rafmacalaba/data-use-mentions-extended huggingface dataset:
# Demand for “Safe Space”: Avoiding Harassment and Complying with Norms<sup>_∗_</sup>

Florence Kondylis<sup>_†_</sup> Arianna Legovini<sup>_†_</sup> Kate Vyborny<sup>_‡_</sup> Astrid Zwager<sup>_†_</sup> Luiza Andrade<sup>_†_</sup> Originally published in the Policy Research Working Paper Series on _June 2020._ This version is updated on _November 2022._ To obtain the originally published version, please email prwp@worldbank.org.

**Keywords** : sexual harassment, gender, public transit, mobility, revealed preferences, Implicit Association Test, stigma

> _∗_ This draft benefited from comments from Girija Borker, Peter Christensen, Simeon Djankov, Erica Field, Emma Frankham, Seema Jayachandran, Gabriel Kreindler, John Loeser, Shomik Mendiratta, Sveta Milusheva, Pedro Olinto, Dev Patel, Martin Raiser, Dan Rogger, three generous anonymous reviewers, and participants in seminars at ASSA 2020, Duke University, Gottingen, INSEAD, ITU, NEUDC, and the World Bank. We thank the World Bank i2i fund, the Knowledge for Change Program, the Umbrella Facility for Gender Equality, and the World Bank Brazil Country Office for generous research funding. Tuanni Borba and Rafael Dantas superbly coordinated all aspects of data collection. Finally, we thank the staff at Premise and SuperVia for their dedication in implementing this research design. This trial was registered in the 3IE database under ID-5a125fecae423 and Duke IRB D0910/2017-0401 and AEA RCT Registry AEARCTR0006142. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent. Replication package and Online Appendix are available at `https://github.com/worldbank/rio-safe-space
in horizontal and vertical equity are substantially different, the overall evidence is clear and shows improvements in equity. In the next sections, we explore the factors behind this development.

# **4.2 Does the block grant system promote geographic equity in service delivery?**

We first estimate equation (1) to investigate whether woreda block grants are positively associated with the poverty headcount. We then examine whether woreda poverty rates are linked to poor service delivery outcomes. If both the relations hold, we infer that the woreda block grant system promotes reductions in geographic inequity.

_Are block grants pro-poor?_ Table 4 presents results for equation 1. The dependent variable is the deviation from the mean in percent of per capita woreda block grants. The explanatory variable is the head count poverty rate. Control variables include region and time dummies. The results show that head count poverty rate for the woreda is significant in determining the level of the per capita woreda block grant. A 1% increase in the poverty head count is associated with a 0.12% increase in per capita mean expenditure.<sup>13</sup> Aggregated to woreda level and over time, such differences can translate into significant improvements in access to basic services in poorer woredas.

_Is poverty headcount linked to poor service delivery?_ The second proposition concerns a possible inverse relationship between the poverty headcount and service delivery in a given area. Results are presented in Table 5. We use a Probit regression to estimate each service delivery indicator as a dependent variable, with the poverty headcount rate as our main explanatory variable, and regional and time controls. As expected, the results show clearly worsening service delivery as the poverty headcount increases, in the sense of lower enrollments and utilization of maternal health services.

_Can block grants improve results in the bottom 20% of woredas?_

> 13 Based on 2011/12 expenditure data; outliers are trimmed at 5% and 95%.

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: author’s elaboration based on high‐level categorization from Low and Pasadilla (2015). Note: for a full list of detailed services sector by NACE 3‐digit for production stages, see Table A2 in Annex 1.

**Most service activities within Turkish manufacturing firms are in the post‐manufacturing stage.** Turkish services affiliate activity can be analyzed in terms of the number of affiliates as well as the revenue associated with each affiliate (Figure 3.6). (The Turkish firm‐level data distribute the revenue of the firm to the affiliates based on their employment share inside the firm. In other words, the revenue share is equivalent to the employment share of the services affiliate within the entire firm.) The left‐hand panel shows the breakdown based on the number of affiliates and the right‐hand panel gives the breakdown based on the employee‐weighted share of revenue that these services affiliates generate. Both breakdowns show that post‐manufacturing services are the largest type of services produced by Turkish manufacturing firms. This category includes transportation and distribution services. Back‐office services and establishment services are the next largest categories.

**Figure 3.6: Share of number of affiliates and revenue of manufacturing firms (2014)**

<!-- Start of picture text --> No. affiliates Share revenue<br>6.2% 13.7% 2.3%<br>17.7%<br>8.5%<br>AgricultureEstablishment 0.2%1.0% Other<br>4.5% Goods Establishment<br>Pre manufacture<br>1.6%<br>Other Manufacturing 34.7% Pre manufacture2.1%<br>Back office Manufacturing<br>13.4% Back office<br>Post sales<br>Post manufacture Post manufacture<br>Post sales<br>4.4%<br>48.1% 33.
, rural poverty rose by 10 basis points in 2019 likely due to a growth slowdown. Our estimates of poverty for recent periods are more conservative than earlier projections based on consumption growth in national accounts and other survey data. Finally, we do not find evidence of rising consumption inequality in our analysis. Our findings are supported by a comprehensive set of independent data sources.

The approach we developed to convert CPHS consumption into NSS consumption could be used to monitor poverty between the NSS years, thereby increasing the frequency of India’s poverty estimates. The approach may also find use outside of India. The first-best approach of course is to work with actual up-to-date household consumption expenditure data. Any imputation-based estimates of poverty and inequality are inferior to survey-direct estimates that are obtained from observed household consumption data. Imputation methods are necessitated when real up-to-date household consumption data are not available. When the imputation methods considered in our study are used to estimate poverty and inequality for the years in between NSS rounds, 63
addition, as part of the household survey, in each household with children of school-going age (between 6 and 11 years old), one child was randomly selected for a brief exam. Finally, enumerators visited the village’s primary school and health facility.<sup>8</sup> At each facility, enumerators undertook three activities. They conducted a carefully designed audit to assess the quality of the infrastructure and the presence of materials and

> 5 In total, 149 village clusters (661 villages) entered the lottery.

> 6 Note that the initial goal of the Tuungane program was improvements in governance, social cohesion and economic welfare (Humphreys et al., 2012).

> 7 Humphreys et al. (2019) targeted two randomly selected villages in each of the 560 clusters (280 treatment, 280 control). In total, 816 villages out of the targeted 1,120 villages were visited. There are no differences in attrition by treatment condition (Humphreys et al. 2012). In 2015, we targeted the same villages as visited for Humphreys et al. (2012), excluding the Maniema province for logistical reasons. These villages sum to 781.

> 8 We are interested in service provision as experienced by villagers. We therefore visited the main primary school and health facility for each village, thus not necessarily the Tuungane-built facilities in treatment areas.

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significantly positive at 0.264 and 0.228, respectively in regression [7] of Table 1. Consequently, portfolio investment inflows and other investment inflows help prevent further declines in GDP growth. The coefficients of FDI flows have insignificantly negative impacts on economic growth (i.e. at -0.0378 in regression [7] of Table 1). FDI is one of the major capital flows into the Sub-Saharan Africa region. Most likely, FDI activity is more dynamic in commodityabundant countries because those commodities attract massive foreign investments.

The cushion created by the fiscal space matters even if the economy’s structure tends to be driven by primary goods/commodities. For instance, empirical evidence suggests that natural resource/commodity exporters<sup>23</sup> experience larger negative and significant impacts on economic 20 The government response indicator (from Oxford Policy Tracker) captures a series of containment and health measures as well as economic support measures implemented by governments in response to COVID-19. The containment and health measures include school closings, workplace closings, cancelation of public events, restrictions on gathering, closure of public transportation, stay-at-home requirements, restrictions on internal movement, and international travel controls. The economic support measures record if the government is providing direct cash payments to people who lose their jobs or cannot work or if it is freezing households’ financial obligations. 21 The negative co-movement between the stringency of containment measures and economic activity is also found with other performance indicators such as consumption, investment, and industrial production, among others (IMF 2020).

22 Medical researchers’ work is still on going and in progress, and they are still finding new evidence. Accordingly, there have not been always definite treatments of COVID-19 yet.

23 Although countries with more concentrated economic structures are vulnerable to the crisis, accumulated savings can work as a cushion against shocks. Oil abundant countries, for instance, experience relatively lower declines relative to non-oil abundant countries in Sub-Saharan Africa (-5.5 vis-à-vis -6.3
confronted by the health system in fighting Ebola.”

# **2.2 Interventions**

## **2.2.1 Community Monitoring**

We model our Community Monitoring (CM) intervention on Björkman and Svensson’s (2009) “Power to the People” intervention, which was implemented in Uganda in 2005. The intervention attempts to mobilize “client power,” empowering patients with the information and forum to demand accountability from frontline staff (The World Bank 2003). CM convenes users and providers to discuss problems around local health service delivery and agree upon actions both groups can take to address these problems.

The CM intervention follows a four-step protocol. First, trained facilitators convene meetings with clinic staff and share scorecards rating local health problems. The scorecard includes five indicators related to maternal and child health (maternal mortality, under-5 mortality, vaccination rate, percentage of births in a health facility, and completion of four antenatal visits). These are constructed from relevant questions in the baseline household survey, and are compared to the district average so as to prompt discussion. Clinic staff are then invited to share their concerns and frustrations with the community. For example, nurses frequently complained that community members do not utilize the clinic, that mothers choose not to give birth in the 7
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**Figure 1. The main components of government employment**

<!-- Start of picture text --> / Adm inistration/<br>% liiXlXilll ,/ _~A d mnin istration<br>Health atio;<br><!-- End of picture text --> Even when comparisons are limited to monetary compensation, there are serious problems. If wage rates are derived from independent surveys or from official information on pay scales, it is impossible to treat non-wage allowances and other monetary benefits uniformly -because certain sources will include them in the wage package while others show only the basic salary. However, budgetary figures on the overall wage bill paid for through the central budget are generally reliable, because monetary allowances are usually captured in the central government budget, and properly classified under the wages and salaries item of the budget. For this reason, measuring the relative 'weight' of the government wage bill, by defining it as a fraction of GDP or of total expenditure, is both reasonable and reliable.

Compensation rates are a different matter: dividing the central government wage bill by the number of employees listed as working for the central government **will** always tend to inflate average compensation, because significant (and variable) numbers of employees are paid out of the central budget but work for, and are shown as part of, local government entities. Consequently, it is necessary, country by country and by recourse to different sources of information, to adjust the figures on personnel paid from the central government-in order to obtain a good approximation of average monetary compensation.

Assessing wage "adequacy", or even only ranking countries by relative levels of government wages, presents additional difficulties. Exchange rate problems make reliable conversion into a single numeraire difficult. Relating public wages in local currency to other meaningful variables also in local currency obviates the exchange rate problem, but raises the obvious issue of the appropriate denominator. The only reliable measure of the adequacy of government wages
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discuss, the accessibility to jobs may be more limited to women in the labor market or job assignment framework. Second, in the transportation or mobility context, women may also have disadvantage over men: Female workers are often more likely to rely on public transportation (Bento et al., 2005) or walking (Mondschein and Taylor, 2017). In addition, public transit may not be safe for women and girls (e.g., Ceccato 2017).

7. The firms’ locational choice is perhaps another side of the job accessibility issue: While employees decide where they live and how they commute to work, employers or firms also choose where they are located, possibly depending on transport connectivity. According to Sweet (2014), firms are more likely to relocate if they face large-scale traffic congestion at the regional level in the Philadelphia Metropolitan Area. In general, firms prefer to locate themselves where access to transport infrastructure is good (e.g., Cieślik and Ryan, 2004; Boudier-Bensebaa, 2005; Milner et al., 2006).

8. Finally, there are an increasing number of studies that aim to develop various indices measuring job accessibility. In recent years, various GIS-based high-resolution data have become available even at the city level, which allow to estimate all kinds of connectivity and accessibility in different ways (e.g., Cheng and Bertolini, 2013; Wang and Chen, 2015; Saghapour et al. 2016). The current paper also uses some spatial data to compute transport connectivity to the central business district (CBD) and job locations.

9. The current paper aims at examining the impact of public transit connectivity on access to jobs, particularly focusing on wages earned by those who commute to work. Given the above discussion in the literature, there are two issues that constitute this result chain: First, among others, accessibility to public transit may affect people’s decision on whether or not to commute to work. Second, once people
community in managing refugee crises and securing refugee rights. Similarly, while we cannot causally ascribe our results to residency in camps since residential selection into camps vs. host community is endogenous, our results for Jordan underscore the importance of revisiting camp settings and the policies governing them. In particular, the confinement of refugees to camps and their strict closures during the pandemic, while justifiable on health grounds, appear to have resulted in adverse socio-economic outcomes for camp residents.

# **Context**

As of May 2022, Jordan hosted 674,000 Syrian refugees as per UNHCR registration records (UNHCR, 2022). The actual number of Syrians in Jordan could exceed 1.3 million when accounting for the unregistered and those who do not consider themselves refugees (Krafft et al., 2019). That is more than one-tenth of the Jordanian population. The bulk of Syrian refugees arrived between 2012 and 2014, with the numbers stabilizing as of mid 2016 (Alhawarin et al., 2021). In the SYPJ sample, 95% of Syrians have been in Jordan for at least 5 years. Syrians in Jordan are mainly recognizable by their different accent.

Despite being the second largest per capita refugee host in the world (UNHCR, 2021b), Jordan does not have a legal framework on refugees. The country is not a signatory of the 1951 Convention Relating to Refugees and the subsequent 1967 protocol and does not have clear domestic refugee legislation. The only framework managing refugees’ issues is the memorandum of understanding the Jordanian government signed with UNHCR in 1998. Nevertheless, in line with customary law, Jordanian law explicitly prohibits refoulement<sup>4</sup> and allows exemptions on the requirements for entry and residency for political asylum seekers (ILO, 2015). Accordingly, Jordan

> 4 The forcible return of refugees or asylum seekers to a country where they are liable to be subjected to persecution.

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. We thus form an unbalanced panel of seven cohorts spanning seven academic years.

Each year, 20 percent of exam takers are randomly selected to complete the _ENLACE de Contexto,_ a multiple choice survey which elicits information about child labor, parental and student sociodemographic characteristics, student and parent expectations, and student perceptions about their peers, teachers and parental involvement.

The Ministry of Education conducts two school censuses per year, known as Formato 911, which are completed by an authorized school representative. The census identifies whether the school belongs to the _general_ , _indigenous_ , or _community_ system and collects a large set of school characteristics, including the number of teachers, students, classrooms, and laboratories and whether a library is available. For general schools, it also provides information

> 10The contiguous villages are named “Section 3 of Adalberto Tejada” and “Section 4 of Adalberto Tejada,” so they appear to be part of the same administrative unit.

> 11We observe a small number of surveyed PAL children in grades 7 through 9, but exclude them from our analysis in order to focus on primary school outcomes.

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Treatment 1|10,461|5,424|5,037|6,362|3,340|238|521|5,185|5,276|3,560|3,489|3,412|
|N Treatment 2|9,572|4,904|4,668|5,781|3,024|387|380|4,715|4,857|3,253|3,121|3,198|
|_R2_|_0.854_|_0.850_|_0.843_|_0.853_|_0.820_|_0.798_|_0.900_|_0.850_|_0.862_|_0.464_|_0.420_|_0.226_|
|||||* p <|0.05, ** p <|0.01, *** p < 0|.001||||||

_Notes:_ All regressions control for pre-treatment outcomes, demographic controls (including dummies for age, gender, academic year, and ethnicity), and municipality fixed effects. Robust standard errors are clustered at the school level in parentheses. All figures are rounded to three decimal places. _Source:_ Administrative data, school year 2016/2017, own calculations.

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cannot fall below some low positive value). As shown in Table 2.1, the determinants include the supply of government services (measured per student for each cycle of education and per-capita for health), the stock of government infrastructure, real household consumption per-capita (an indicator of the ability of households to make purchases in support of stronger MDG and education outcomes), and other MDG indicators (to reflect the fact that progress for one MDG may have a positive impact on other MDGs).<sup>12</sup> In the absence of crosscountry data for the provision of water and sanitation services, an alternative variable, absorption per capita (an indicator of overall capacity to support the living standards of the population), is the single determinant for MDGs 7w and 7s.<sup>13</sup> A wage incentive indicator is a determinant specific to education; it is expressed as the ratio between the wages for labor at the next higher and current levels of education for the student in question (an indicator of payoff from continued education). From a broader perspective, the education module tracks base-year stocks of students and new entrants through the different grades of the three cycles (primary, secondary, and tertiary). In each year, students will successfully complete their grade,

> 10 Given our focus on food prices, our nutritional analysis is focused on calorie undernourishment – the link between food prices, food consumption and calorie consumption is relatively direct and clear-cut. For other nutrition indicators, like wasting (weight for age) or stunting (height for age), the relationships are more long run while data on the impact of food prices and food consumption on these indicators are lacking.

> 11 Empirically, the impact of changes in per-capita calorie consumption on labor productivity turned out to be negligible in the context of moderate changes in calorie consumption and plausible elasticities of labor productivity with respect to calorie consumption.

12 Sadoulet and de Janvry (1995, p. 16) observe that absorption is
<!-- Start of picture text --> 100%<br>4% 4% 4% 3% 3% 3% 3% 3% 3% 3% 3% 3% 3% 3% 3%<br>Extractive industries 18% 17% 19% 17% 16% 15% 14% 15% 15% 13% 14% 12% 12% 11% 11%<br>80%<br>Utilities 18% 20% 20% 20% 19% 19% 21% 21% 22% 23% 23% 23% 25% 25% 25%<br>Construction<br>60%<br>Public administration<br>Manufacturing 40%<br>Services 59% 58% 57% 59% 61% 62% 61% 60% 59% 60% 60% 61% 60% 60% 61%<br>20%<br>Agriculture, forestry<br>and fishing<br>0%<br>2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014<br><!-- End of picture text -->

**Source:** Authors’ élaboration based on the Enquête Nationale sur l’Emploi (ENE; Labor Force Survey)

Labor market outcomes in Morocco reflect a unique circumstance in which trade shocks came along with a decrease in FLFP<sup>7</sup> and a reduction in informality.<sup>8</sup> Over the past 15 years, both female and male labor force participation in Morocco decreased, in contrast to trends elsewhere following trade growth. At the same time, informality rates for both men and women decreased. These trends might be associated in part with policies promoting formalization but deterring female participation in specific sectors. Informality rates in top exporting sectors (Figure 2.11) are relatively low compared to the overall informality rate of 74 percent in 2018. At the same time
# **Mapping Data Governance Legal Frameworks Around the World: Findings from the Global Data Regulation Diagnostic**<sup>**1**</sup>

Rong Chen Key words: data protection, laws, regulatory framework JEL codes: K19, K24, L86, O38

> 1 The paper is a background paper for the World Development Report 2021: Data for Better Lives. The author would like to thank the following colleagues from the World Bank Group for their review and valuable feedback on the paper: Mark Williams (Practice Manager, Digital Development Global Practice) and Silvia Muzi (Program Coordinator, Development Economics Vice Presidency). The author is also grateful to participants to the World Development Report 2021 Seminar Series (Seminar 2: Data policies, laws and regulations) for their comments and suggestions.