the estimations. The impact is sizable. The marginal impact of productcountry-specific foreign export spillovers is five times as large as the effect of a 10 percent increase in the demand for the product in the destination country. Foreign export spillovers are also shown to be primarily limited to ordinary trade activities. Overall, our findings suggest that even for a country with an important cost-advantage such as China, there is room for initiatives from policymakers that will diffuse best practices regarding export experience among exporters.

This paper is a product of the Partnerships, Capacity Building Unit, Development Economics Vice Presidency. 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 florian.mayneris@uclouvain.be and sandraponcet@cepii.fr.

_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
>6</sup> .

> 6For the random sample of households to whom we administered the household survey, we also asked how many assemblies a household member was sent to within the last year. Across our more than 8,000 households, less than 3% did not send a representative to a single assembly with in the past year. While households were asked about all assemblies, the leaders were responding about the most recent assembly, so these numbers are not necessarily inconsistent. Although this is quite a small number, we run a basic probit regression with non-attendance as the dependent variable and the available household characteristics as covariates (results shown in Table A5). Broadly speaking, non-attendance is greater for older and less educated households.

10
estimates of the short-run gains closing employment gender gaps while keeping the capital stock fixed (not produced in Pennings (2022)).

As the differences between long-run and short-run estimates are often large, we then study the transitional dynamics to 2050 (the medium-term) using the World Bank Long Term Growth Model (LTGM) of Loayza and Pennings (2022). The LTGM also allows for a slow-but-steady pace of increase in female employment rates. As around half of the countries in MENA are resource-rich, we simulate growth paths for these countries using the Natural Resource Extension of the Long Term Growth Model (LTGM-NR) of Loayza et al. (2022). The medium-run economic gains of closing gender employment gaps in this extension tend to be reduced because resource sectors are not in general labor intensive.

Finally, because gender gaps in employment are often larger for the non-college educated, and education levels among women in MENA have been rising rapidly, we calculate the effects of closing gender employment in a model with capital-skill complementarities (CSC) where closing gender gaps in employment rates could generate an additional boost in the accumulation of physical capital. This model also helps us to consider potential distributional effects through changes in the wage rates of unskilled and skilled workers.

In each of the three models—GEGI, LTGM and CSC—we first posit a production function and calibrate the model to a benchmark (MENA countries or the US). We then simulate the effect of closing the _same_ gender gap in employment rates, which makes our estimates comparable across models. In each case, we present the size of the increase in output per person relative to the baseline (in the absence of the policy change). We then study the role of specific assumptions in explaining the magnitude of the effects. To measure employment rates, we use the data on employment-to-population ratios from Pennings (2022), with the share of workers across different levels of schooling from national estimates in ILOSTAT (for those MENA countries where the data is available).

**
**|
|Labor market regulation index (EFW)|||||||
|Overall index|103|-0.0474|-0.0400|-0.0662|0.1265*|0.1086|
|Labor regulations and minimum wage|103|0.0781|0.0192|0.1199**|0.1658***|0.1136***|
|Firms identifying major constraint in (percent of firms,_En_|_terprise Survey_)||||||
|Tax rate|95|-0.0134***|-0.0132**|-0.0127***|-0.0069|-0.0065|
|Tax administration|95|-0.0134**|-0.0146**|-0.0106**|-0.0102*|-0.0099|
|Access to land|95|-0.0037|0.0004|-0.0060|-0.0270***|-0.0233***|
|Political instability|95|-0.0108**|-0.0155***|-0.0053|-0.0072**|-0.0107***|
|Corruption|95|-0.0094*|-0.0152***|-0.0021|-0.0056|-0.0083*|
|Access to finance|95|-0.0032|0.0036|-0.0086*|-0.0200***|-0.0150***|
|Source of finance for firm working capital (percent of wo<br>|rking capital,_Ente_<br>|_rprise Survey_)<br>|||||
|Internal fund|95|0.0054|0.0075|
school, and if she makes that choice, does her daughter actually attend school? If an outcome needs explaining, the ME framework suggests collecting data on assets and institutions as these are the factors most strongly associated with empowerment.

Taken from empirical work on inclusion in local elected bodies in India, box 3 illustrates the complex relationships between assets and opportunity structure.

- 1.4 Where Empowerment Takes Place—Domains and Levels

Using agency and opportunity structure to frame analysis of empowerment is helpful, but leads to two further questions. First, does a person’s capacity to make effective choices vary according to _what_ he or she is doing? Second, does empowerment vary according to the _level_ at which a person is acting? As box 3 illustrates, the answer to both questions is yes.

# **Box 3.  The Importance of Assets and Opportunity Structure to Effective Political Choice in India**

[Elected] representatives who are landless participate [in local elected body meetings] to a significantly lesser extent than those who own some land. As the landless are dependent economically, they are therefore less likely to raise dissenting opinions against their potential employers in the village—a conclusion that is also supported by case study data. Education and access to information also significantly associate with participation among elected representatives. Every additional year of education tends on average to raise representatives’ participation by more than two-and-a-half percentage points. A representative who has ten years of education scores on average 27 percentage points higher on this scale compared to another who has no formal education. Similarly, higher access to information is associated with greater participation among representatives by almost three percentage points, on average, for each additional source of information that they consult.

Respondents stated that individual benefits [from the elected body—the Panchayat] could be accessed only by people who had a relationship with the Sarpanch’s [president’s] family. Such relationships were based on frequent labor work for the Sarpanch and kin, purchasing goods from shops owned by them
17

# **Table 4.5: Rural/Urban Pattern of Real Household Per Capita Expenditures by Geographic Region**

|||**RU**|**RAL**||**UR**|**BAN**|
|---|---|---|---|---|---|---|
|**Region**|**1985/86**|**1992/93**|**Percentage change**|**1985/86**|**1992/93**|**Percentage change**|
|Northern|476.58|629.75|32.14|682.63|643.4|-5.75|
|Middle Belt|<br>488.44|766.11|56.85|631.74|732.67|15.98|
|Southern|607.68|936.70|54.14|732.98|931.78|27.12|
|Nigeria|531.28|779.96|46.81|700.35|812.95|16.08|
|Source: NCS,|1985/86 and 1|992/93.|||||

# **4.2 Evolution of Regional Poverty in Nigeria**

This section examines the evolution of poverty between 1985 and 1992. In analyzing the extent of poverty, it would generally be preferable to use individuals rather than household as the unit of analysis. Re-weighting the data according to household size is an alternative, but this makes the assumption that consumption is evenly distributed within the households. Given that there is inadequate information to construct adult equivalence scales, Average per capita expenditure (PCE) is used as the basis for poverty analysis.

The evolution of regional poverty is shown in Table 4.6.
# _4.1. The dataset_

We use data collected during four rounds of the DHS in Ghana: 1993-94 (5,822 households surveyed), 1998-99 (6,003 households), 2003 (6,251 households), 2008 (11,778 households).<sup>6</sup> The four rounds include data for each household on the main source of drinking water and the time it takes to walk to this source, fetch water, and return. It is thus a perround-trip measure. The number of trips, by each household per day, to collect water is not available in the data. Characteristics of all household members are also available, in particular age, sex and whether each member is or is not in school. The information available for each household however differs somewhat from one round to the other. Each household belongs to a unique cluster which is spatially identified by GPS coordinates data. There were 400 such clusters in 1993-94 and 1998-99, and 412 clusters in 2003 and in 2008.

These four rounds do not represent a pure panel, as the households surveyed in these four rounds are not identical. However, and as will be explained in the next paragraph, the GPS coordinates data still allow us to build a panel of clusters.

# _4.2. Using the GPS coordinates to build a panel of communities_

The DHS data provide GPS coordinates of the surveyed clusters in each of the four rounds (1993-94, 1998-99, 2003 and 2008). For the 2008 sample, GPS coordinates are missing for seven clusters, leaving us with a total of 405 GPS-identified clusters for that year. For each of these clusters we identify the closest neighbor (belonging to the same region) in the other three rounds by calculating great distance circles between all pairs of clusters.<sup>7</sup> Table 1 reports the average distance (in miles) between two matched clusters in each region.<sup>8</sup> For example, in the
00|-1.80|-1.80|
|Works/Not in paid job<br>|2.90|0.18<br>|3.08|
|Homework time|1.22|1.85|3.07|
|Highest education of parent|-0.45|-1.62|-2.07|
|Both parents born/not born in country<br>|0.46|0.43<br>|0.89<br>|
|Books at home|0.10|-0.16|-0.06|
|**Total**|**3.47**|**-1.12**|**2.35**|
|School characteristics||||
|Total enrolment, grade 8|3.29|-5.79|-2.50|
|Community size|0.06|-1.76|-1.70|
|Proportion of disadvantaged students|-0.16|2.18|2.02|
|Ability grouping yes/no|-0.07|0.86|0.79|
|Remedial lesson in Math Yes/no|0.04|0.91|0.95|
|Severe absenteeism in school yes/no|0.68|4.50|5.18|
|Shortage of buildings yeas/no|0.53|-0.14|0.39|
|Shortage of teachers yeas/no|0.00|0.17|0.17|
|Index of good attendance|-1.12|-3.18|-4.30|
|**Total**|**3.25**|**-2.25**|**1.00**|
|Teacher characteristics|||
and 2010, coincide with the years in which under-five population data are compiled for each country in the sample.

We create regional averages of stunting measures weighted by the under-five population of each country of the middle of each reference period. Following the World Bank regional classification, we divide the countries in our sample into six regions: East Asia and Pacific (EAP), Europe and Central Asia (ECA), Latin America & Caribbean (LAC), Middle East & North Africa (MNA), South Asia (SAS), and Sub-Saharan Africa (SSA). These regional averages are presented in Figure 3 using two graphs that show (i) headcount rates for the different regions, and (ii) gap rates for the regions.

Figure 3: Regional trends of stunting headcount and stunting gap <!-- Start of picture text --> Stunting headcount<br>70%<br>60%<br>50%<br>40%<br>30%<br>20%<br>10%<br>0%<br>1995 2000 2005 2010<br>East Asia and Pacific Europe and Central Asia<br>Latin America & Carribean Middle East and North Africa<br>South Asia Sub‐Saharan Africa<br><!-- End of picture text --> 18
|[0.013]***|
|Observations|890|918|890|918|2,627|2,376|2,629|2,382|
|Countries|22|22|22|22|66|63|66|63|

Note: Dependent variable is consumption growth. GMM Dynamic Panel Estimates. Lags 2-4 of consumption growth, all right hand side variables and lagged saving are used as instruments. De Jure refers to financial integration measures of Chinn-Ito and Quinn. _De Facto_ measures refer to financial integration measures such as stocks of assets and liabilities from Lane and Milesi-Ferretti dataset.

23
the protected area and whether its strategic design and planning promote effective operations [77]. AP management increases this dimension by 0.683 standard deviations, reflecting AP’s proactive and robust planning approach, although this effect is not statistically significant due to the limited METT data available (Table 1).

**Capacity and Resources:** This dimension relates to the availability and management of resources, including staff count and budget. Effective management requires adequate resources and capacities, encompassing well-trained staff and sufficient equipment to enforce regulations, diminish threats, and enhance ecological conditions [76, 77]. We find an increase of 0.581 standard deviations in this category due to AP management, signifying AP’s effective fundraising and resource management (Table 1). However, this effect is also not statistically significant.

**Monitoring and Enforcement Systems:** This category assesses the enforcement capacity of the protected area, evaluates if its legal framework permits action against the protected area’s primary threats, and measures understanding of the biological conditions within the protected area. AP management significantly improves this dimension, with an increase of 0.926 standard deviations (Table 1). This result aligns with AP’s focus on law enforcement and monitoring.

**Decision-Making Inclusiveness:** This dimension pertains to stakeholder involvement and their influence on management decisions. Including diverse stakeholders can improve the perceived legitimacy of the protected area and facilitate its

11
# 3. Summary

The framework proposed for measuring empowerment is a simple one. It comprises three core concepts: agency, opportunity structure, and degree of empowerment. These are further refined into clusters of indicators. A broad range of assets are used as indicators of agency. Measurement of the presence and operation of formal and informal institutions provides indicators of opportunity structure. The existence of choice, the use of choice, and the effectiveness of choice are used as indicators of the degree of empowerment a person or group experiences. For ease of data collection and analysis, three domains (state, market, and society) are identified and divided into a number of sub-domains, or stages in or upon which actors live out their lives. These sub-domains are differentiated according to the level at which actors operate—the macro, intermediary, and local levels.

Using this framework, empowerment can be measured within projects or interventions. It can also be used as the basis for in-depth research, for national-level monitoring, and, with certain caveats, for comparing the status of and changes in empowerment across countries. While the framework is simple and easily applied, it is also comprehensive in that it enables an assessment of a person’s or group’s empowerment across the different domains in which they act. In how many different domains and at how many different levels empowerment is assessed depends on the nature of the intervention and the scope of the measurement exercise. As demonstrated in the Ethiopia WDIP indicators (annex 2, table 1), empowerment is measured in five of the eight sub-domains, but in the Honduras Community-Based Education Project (annex 2, table 3), empowerment is measured in only two sub-domains. How many domains an in-depth research exercise focuses on depends on the purpose of the study and the specific country context. As outlined in section 2.3, national-level monitoring is recommended for all sub-domains.

This paper also introduces indicators and a preliminary household survey instrument that can be used to measure and track empowerment within countries.
product features are compatible with those imported from elsewhere by India.

The statistics of the second largest economy, Pakistan, suggest a similar scenario. The region, which barely accounts for 2 percent share of Pakistan’s imports, overall demonstrates a negligible capacity to fulfill its import needs. The RCA indices show prospects that a limited portion of Pakistan’s import requirements

> 24 Ideally, comparative advantage should be measured in an environment in which neither external trade constraints (like tariff and non-tariff barriers, or preferential access to export markets) distort an individual country’s “real” export structure, or where domestic market interventions (such as subsidies) in the exporting country have sector-specific effects or a general anti-export bias.

> 25 The major 50 imports at SITC 4-digit level represent between 66 and 96 percent of total imports of South Asian countries. The product mix in 1998 is largely representative of latter 1990s.  Readers must also note that the product differentiation within each of the SITC 4-digit classification (identified at Harmonized Classification 6-digit level) may provide part of an explanation for the apparent discrepancy between similar products that have successful global exports, but have no effectual intra-regional trade.

29
Bank of Greece, Ministry of Finance, IMF and OECD data.

# **3.4 The Search for Efficiency and International Integration (1996-2000)**

The attractiveness of government securities to domestic non-bank investors peaked in 1996 when they accounted for 79 percent of new issues (Table 3.7). A drastic change occurred in 1997 that was intensified in the remaining years of the decade. Institutional investors from other European countries became attracted to the high yields offered by Greek government securities, an attraction that was reinforced by the prospect of large capital gains that were likely to ensue from falling interest rates linked to economic convergence and eventual entry of Greece into the euro zone. The strong political commitment to achieve economic convergence and join the euro zone strengthened the credibility of government policy and paved the way for the successful integration with the euro markets.

Between 1997 and 2000, foreign investors acquired debt securities that amounted to 120 percent of new borrowings, while domestic non-bank investors sold securities equal to 65 percent of the same total (Table 3.7). Most of the increase in the holdings of foreign investors concerned drachma-denominated securities that were issued in the domestic market. During this period foreign debt rose by less than one-fifth of the total increase in the holdings of foreign investors.

> 20 This probably understates the total holdings of pension funds because it includes only those investments that are effected through the central bank and are reported in its annual report. It excludes any direct investments by pension funds that do not use the services of the central bank.

32