rafmacalaba/data-use-mentions-extended huggingface dataset:
profitability, while desirable, are simply not available in a standard format across countries.

Caveats aside, it seems likely that our five indicators – M2/GDP, Private Credit/GDP, Cash/M2, interest spreads, and concentration – provide a reasonably complete picture of financial sector development since 1992. Note also that the indicators are differentially suited to capturing short versus long-term financial development. On the one extreme, movements in the ratio of cash/M2 can provide a summary of depositors’ short-term reactions to policy changes. On the other end of the spectrum, the private credit ratio and the concentration ratio, while both admittedly subject to some short-term perturbations, tend to capture long-term financial development. M2/GDP and spreads are, arguably, somewhere in between the two extremes. Taken together, the five indicators are likely to provide a more complete picture of both long-term and short-term banking development.

While the financial outcome variables that we use are standard within the finance and growth literature, our data on World Bank projects to support financial reform are not. The World Bank’s Operations Evaluation Department (OED) has recently compiled a comprehensive database of 556 projects from 1992 to 2003 in which an intention to reform the financial sector was expressed. These projects include loans for adjustment, technical assistance, or lines of credit (LOC).<sup>6</sup> We focus our analysis on adjustment loans because these tended to be larger (in dollar terms), with conditionality attached to specific financial reforms, but aimed at broad financial sector development. By contrast, LOC often focused on channeling funds through specific financial institution(s), while technical assistance loans tended to be much smaller than adjustment loans, and focused on more narrow issues. The Appendix lists the 68 countries that received at least one adjustment loan with conditions tied to financial reform. As noted, these are either pure financial sector adjustment loans or multi-sector adjustment loans with financial sector components. A control group of 38 countries identified as having
operation and Development, and official government publications of each country, among others;

- _educ1_ = government spending on education as percentage of GDP from the WDI database;

- _educ2_ = people with completed secondary and tertiary education as percentage of population aged 15 and over from Barro and Lee (2010);

- _rd_ = a country’s expenditures on research and development as percentage of GDP from the WDI database;

- _investment_ = measure of investment freedom in natural logarithms from the Heritage Foundation <mark>and serves as a proxy for investment promotion.</mark> The score ranges from 0 to 100 (highest investment freedom) and measures the ability of individuals and firms to <mark>move their resources in and out of specific activities both internally and across the country’s borders</mark> . <mark>This variable is mainly based on official government publications of each country on capital flows and foreign investment;</mark>

- _trade1_ = a country’s share of exports of goods and services as percentage of GDP from the WDI database;

- _trade2_ = measure of trade freedom in logarithms from the Heritage Foundation, which is a composite measure of the trade-weighted average applied tariff rate and non-tariff barriers with scores ranging from 0 to 100 (highest trade freedom), reflecting the absence of trade protectionism. The measure is based on various underlying sources including data from World Bank, the World Trade Organization, and the Economist Intelligence Unit, among others;

- _business_ = measure of business freedom in natural logarithms from the Heritage Foundation as an outcome-based indicator of a country’s institutional development. It is a measure reflecting the ability to start, operate, and close a business with scores ranging from 0 to 100 (highest business freedom). The measure mainly relies on the World Bank’s Doing Business study;

- _hhi =_ HHI of sector concentration to capture competition in a domestic firm’s sector. The HHI of sector concentration is defined as the sum of squares of firm’
**_Figure 1: Discriminatory behavior by firms in the DRC inside and outside the capital city_**

<!-- Start of picture text --> 79%<br>45% 45% 43%<br>35%<br>31%<br>25% 25% 26%<br>19% 17%<br>13%<br>10% 8%8%<br>0% 3% 5% 5% 2% 3%<br><!-- End of picture text --> While it is difficult to ascertain the relative roles played by discriminatory laws versus social norms in holding women back in the DRC from reaching their full economic potential, the data summarized in Figure 1 do provide suggestive evidence that social norms may matter. The legislation set out in the labor and family code refers to the entire economy, and not just to Kinshasa – this suggests that something other than laws is driving the differences we see in discriminatory behavior. An alternative explanation may be that there is a lack of enforcement in laws in Kinshasa, but it is quite likely that the level of enforcement is endogenous to prevailing social norms. We posit that social norms are a likely driver, in line with a wellestablished literature that shows that women with more traditional gender roles or living in a more traditional context are less likely to be employed than women with less traditional gender roles or living in less traditional contexts (Fernández, 2007; Alesina et al., 2013). These findings are also in line with interesting insights about the role of culture or social norms in the DRC provided by the Demographic and Health Survey (DHS) data. During the 2013-2014 DHS, questions concerning the decisions about the use of the salary were asked to married women who had worked during the previous 12 months. In Kinshasa, 63 percent of married women replied that they are the main person who takes decisions about the use of their salary versus an average of 26
# **Introduction**

Since the availability of the first COVID-19 vaccines in late 2020, the world has witnessed the largest vaccination effort in history.<sup>1</sup> In early June 2022, 60 percent of the world population had been fully vaccinated for COVID-19. However, large regional disparities in COVID-19 vaccine coverage remain (Figure 1). Sub-Saharan Africa (SSA), in particular, is lagging in its vaccination efforts. As of July 1, 2022, less than 17 percent of the population had received at least two doses. Consequently, all but two countries (the small island states of the Seychelles and Mauritius) in SSA remain adrift of the World Health Organization’s (WHO) goal to fully vaccinate over 70 percent of the African population by June 2022.<sup>2</sup> _Figure 1: Share of the population fully vaccinated over time._ <!-- Start of picture text --> 60<br>Burkina Faso<br>40 Kenya<br>Malawi<br>Nigeria<br>Tanzania<br>Low income<br>Lower middle income<br>20 Sub-Saharan Africa<br>World<br>0<br>1/1/2021 7/1/2021 1/1/2022 7/1/2022<br>Date<br>Source: Our World In Data<br>Percent<br><!-- End of picture text --> A variety of reasons have been cited for why vaccination efforts in SSA are trailing their targets.<sup>3–12</sup> Shortages in vaccine supplies, the accessibility of vaccination sites, and vaccine hesitancy are the main hypotheses discussed to explain the low coverage.<sup>3,13</sup> However, there is a conspicuous lack of systematic, cross-country comparable, and up-to-date evidence on these issues. Using data from five national phone surveys, we provide new evidence on vaccine
Bank, 1998). In addition to the Apoyo evaluations, Moncada (1996) considers various aspects of FONCODES performrance; Schady compares the FONCODES index of unmet basic needs with other district-level mesures of welfare available in Peru, and analyzes political influences on the timing and distribution of FONCODES investments (Schady, 1998 and 1999, respectively,.

The analysis in. this paper complements the work done by Apoyo and others. The Apoyo evaluations are useful to assess the opinions that FONCODES beneficiaries have of FONCODES, but they have only lirmited value to measure the targeting and impact of FONCODES investments. The evaluations did not create a rigorous control group necessary for a comparison of FONCODES beneiaiciaries with others; they were not based on a sampling framework which would make it possible to apply the results from the sample to a larger population-even if this population were limited to FONCODES beneficiaries; and information was not gathered on a number of important variables, including actual figures on school attendance or grade repetition.

# **5. The targeting ,of FONCODES investments in education**

Social expenditures in Peru have traditionally favored vocal, urban middle-class constituencies. FONCODES was set up, in part, to redress this balance, and funding projects which benefited poor areas and poor households has been an important program objective from the outset.

Targeting education resources is important in Peru because there are large difference ; in measures of educational attainment across regions and income groups. We use data from tY e 1996 INEI survey to illustrate this point. In Figure 5.1 we graph the average number of years of schooling attained by children of different ages who live in the poorest 25% of districts, up to those who live in the richest 25% of districts, when districts are ordered by mean per capita income.<sup>6</sup> Figure 5.2 presents a comparable graph for household income quartiles. Figures :i. and 5.2 clearly show that children in poor districts and poor households lag behind in the years of schooling they
sometimes multiple times depending on the number of agency inspections, with direct costs charged to the importer and higher risks of deterioration for perishable goods. As in previous steps, the quality of the port physical infrastructure and efficiency of port operators in moving the cargo, as well as their limited use of IT systems to efficiently allocate containers, can also generate delays (even for non-intrusive inspection methods based on x-rays). In addition, delays can occur as the importer or its representative must be physically present during any physical inspection. Also, rent-seeking practices, including informal payments to obtain a modification of the Customs classification or valuation of the imported good, or to limit or altogether avoid sample testing can occur at this stage considering the multiple stakeholders involved in the clearance process. In a final step,<sup>14</sup> Customs clear the shipment once all border control agencies have provided their clearance and the importer has paid any outstanding balance, marking the end of the import process as defined in this paper. The released shipment can then be picked up by the importing firm either immediately or after some time if the firm decides to take advantage of port storage facilities or if it faces liquidity constraints to pay port fees.

We rely on the World Bank Enterprise Surveys (WBES) database for the period 2006-2016 to construct our measure of uncertainty in import clearance times, which covers unpredictable delays arising at any stage of the import process as discussed above, from vessel berthing to Customs clearance.<sup>15</sup> The WBES database provides quantitative and qualitative information on the characteristics of firms operating in the manufacturing and services sectors in developing countries; as well as the business environment they face (e.g. access to finance, regulations, taxes and trade costs). Surveys are administered to nationally representative samples of formal firms with at least five workers. We use the standardized version of the database which compiles only those surveys following the WBES Global methodology, yielding information that is comparable across countries and years
_For labor or for divorce?_ making their divorce threats more credible in case of conflict. Moreover, altered marriage contracts arguably provide women with incentive to supply labor and remain in the labor market through many channels. Chiappori et al. (2002) find evidence of a shift to higher female bargaining power intra-household and El Lahga and Moreau (2007) suggest lower degrees of specialization in domestic production. Drawing on this strand of literature, our central hypothesis is that divorce legislation reform should increase women’s bargaining power during the marriage, potentially, allowing more women into the labor market.

To test this argument, we construct a pseudo-panel of mothers that we assign to treatment and control groups based on the ages of their youngest child. Using data from the Demographic and Health Survey (DHS) program that spans over decades and a quasiexperimental difference-in-differences design, we assess how the implementation of the right to unilateral divorce affects women's labor outcomes in Morocco, The Arab Republic of Egypt, and Jordan. We follow cohorts of “treated” mothers for several periods before and after the reform thus including the short-term and long-term effects of legislative reforms on women’s socio-economic position. Our findings suggest that there are two main mechanisms: a power-shift effect and an anticipatory effect.

Our results show that the power-shift effect is most prevalent impacting mainly married mothers with children below the legal age-custody cutoff, for whom divorce is less costly. However, this effect can be offset by higher costs in the labor market that remain barriers to women’s labor marketization. This study contributes to the literature on the effects of divorce, child custody and alimony legislation on women’s labor outcomes (Parkman, 1992; Gray, 1998; Bremmer and Kesselring, 2004; Genadek et al., 2007; Stevenson, 2008; Bargain et al., 2012; Hassani- Nezhad and Sjögren, 2014; Fernández-Kranz, 2022; Corradini and Buccione, 2023). Additionally, it shows how the effects of legislation are heavily dependent on context
dramatically changing the point estimates derived from the survey. In some cases, the estimate lies exactly on the 45 ̊ which signifies that the model-based estimates did not provide additional information enough to revise the direct estimates.

**Figure 37: Direct vs. Fay Herriot Estimates for in-sample Poverty $5.5day (left) and average consumption (right)**

<!-- Start of picture text --> 1 20<br>R2 = 0.9975 R2 = 0.9628<br>0.9 18<br>0.8 16<br>0.7 14<br>0.6 12<br>0.5 10<br>0.4 8<br>0.3 6<br>0.2 4<br>0.1 2<br>0 0<br>0 0.2 0.4 0.6 0.8 1 0 5 10 15 20<br>Direct Estimate Direct Estimate<br>Fay Herriot Fay Herriot<br><!-- End of picture text --> Coefficients of variation (CVs) are a useful guideline with respect to precision when estimates are far away from zero, and when the sample size is small (for instance, the surveys in UZB and TJK are much smaller than for the other two countries). In the case of per-capita consumption, no resulting in-sample estimates are above the 20% threshold that some statistical agencies adopt for reporting (Eurostat, 2013). Furthermore, the R2 between district poverty rates at $5.5/day and average consumption is very high (.74) suggesting that the estimates of poverty and average consumption are very consistent. This strong accordance should give greater credence to the poverty estimates.

70
countries, with only a few being applied bilaterally.<sup>10</sup> The database is based on the WTO notifications available from the Integrated Trade Intelligence Portal (I-TIP) for more than 100 importers and over 5,000 products for the period 1995-2019, complemented with data from Bown (2016).<sup>11</sup> This dataset simplifies econometric analysis because it has been enriched by imputing missing product codes at HS 6-digit level. The final dataset provides information on (i) the concerned country and the country implementing the measure, (ii) the year the measure was introduced, (iii) the affected HS 6-digit product, (iv) the nature of the measure (e.g., SPS, TBT, quantitative restrictions<sup>12</sup> ), and (v) where applicable, the actual date the measure was removed. Using this information, we calculate the count of SPS and TBT measures imposed by a destination country to exports of HS6-digit products from an origin country. This count proxies regulatory intensity with regulatory burden increasing with increasing count of NTMs.

# **3.1.1** **_Stylized facts on non-tariff measures_**

Over time, the use of NTMs to regulate trade flows has increased. The number of countries imposing an NTM, whether SPS and/or TBT measures, either unilaterally or bilaterally on exports from Burkina Faso, Malawi, and Senegal has been on a steady increase since 2000 (Figure 2a). The number of unique HS6-digit products that attract an NTM has also been rising since 2003. We observe a similar pattern for both SPS and TBT measures and in both the agriculture and manufacturing sectors (see Figure A2 ). This contrasts with the use of tariffs which have been on a downward trend over a similar time frame (see Figure 4).

When it comes to the use of NTMs to regulate trade, there is a clear divide between developed and developing countries. Often, the
Paradoxically, families who earn barely enough to survive spend vast amounts of money on celebrations. In the rural South Indian data' I analyze in this paper, a typical household spends approximately seven times its annual income on a daughter's marriage - on celebrating the wedding and on dowry transfers to the groom's family. Moreover, fifteen per cent of its expenditures, on average, are spent on celebrating village festivals. Poor households tend to find such large sums of money by going severely into debt at interest rates that range from 100-300 per cent per year which leads to chronic indebtedness and, sometimes, bonded labor. Despite the importance of these expenditures the Economics literature has largely ignored them, perhaps because they fall into the realm of "non-rational" behavior. However, given their pervasiveness, and the dominant role accorded to Economics in the formulation of policy, this omission can have serious consequences for the design of policy interventions. Money spent on celebrations is, after all, money not spent on food, education, health, and other productive inputs.

What explains this paradox? Are celebrations wasteful? In this paper I will examine the factors underlying expenditures on festivals and weddings with qualitative and quantitative data from South India. In this introductory section I sketch a general conceptual model of publicly observable events and the role they play in Indian village life. I will then illustrate this conceptual framework by examining aspects of wedding and festival related behaviors. While the paper relies on fieldwork from the South Indian state of Karnataka, I believe that the analysis is easily generalized to other parts of South Asia. With changes in structure and context, the basic points are perhaps also relevant to human behavior in other non-Western societies. Working within a context with which I am relatively familiar, however, allows me to provide a more nuanced perspective on an important aspect of the cultural economics of behavior in poor households<sup>2</sup> .

In rural Indian life, celebrations tend to mark important transitions: A wedding marks
ROSCAs, and “cash kept at home or in a secret hiding place, that is not for daily living expenses”), and in-kind savings (advance purchase of farm inputs, business inventory, and bags of maize stored for later use). These three categories are mutually exclusive and exhaustive. For ease of comparison to the administrative data, the first column of Table 5 includes only savings in NBS accounts. Columns (2) - (4) are the three categories described above. Column (5) is total liquid savings, the sum of formal and informal savings, and column (6) is total household savings from all sources.

Directly depositing money into NBS accounts increases self-reported savings by MK 1,670 as measured one week after the transfers. The effect is smaller than in the administrative data, perhaps because the control group reports a higher level of savings at NBS than observed in the administrative data, but reflects the same trend: the savings default increases the amount of money in NBS accounts. Because we lack expenditure data after the transfer for the eight day delay group, Panel B has a smaller sample and thus results are not directly comparable to those using administrative data. Nonetheless, the magnitude of the effect of the savings default on NBS balances after two weeks is remarkably consistent with the administrative data.

Columns (2) to (6) show that the increase in money saved at NBS reflects a change in the composition rather than the total value of savings. Focusing on results after one week, where data for the full sample are available, we see that total savings in formal financial instruments rise by an amount comparable to the increase in savings at NBS (column 2), and that the change is more than offset by a decline relative to the cash transfer group in informal savings (column 3), which includes cash kept at home. In other words, the cash transfer group kept money at home while the savings default group kept it at the bank. Inkind savings is
and women’s participation in household decision making. We explore the Census of Human Resources of the Guatemala Central Government (collected by INE in 2017-2018), 2017 and 2018 municipal statistics (published by INE and by FUNDESA), 2017 social spending data (from ICEFI), and 2017 data assessing the degree of societal agreement with broad gender-parity statements (collected by Latinobarómetro in 2017). Based on these data sets we define variables that capture social norms and the role of public policy at the local level with: (i) share of women in high-paying public sector jobs (in the central administration) at the department level (based on data from the Census of Human Resources, 2017-2018), (ii) intrafamily violence at the municipality level (based on data collected by 2017 INE); and (iii) share of males agreeing with gender parity in congress and in the judicial system relatively to the entire population (based on 2017 Latinobarómetro). We proxy the influence of social public policies with: (i) 2017 municipal number of preprimary centers (collected by INE), (ii) 2017 per capita spending in education and health at the department level (collected by ICEFI), and (iii) the municipal road accessibility in 2018 (collected by FUNDESA). See Table A1 for details on these variables.

The set of local labor market characteristics include the per capita GDP at the municipality level in 2017 (collected by FUNDESA), the ratio of male-to-female employment in each municipality based on 2018 Population Census,<sup>9</sup> sectoral structure of (male) employment from the 2018 Population Census, and the municipality crimes rate in 2018 (collected by INE).

The main 2018 census sample includes 1,696,260 women of working age (25 to 49 years old) living in households were they or their partner is the household head. Our final sample covers a total of 333 municipalities (out of 340 total) and 22 departments (out of 22).