rafmacalaba/data-use-mentions-extended huggingface dataset:
Table 4: Rwanda- correlations between IPV and respondent characteristics across methods

||Q: husband|pushed or t|hrown you|Method<br>t|differences: P-<br>ests of differen|values from<br>ces|
|---|---|---|---|---|---|---|
|Variable|(1)<br>List|(2)<br>F2F|(3)<br>ACASI|(1)-(2)<br>List-F2F|(1)-(3)<br>List-ACASI|(3)-(2)<br>ACASI-F2F|
|Vulnerability index|0.23***<br>(0.08)|0.06***<br>(0.02)|0.05*<br>(0.03)|0.07|0.05|0.65|
|Unequal village gender norms index|0.37***<br>(0.10)|0.03<br>(0.03)|0.04<br>(0.03)|0.00|0.00|0.75|
|Relationship quality index|0.03<br>(0.05)|-0.07***<br>(0.01)|-0.04***<br>(0.01)|0.06|0.17|0.18|
|Gender engagement index|-0.10**<br>(0.04)|-0.02*<br>(0.01)|-0.01<br>(0.01)|0.11|0.07|0.48|
|Progressive gender attitudes index
. _Journal of Public Economics_ , 95(7): 476-487.

<mark>Alkire, S., Foster, J. E., Seth, S., Santos, M. E., Roche, J. M., and Ballon, P. (2015).</mark> _<mark>Multidimensional Poverty Measurement and Analysis</mark>_ <mark>. Oxford: Oxford University Press.</mark> Alkire, S. and Jahan, S. (2018). ‘The new global MPI 2018: Aligning with the Sustainable Development Goals’, OPHI Working Paper 121, University of Oxford.

Alkire, S., Kanagaratnam, U., and Suppa, N. (2020). ‘The global Multidimensional Poverty Index (MPI) 2020’, OPHI MPI Methodological Note 49, Oxford Poverty and Human Development Initiative, University of Oxford.

<mark>Appleton, S. (1996). Women-headed households and household welfare: An empirical deconstruction for Uganda.</mark> _<mark>World Development</mark>_ <mark>,</mark> _<mark>24</mark>_ <mark>(12), 1811-1827.</mark> Assad, R., Krafft, C., & Pastoor, I. (2021). Gender Role Attitudes and Gendered Outcomes: Syrian Refugee Adolescents in Jordan. World Bank and Policy Research Working Paper, forthcoming. World Bank Group.

29
is important to consider the availability of existing social programs, administrative capacity, fiscal soundness of the budgets, as well as the political context (Yemtsov et al., forthcoming). Such compensatory measures should be tailored to the likely impact of the reform on a variety of different groups.

**Box 1: Indonesia’s subsidy reform experience**

Indonesia is one of the flagship examples of successful subsidy reform. In 2005, the increase in international oil prices gave way to ambitious subsidy reforms, which proceeded in two stages (Clements et. al., 2013). In March 2005, the government raised gasoline and diesel prices by 33 and 27 percent respectively. Kerosene, being the least regressive of the subsidized goods, was initially left unchanged. In the second round of reform later that year, all fuel prices were increased, and kerosene prices almost doubled as a result. Had there not been a proper compensation plan, it is estimated that these price hikes (particularly of kerosene) would have caused the poverty headcount index to rise by 5.6 percentage points (Yemtsov et al., forthcoming). To mitigate such drastic impacts on the poor and near‐poor households, the government introduced a two‐pronged compensation package, reallocating a significant share of the savings from the subsidy reform towards social protection. A temporary (two‐year) unconditional cash transfer introduced in conjunction with the reforms, _Subsidi Langsung Tunai,_ was provided to the poorest 35 percent of the population (well above the 16 percent poverty line), in order to protect the near‐poor and minimize political unrest (Beaton and Lontoh, 2010). What was then the world’s largest UCT program proved to be largely successful in reaching the poor; the poorest quintile received 21 percent of the benefits, while the second, third and fourth quintiles received a total of 40 percent. The compensation package also included education, health and rural infrastructure programs for the poor (which were introduced later).

Cash
developing economies. If we recompute the gap, it declines to 2 _._ 2% for workers without college and 1 _._ 2% for workers with college. These are declines of 25% and 35 _._ 7% respectively. Thus, even under a scenario where all training is complete within 4 years, a significant gap in returns remains.

# **7. Conclusion**

In this paper, we provide additional global evidence that experience matters.

First, we studied wage-experience profiles and obtained returns to experience, and education, using data from 1,084 household surveys and census samples across 145 countries. Across many specifications, we found that returns to experience are strongly correlated with economic development and that workers in developed countries may accumulate twice more human capital at work than workers in developing countries.

Second, exploiting the fact that we were able to estimate returns to experience for more than 100 countries and multiple years of data during the period 1990-
br>Drought Extreme Flood Landslide Storm Wildfire<br>temperat<br>D. Number of disasters by region,<br>1981‐2017<br>100<br>90<br>80<br>70<br>60<br>50<br>40<br>30<br>20<br>10<br>0<br>EAP ECA LAC MENA SA SSA<br>Note: Regional median per period in blue. 25 th and 75 th percentiles are bottom<br>and top of box, respectively<br>No. weather related disasters<br><!-- End of picture text --> 30
planning and supervising the construction of new facilities and major rehabilitation of existing schools.<sup>22</sup> Besides employing RED fixed effects in our regressions, we aimed to directly account for differences in topdown accountability across schools by asking school directors and teachers specific questions about monitoring and possible penalties. Our main variables of interest are: the number of visits of RED representatives in the previous academic year (January-May 2009); whether the school director is subject to penalties if he/she underperforms (self-reported by school directors); whether teachers are subject to penalties if they underperform (self-reported by teachers); and the days of unjustified absence of teachers in the month of May 2009, as reported in the teachers‟ absence registry, in the schools where such a registry is kept.

63. To measure transparency, we report whether the school keeps a teacher absence register and if it publicly displays teachers‟ absence and students‟ performance in the final year examination. We also generate a measure of corruption in the appointment of school directors and teachers based on perceptions of all the surveyed stakeholders. Each respondent was asked to evaluate how often school directors (teachers) are appointed to posts based on personal connections rather than their qualifications, using a 5-item Likert scale, ranging from “never” (1) to “always (5). In each school we consider the proportion of respondents that answered “often” or “always” to the above questions.

# _2.b.4. Parent Involvement in Participatory “Bottom up” Accountability Structures_

> 22 The REDs are also responsible for teachers‟ salaries, which are paid using the total budget allocated by the MoES, and for the collection of information at the district level and transmitting this information to the Ministry. The local municipalities/communes have very limited responsibility for the delivery of education services. Under the current arrangements, they receive conditional transfers from the MoES, through the REDs, to cover teachers‟ salaries and scholarships for pupils in secondary schools.
whether the credit supports those _eligible_ for the financial incentive provided by the government. To this end, we examine impact heterogeneity by subsidy eligibility status, thereby analysing whether impacts are concentrated amongst subsidy ineligible or subsidy eligible households, or both. Matching the household survey data to the SBM administrative records allows us to obtain households’ official subsidy eligibility status, which is determined by both its VG classification and its official record of SBM baseline toilet ownership. Restricting the matched sample to MF client households that did not have a toilet at survey baseline (since these are the households targeted by the micro-credit and subsidy interventions) we estimate the following equation: where _SLv_ takes the value of 1 if the household lives in GP _v_ that was randomly assigned to the treatment group, and 0 otherwise. Dichotomous variables _SubsidyEligibleiv_ and _SubsidyIneligibleiv_ denote whether or not household _i_ is officially classified as being a subsidy eligible household. _Xiv_ is a vector of household-level controls that helps to increase power and precision.<sup>17</sup> Vector _Xiv_ also includes a dummy for whether or not a manual check revealed some uncertainty about the reliability of a particular match between a survey data record and an SBM administrative data record (see Section 3). We also control for a set of strata dummies _θv_ for GP _v_ . Standard errors are clustered at the GP level.

We estimate equation 1 for four main outcomes of interest _Yiv_ :(i) sanitation loan uptake, (ii) toilet ownership, (iii) toilet usage and open defecation, and (iv) subsidy uptake. Sanitation loan uptake is measured as a dichotomous variable using administrative data from the MFI. Toilet ownership is measured based on interviewer verified reports on toilet ownership by the survey respondent (usually the household head). Specifically, this variable takes a value of 1 if the respondent reports that the household owns a toilet, and the interviewer sees it; and 0 otherwise. We complement this measure with toilet ownership status captured in the 2016 SBM snapshot and use toilet construction date
Even among these 92 firms, 53% (unreported in the table) had a sufficient cash balance to cover their liquidity crunch. Thus, a very small percentage of the firms in the US sample had a positive increase in sales from 2009 to 2010 while the overall change in credit (short-term debt, long-term debt, net capital stock issuance, cash generated from cutting dividends and cash from investing and operating activities) was negative.<sup>23</sup>

# **_5.2 Firms’ Financing and Investment Decisions during Recovery – US Case_**

In this section we repeat the analysis in section 4.2 for the US case. We examine how positive and negative cash flow shocks affect firms’ investment, financing, and distribution decisions jointly, subject to the accounting identity that sources of cash equal uses of cash. We re-estimate the system of equations in (7) over 2006-2010 using a sample of US firms from Compustat. We start with the balanced sample of 3,338 firms and remove the top and bottom 1% outliers for all the variables in the system. To estimate the effects during the crisis and recovery periods separately, we estimate the system by including four time dummies for 2006-2007 (pre-crisis period), 2008 (crisis year), 2009 (crisis year) and 2010 (recovery year) and interactions of Operating cash flow (OCF) with each of the four dummies. In all regressions, we use de-meaned values of all variables (to proxy for firm fixed effects) and control for firm size (Log Total assets) and Tobin’s Q. The system is estimated as a seemingly unrelated regression (SURE) model subject to the constraints that across the system, in each year, the operating cash flow coefficients sum to one while the other coefficients sum to 0. That is, Σ Coefficient of OCF + Σ Coefficient of (OCF x 2006-2007 dummy) = 1; Σ Coefficient of OCF + Σ Coefficient of (OCF x 2008 dummy) = 1
|18.7|20.2|15.9|14.6|16.1|
|_difference_|_4.7_|_5.7_|_5.6_|_5.8_|_8.2_|_7.5_|

Source: Authors’ estimates from the NSS for urban women aged 25-55, who are wives of household head.

We expect a lower likelihood of employment for younger women, those belonging to nonSC/ST/OBC households and Muslim women. SC/ST women have been generally disadvantaged and are among the poorest; therefore, they are more likely to work compared to non-SC/ST women. They also tend to have weaker norms of male-female segregation (Das and Desai, 2003; Das 2006). Religion, however, plays a complex role and its negative effects on employment are stronger for Muslim women, due to a variety of reasons, of which lack of opportunities may be one (see Das 2005). We also add the husband’s education and employment type as a proxy for household income and socio-economic status.<sup>10</sup> Further, we account for household structure to bring in the presence of potential caregivers. In doing this, we include older females and males by age group, assuming that their presence in

> 8 The difference in LFPR between women with at least one young child and those without young children is statistically significant in all years.

> 9 We estimate the LFPR for women with children aged 6–7 and find that it is around 2–3 percentage points higher than the LFPR of women with children under age 6 in the period 2004–2011, whereas in the years before the difference was negligible.

> 10 The NSS surveys do not collect earnings information for self-employed workers (who constitute around half of employed persons) making it impossible to infer household income.

10
port operators, and cargo vessels (UNCTAD 2021). According to the Drewry database, the average global maritime freight rate reached over US$10,000 per 40-foot container

> 1 See ADB (2020) for more details. We would like to express our special thanks to the Central Asia Regional Economic Cooperation (CAREC) member countries and the Asian Development Bank (ADB) Corridor Performance Measurement and Monitoring (CPMM) team for sharing relevant raw shipping data. 2 The following analysis examines the period from 2010 to 2020. The impact of the COVID crisis may not be reflected sufficiently in our dataset.
# **Map 3: The use of citizen-collected data in Bogotá led to greater safety around bike paths**

_Source_ : Safetipin 2016. _Note:_ Ratings of poor to excellent are based on safety scores.

In the Middle East and North Africa, basic statistics such as unemployment rates are measured with imprecise definitions, blurring the line between unemployment and informality which distort the role of women and rural areas in assessments of national employment. Small changes in the definitions have large implications on the quantity of interest (Arezki et al. 2020).

In 2010, Ghana officially revised its GDP figures upwards by about 60 percent. This change suggested that Ghana’s economic performance had been significantly underestimated for years. The revision was the result of moving from the 1968 System of National Accounts guidelines to the 1993 vintage – as well as accounting more accurately for emerging sectors of the Ghanaian economy (Jerven and Duncan, 2012). Similar upwards revisions occurred in other African nations, including Nigeria, Senegal, Kenya, and Zimbabwe, among others (Koumane et al., 2019). While these revisions have no real direct effect on improving well-being, they do improve cross-country comparability which allows countries to better monitor relative performance of each country which can then inform macroeconomic policies which may indirectly improve well-being.

16
equity managers (Leeds and Sunderland, 2003) or create indices of attractiveness for private equity investments based on a large set of parameters (Groh et al., 2010) rather than using actual investment data.<sup>6</sup> To the best of our knowledge, this is the first systematic study on the determinants of buyout investments using actual buyout investment data from a comprehensive sample of developed and developing economies. Hence, the evidence we provide complements the existing evidence on the determinants of venture capital activity across nations and adds to our knowledge on international private capital flows.

Our study also contributes to the literature on law and finance (La Porta et al, 1997) and opens new avenues for research in the area of financial development and economic growth (King and Levine, 1993). Our results are helpful in understanding how capital markets are going to evolve globally and if and which other countries are most likely going to trend like the United States and the United Kingdom in terms of financial development, which potentially has new implications for economic growth in other developed or developing nations.

Finally, our results also have policy implications by identifying the factors a country should focus on when trying to attract more private equity investment. Aldatmaz and Brown (2020) find evidence for positive spillovers from private equity investments on public industry peers and highlights the importance of private equity capital on industry growth. Hence, in light of our findings, policy makers, especially those in developing economies, should focus on improving the institutional and regulatory environment in addition to providing growth potential to attract private capital, which may help local companies by providing the needed capital along with management expertise to realize growth opportunities.

> 6 This is likely due to data limitations. Detailed private equity investment data are very limited at the countryindustry level from other providers.

6
# **5.5 Quantifying Spillovers**

Given the potential for spillovers to women in the control group due to our individual-level randomization, we use baseline social network data to directly estimate spillovers. We find evidence of positive, significant network-based spillovers to women in the control group. Table 7 shows estimated spillovers at endline for our skills index, owning a business, earning positive profits, our extensive and intensive margin indices of business performance, employment, and wage work. Panel A shows spillovers estimated by accounting for any network link between a woman in the control group and a treated woman at baseline. Panel B shows spillovers for women connected at baseline through friendship links, and panel C shows spillovers for women connected at baseline through business links.

There is little evidence of positive spillovers in skills. None of estimated effects are statistically significant and they are all relatively small. However, we observe positive spillovers on a range of business outcomes. Having baseline business links with a treated woman increases the likelihood of owning a business by 5.7pp, 9%. It increases the likelihood of earning positive profits by 13% and the coefficient on the intensive margin business performance index is positive, though not statistically significant. Business links to treated women also reduce the likelihood of wage work by 32%, with no effects on overall employment. Strikingly, these effects are more than twice the size of the effects for women connected through friendship links at baseline, suggesting that there may be direct, positive economic spillovers between businesses.

Given that business links with treated women lead to positive spillovers, we adjust all estimated average treatment effects using spillovers specifically from business links.<sup>27</sup> At baseline, the average woman in the control group has 0.26 business links with a treated woman. We multiply the estimated spillovers by 0.26 and add them to our estimated average treatment effects (see Table A8, Table A5, Table A6, Table A7, and Table A9). Adjusted effects on
under alternative sets of circumstances which are independent from her will. In addition, implementing models (3) or (4) would provide a picture of the evolution of EOp over the life cycle of the specific birth cohorts that are present at the start of the analysis.

A less demanding approach in terms of data exploits the availability of repeated cross sections from the same population. If one is interested in understanding whether a society is experiencing changes in the EOp of its citizens, the relevant model considers where Y�� is the income of individual i sampled in survey t. The data generating process is allowed to change over time among random draws from the (same country) population. The implicit assumption is the over-time stability of the population, such that changes in EOp can be attributed to changes in the relevant parameters a and b. Model (5) is specular to cross-country analysis, once t is interpreted as a country indicator, but has the advantage of greater comparability of the underlying populations, originating from the same country.

> 3 In this paper we follow the ex ante approach. See Fleurbaey and Peragine (2013) for a comparison between the ex ante and ex post approaches to equality of opportunity.

3
# **Refugee Return and Social Cohesion**

Isabel Ruiz University of Oxford isabel.ruiz@bsg.ox.ac.uk Carlos Vargas-Silva University of Oxford, and Peace Research Institute of Oslo carlos.vargas-silva@compas.ox.ac.uk Key words: repatriation, social cohesion, Burundi JEL Codes: D74, F22, Q15 <mark>The paper was prepared for the Social Sustainability and Inclusion Global Practice unit and is an activity related to “Preventing social conflict and promoting social cohesion in forced displacement contexts”, led by task team leader Audrey Sacks.</mark> This work is part of the program “Building the Evidence on Protracted Forced Displacement: A Multi-Stakeholder Partnership''. The program is funded by UK aid from the United Kingdom's Foreign, Commonwealth and Development Office (FCDO), it is managed by the World Bank Group (WBG) and was established in partnership with the United Nations High Commissioner for Refugees (UNHCR). The scope of the program is to expand the global knowledge on forced displacement by funding quality research and disseminating results for the use of practitioners and policy makers. This work does not necessarily reflect the views of FCDO, the WBG or UNHCR.

Vargas-Silva also acknowledges funding from the Research Council of Norway via the TRUST project, grant no. 301065. The data used for this project was collected as part of the LAMFOR project funded by IZA-DFID. This work does not necessarily reflect the views of FCDO, the WBG, UNHCR, the RCN or IZA.
- 38 J.C. Duque, N. Lozano-Gracia, J.E. Patino, P. Restrepo / LCR Flagship Report on Cities and Productivity

Garcia-López, MA; Muñiz, I (2013). Urban spatial structure, agglomeration economies, and economic growth in Barcelona: An intra-metropolitan perspective. _Papers in Regional Science_ , 92(3): 515-535.

Gilbert, A (1996). The Mega-City in Latin America. United Nations University Press, USA (1996) Harari, M (2016). Cities in bad shape: Urban geometry in India. Working paper. The Wharton School, University of Pennsylvania.

- Henderson, JV; Storeygard, A; Weil, DN (2012). Measuring Economic Growth from Outer Space. _American Economic Review_ , 102 (2): 994–1028. doi:10.1257/ aer.102.2.994.

- Hijmans, RJ; Cameron, SE; Parra, JL; Jones, PG; Jarvis, A (2005). Very high resolution interpolated climate surfaces for global land areas. _International Journal of Climatology_ , 25: 1965-1978.

- Huang, J; Lu, XX; Sellers, JM (2007). A global comparative analysis of urban form: Applying spatial metrics and remote sensing. _Landscape and Urban Planning,_ 82: 184–197.

- Hsu, FC; Baugh, KE; Ghosh, T; Zhizhin, M; Elvidge, CD (2015). DMSP-OLS radiance calibrated nighttime lights time series with intercalibration. _Remote Sensing_ , 7(2): 1855–1876. https://doi.org/10.3390/rs70201855

- Jarvis, A; Reuter, HI; Nelson, A; Guevara, E (2008). Hole-filled SRTM for the globe. Version 4, available from the CGIAR-CSI SRTM 90m Database. Retrieved from http://srtm.csi.cgiar.org

- Kleibergen, F; Paap, R (2006). Generalized Reduced Rank Tests using the Singular