rafmacalaba/data-use-mentions-extended huggingface dataset:
15 specialized technology through their association with international firms. In contrast, static scale economies are out of reach to small countries.

63. The available information does not allow us to discard the hypothesis that there also exist significant scale economies in collection over the number of contributors and employers observed in small countries. For example, the fact that all Chilean pension fund administrators (AFPs) with less than 100,000 members have decided not to integrate into collection (to avoid the fixed cost of the specialized technology) does not settle the issue of whether static or dynamic scale economies are present. This evidence may be representative of a past when Chile was the only country with competitive pension management companies, or it may show the importance of static scale economies. Evidence of these scale economies may be seen in the fact that SERVIPAG, a specialized Chilean collection company that services financial companies, utilities, and small pension fund management companies, has not been challenged by large-scale entry of other firms into this market. However, this same evidence may be seen as the result of restrictions on bank and AFP entry into this specialized business.

64. Economies of scale do obtain in a small country. In this case, both conditions for natural monopoly (sunk and fixed costs) would be present. If the relative size of these economies were substantial, competition among pension management companies that are vertically integrated into collections would favor the largest ones at the local level. In a small country, this process would lead to a concentrated market structure and higher charges, and to concentration of the trustee function. Given the negative impact of this latter outcome on the political risk affecting pensions, there may be a case for the government to intervene in collections.

65. The required intervention would be to prohibit vertical integration of collection and processing of contributions with the other functions. The gain from prohibiting vertical integration is that it prevents concentration of the trustee function. However, forced disintegration does impose costs. For example, looking in the membership archives held
Policy Research Working Paper 10012

# **Abstract**

This paper estimates the impact of a large negative childcare shock on gender gaps in entrepreneurship using the shock created by national COVID-19 school closure policies. The paper leverages a unique data set of monthly enterprise data collected from a repeated cross-section of business owners across 50 countries via Facebook throughout 2020 and in 2021. The paper shows that, globally, female-led firms were, on average, 4 percentage points more likely to close their business and experienced larger revenue declines than male-led firms during the COVID-19 pandemic in 2020 (male firms closed at a rate of 17 percent in 2020, and 12 percent in 2021). The gender gap in firm closures persisted into 2021. The closing of schools, a key part of the care infrastructure, led to higher business closures, and women with children were more likely to close their business in response to a school closure policy than men with children. Female entrepreneurs were found to take on a greater share of the increase in the domestic and care work burden than male entrepreneurs. Finally, the paper finds that women entrepreneurs in societies with more conservative norms with respect to gender equality were significantly more likely to close their business and increase the time spent on domestic and care responsibilities in response to a school closure policy, relative to women in more liberal societies. The paper provides global evidence of a motherhood penalty and childcare constraint to help explain gender inequalities in an entrepreneurship context.

This paper is a product of the Africa Region, Gender Innovation Lab and the Development Research 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 mgoldstein@worldbank.org; pgonzalezmartine@worldbank.org; spapineni@worldbank.org; and jwimpey@worldbank.org.

_The Policy
shown dynamic growth from 2001 to 2006.

These broad patterns mask the varying trends in female entrepreneurship, employment, and gender segmentation across leading versus lagging regions as well as among the industries within manufacturing and services. Our state and industry level descriptive statistics suggest that the states and industries with higher female entrepreneurship shares are also the ones with higher female participation shares in employment. Further, there is a positive association between female involvement in ownership or in employment and gender segmentation in female-led businesses. In general, the magnitude of this correlation is found to be stronger in unorganized manufacturing than in the services sector.

Among the correlates of female activity, we find that participation of women in both manufacturing and services is greatly influenced by larger working age populations and femaleto-male gender ratios in the local economy. Technology plays a vital role in reducing gender segmentation in the services industry relative to that in informal manufacturing. Across the board, we find a relatively higher importance of district level local infrastructure in determining female participation and in reducing gender segmentation among male-led plants.

> 5 Relatedly, Ghani, Kerr and O'Connell (2014) did some early parallel work in this regard with respect to female political set-asides.

> 6 Ghani, Mani and O'Connell (2013) document the substantial increase in female entrepreneurship in India’s unorganized manufacturing sector from 1994 to 2000.

4
worsening of living conditions for the bottom 15 percent of the population in years 2016 and 2017 with respect to 2015, but improving conditions in year 2018.<sup>9</sup> The unavailability of CP data from 2011/12 prevents a direct comparisons of consumption growth between CP and CES surveys.<sup>10</sup>

# **3. Survey-to-survey imputation**

As described in the previous section, none of the alternative surveys are fully comparable to the CES of 2011/12. The IHDS uses the same measure of consumption as the official surveys but is not nationally representative in recent years. The SCSs are nationally representative and cover a long period but use a different welfare aggregate. The PLB and CP surveys measure a different welfare aggregate and cover a shorter period, preventing a meaningful assessment of the trend in poverty since 2011/12.

In the absence of a comprehensive welfare aggregate covering the period after 2011/12, we use the survey-to-survey imputation methodology originally proposed by Elbers et al. (2003). We closely follow Newhouse and Vyas (2019), who apply this method to India over an earlier period. This method consists of imputing consumption into a survey without consumption data, based on the relationship between consumption and other household characteristics from a survey with consumption data. With the imputed consumption expenditure in the target survey, it is then possible to estimate poverty. A prerequisite for this method is that the two surveys involved in the exercise have a comparable set of explanatory variables. Here we use the Health SCS 2017/18 that includes a series of demographic, economic and locational characteristics that are also included in the previous rounds of the CES. A comparison of the available CES and SCS Health surveys is included in the Appendix.

## **3.1. Empirical Methodology**

This method predicts the conditional distribution of per capita expenditure, ych, for household, h, within cluster, c, of the target data set that is missing actual consumption
fixed income index IDXTES drawn up by Reveiz and León (2008). Additionally, state bond indices were constructed from the interest rate curves

> **49** The dynamics in question correspond with the Cholesky decomposition of an asset base with correlated shocks, and on that used  by Detemple et al. (2003, §VI.A) and Munk and Sørensen (2010).

> **50** This obeys the variance-covariance matrix of returns which tends not to be positively defined when a relatively high number of assets and their returns are highly correlated.

43
Table C.3: Baseline Parameters (continued)

|Parameter|Description|Units|Value|
|---|---|---|---|
|_✓_<sup>_e_</sup><br>0|Energy Technology Index in 2004||1.195|
|__<sup>_e_</sup>|Energy Technology Index Growth Rate||0.0225|
|_⇢e_|CES Parameter for Petroleum and Biofuels||0.5|
|_↵_<sup>_e_</sup>|Share of Biofuels in CES Function||0.09|
|_✓_<sup>_yw_</sup><br>0|Timber Processing Technology Index in 2004||1.52|
|__<sup>_yw_</sup>|Timber Processing Technology Growth Rate||0.0225|
|_c_<sup>_o,yw_</sup>|Timber Processing Cost|share of _X_<sup>_O_</sup><br>_t_|0.0224|
|_✓_<sup>_r_</sup><br>|Ecosystem Services Technology Index||0.71|
|_↵_<sup>_A,r_</sup><br>|Share of Agricultural Land in CES Function||0.02|
|_↵_<sup>_P,r_</sup><br>|Share of Pasture Land in CES Function||0.14|
|_↵_<sup>_C,r_</sup>|Share of Managed Forest Lands in CES<br>Function||0.26|
|_⇢r_|CES Parameter for Ecosystem Services||0.123|
|_✓_<sup>_R_</sup>|E↵ectiveness Index of Protected Lands||10|
|_c_<sup
**Figure 4: Volatility of Output Gap vs.  Regulation Indices**

<!-- Start of picture text --> Overall Regulation Product Market Regulation<br>Correlation: 0.41*** SLE Correlation: 0.43*** SLE<br>TGO TGO<br>PNGIDN MWI IDN MWIPNG<br>THA THA<br>MYS KORTUR JORZWEMAR HTI TURKORMYS JORMARZWE HTI<br>ZMB ARG ZMBARG<br>PER NERVEN COG PER VENNER COG<br>URY CRI MEXNICCIV ECU SYR URY MEXCRI NICCIV ECUSYR<br>USAGBR CHECANAUSDNKIRLNLDISL FINSWENORAUT JPNBELCHLJAMESPBWAISRPRTITAFRAZAFGRCTTOLKAKENCOLSLV GTMGHABGDDOMPHLPAKINDHNDPANTUNSENNGABOLPRYEGYBRAGMBIRNMDG BFA GBRNLDUSACANDNKFINAUSSWEIRLCHEBELISLNORAUTJPNESPITAPRT GRCISRFRACHL JAMZAFBWACOLLKATTOSLVKENPANTUNGTMPAKGHAINDPHLEGYBRABGDSENHNDDOMBOLPRYNGAIRNGMBMDGBFA<br>.2 .3 .4 .5 .6 .7 0 .2 .4 .6 .8<br>Overall Regulation Index Product Market Regulation Index<br>Labor Regulation Fiscal Burden<br>Correlation: 0.16 SLE Correlation: -0.25** SLE<br>TGO TGO<br>PNG IDN MWI IDN PNG MWI<br>THA THA<br>MYSZWE KORMAR TUR JORHTI HTI MYS KORJOR TURMAR ZWE<br>ZMB ARG ARG ZMB<br>NER COGPERVEN NERPERVEN COG<br>URYSYR CIV ECU CRINIC MEX ECU URYCRI NICMEX CIV SYR<br>USA KENGBRBWATTOJAMGHAAUTCANZAFJPNISRCHEDNKAUSNGALKA BGDIRNINDDOMFRACHLSENNORIRLPAKHNDCOLTUNNLDBELPHLEGYGTMSWEBFA BOLGRCITAESPSLVPRYMDGFIN PANBRAPRT PRYSLVDOMBOLGTMCHLBGDMDHNDNGA G JAMMBPHLCHE COLBWALKABFAPANTTOKENPAKBRAISLUSAIRLGHASENGBRIND NORAUSIRNESPGRCZAFPRTFINTUNSWEEGYCANAUTJPNDNKNLDISRFRA ITABEL<br>0 .2 Labor Regulation Index.4 .6 .8 0 .2 Fiscal Burden Index.4 .6 .8 1<br>.06 .06<br>.04 .04<br>Volatility of output gap .02 Volatility of output gap .02<br>0 0<br>.06 .06<br>.04 .04<br>Volatility of output gap .02 Volatility of output gap .02<br>0 0<br><!-- End of picture text --> _Note: *, **, and *** denote significance at the 10%, 5%, and 1% level
are larger in wealthier areas than in poorer ones, suggesting that the price‐wealth gradient does not only represent cross‐subsidization.

A few other studies have documented positive relationships between patients’ wealth and the quality of health services received in low‐ and middle‐income countries. Sharma et al. (2017) show that in Kenya, health facilities located in more impoverished areas have worse infrastructure and provide lower quality antenatal and delivery care. In Mexico, Barber, Bertozzi, and Gertler (2007) find that poorer women reported having received fewer procedures in their antenatal consultations, and that indigenous women receive particularly low levels of care. Barber, Gertler, and Harimurti (2007) find that in Indonesia the poor and the wealthy have access to providers of similar knowledge levels, but that poorer women report receiving worse quality of prenatal care. The authors conclude that these results might suggest discrimination against the poor due to informal payments or social and educational differences between providers and patients. Das and Mohpal (2016) show that socioeconomic status is correlated with access to and use of more knowledgeable health care providers in the Indian state of Madhya Pradesh. However, this relationship was driven by differences across villages; within villages, better‐off and worse‐off households use the services of equally knowledgeable providers.

This paper contributes to the literature in several ways. First, to our knowledge, this is the first study that formally decomposes quality differentials into facility selection and within‐facility discrimination mechanisms. Second, this is the first study to combine direct clinical observations of patient‐provider interactions with maternal recall data. The combination of three data sources—clinical observations, patient exit interviews conducted immediately following the observations, and household‐based interviews with women who recently gave birth—allows us not only to measure differential access, but also to measure objectively the quality of services received. Third, the exit interviews that were collected allow us to assess directly the out‐of‐pocket payments and their relationship to the quality of care
Policy Research Working Paper 8684

# **Abstract**

Toilet ownership in India has grown in recent years, but open defecation can persist even when rural households own latrines. There are at least two pathways through which social norms inhibit the use of toilets in rural India: (i) beliefs/expectations that others do not use toilets or latrines or find open defecation unacceptable; and (ii) beliefs about ritual notions of purity that dissociate latrines from cleanliness. A survey in Uttar Pradesh, India, finds a positive correlation between latrine use and social norms at baseline. To confront these, an information campaign was piloted to test the effectiveness of rebranding latrine use and promoting positive social norms. The intervention, which made information about growing latrine use among latrine owners more salient, reduced open defecation practices across all treatment households, with average latrine use score in treatment villages increasing by up to 11 percent, relative to baseline. Large improvements were also observed in pro-latrine beliefs. This suggests that low-cost information campaigns can effectively improve pro-latrine beliefs and practices, as well as shift perceptions of why many people still find open defecation acceptable. Measuring social norms as described can help diagnose barriers to reducing open defecation, contribute to the quality of large-scale surveys, and make development interventions more sustainable.

This paper is a product of the Mind, Behavior, and Development (eMBeD) Unit, 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/ research. The authors may be contacted at vgauri@worldbank.org, trahman4@worldbank.org, and isen@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
aggregate effect of electrification conditional on outages reported in the sample is associated with a 16 percent increase in expenditure for households in the bottom quantile but a 6.1 percent increase for those in the top quantile. The results are robust in models with and without controls for power outages (columns 2 and 1, respectively). This result suggests that the return to electrification is higher for poorer households in India. The distribution of the marginal effects of electrification on households’ expenditure by per capita expenditure quantile (when outages are controlled for) is further shown in figure 3. The marginal benefit of electrification gradually decreases as one moves from the 10th to the 50th quantile. From the 50th quantile onwards, the marginal benefit drops rather quickly and even becomes statistically insignificant.

This finding is somewhat different from those reported by Khandker et al. (2014). Using cross‐sectional data from the IHDS for 2005, Khandker et al. (2014) find that a larger share of the benefits from rural electrification accrues to wealthier households rather than to poorer ones. Because we use panel data from the IHDS that span seven years, we report longer‐term effects of electrification on the same households. The difference in findings suggests a possibility that over time the rate of return from electrification has declined among richer households while poorer households have caught up by diversifying their use of electricity.

# **VII. Conclusion**

Universal access to modern energy services is one of the three objectives of the Sustainable Energy for All (SE4ALL) program launched by the United Nations in 2011. Access to electricity not only brings better‐quality lighting; it also is a key driver of social and economic development. Using household‐level panel data from a nationally representative survey conducted in 2005 and 2012, this study estimates the impact of rural electrification on a broad range of household welfare measures in India.

We find that electrification is associated with substantial improvements in households’ income, expenditure, employment, and educational achievement. But the size of
the sisters of HRS<sup>2</sup> -serial surveys, CHARLS is rich in information ideal for research on transfers. In the interview, the respondents were asked whether they had received transfers from and/or given transfers to each of their children, and if so the corresponding amount.<sup>3</sup> Transfers are specified in two categories: financial transfers<sup>4</sup> and in-kind transfers (mostly in the form of goods), both of which are non-time transfers.

The survey was conducted in Zhejiang and Gansu, representing two very different development levels in China (see the two provinces on the China map of Figure 1). Zhejiang, a southeast coastal province, has been enjoying rapid economic growth since the implementation of the reform policies, and now it is one of the richest areas in China. Gansu, by contrast, which is located in the hinterland of Northwest China, is one of the poorest provinces, the development of which has been constrained by its inclement natural environment and geographic distance from commercial centers. The two differing economic and natural environments contribute to different living standards of residents and potentially influence intergenerational transfers. Both provinces had major declines in fertility and mortality, with the fertility decline accelerating in the late 1970s, when stronger family planning policies were introduced (China's Population and Employment Statistics Yearbook, 2009).

> 2 HRS: Health and Retirement Study.

> 3 Amounts are asked if financial transfers occur, and frequencies are asked if time transfers occur. In this paper, we only focus on financial transfers.

> 4 Financial transfers are further classified into two types: regular financial transfers and non-regular financial transfers. Non-regular transfers are those made at special times of the year such as Spring Festival or a parent’s birthday.

8
Figure 2: Changes in per capita caloric intake and Total Energy Expenditure by state, 1983-2012 <!-- Start of picture text --> 1983-2005 2005-2012<br>Andhra Pradesh<br>Kerala<br>Punjab<br>RajasthanHaryana<br>West Bengal<br>Tamil Nadu Bihar<br>Kerala<br>OrissaAssam<br>Uttar Pradesh<br>MaharashtraOrissa<br>Tamil NaduWest Bengal<br>Uttar PradeshBihar Delhi Gujarat Karnataka DelhiAssamMadhya Pradesh<br>MaharashtraAndhra Pradesh<br>Karnataka<br>Haryana Gujarat<br>Madhya PradeshPunjab<br>Rajasthan<br>-100 0 100 200 -150 -100 -50 0 50<br>Change in mean TEE per capita Change in mean TEE per capita<br>State Linear fit State Linear fit<br>45 degree line 45 degree line<br>400<br>50<br>200<br>0<br>0 -50<br>-200 -100<br>Change in mean caloric intake per capita Change in mean caloric intake per capita<br>-400 -150<br><!-- End of picture text --> _Source:_ Authors’ analysis based on data from 1998-1999 India Time-Use Survey, National Family Health Survey rounds 2, 3 and 4, and National Sample Survey (NSS) rounds 38, 43, 50, 55, 61, 66, and 68. _Note:_ State-level average Total Energy Expenditure (TEE) is imputed using NSS Schedule 10 as described in the text and caloric intake per capita is the authors’ estimate using NSS Schedule 1. The scatter plot excludes states with population below 10 million for readability.

28
# **5. Conclusion**

We present two main findings. The first is that in four of the five sectors for which we have data, donor agencies’ project outcome ratings provide no information as to the long-run impact of their projects. It follows that they are a poor measure of aid effectiveness, though they may still be useful for monitoring other aspects of project performance. Our second finding is that the single most important correlate of impact is what appears to be a proxy for the degree of contextualization of project design to country circumstances, far ahead of country institutional quality, project size or other commonly identified factors. Our methods enable us to explain around 70% of the residual variance in development outcomes, a much higher proportion than previous analyses of the determinants of project outcome ratings.

These findings have significant implications for how we think about project preparation. Further work is needed to establish what the embeddings mean. But our results at least suggest that greater attention be paid to country contextualization. This does not appear to correlate with the standard determinants of project quality identified in the literature, such as project manager’s age, education or prior experience. Nor does it correlate with whether the staff is based in headquarters or in the field - consistent with IEG’s own assessment that corporate field staffing targets have failed to ensure that decentralization is tailored to country and program needs or applied to areas where it can bring the most benefits (Independent Evaluation Group 2016). While we find some evidence that the length of project preparation and existence of prior analytical work are positively associated with impact, we are unable to say to what extent they matter.

Our analysis also has implications for how we think about project evaluation. On the one hand, it is encouraging that ICRs provide sufficient information to accurately predict the likely contribution of projects to long-run outcomes. On the other hand, the incorporation of this information into summary ratings appears to have resulted in them becoming disassociated from development impact. This may warrant a more