rafmacalaba/data-use-mentions-extended huggingface dataset:
Figure 4. Cumulative Distribution Functions of Price Volatility for Selected Manufactured Products <!-- Start of picture text --> 1<br>0.9<br>0.8<br>0.7<br>0.6<br>0.5<br>0.4<br>0.3<br>0.2<br>0.1<br>0<br>0 1 2 3<br>standard deviations<br>primary commodities computers<br>all manufactured goods IMF commodity price index<br>cumulative distribution functions<br><!-- End of picture text --> Note: The figure shows the cumulative distribution functions of the standard deviations of Hodrick-Prescott filtered series of individual goods prices. Data are from the Foreign Trade Division of the U.S. Census Bureau.

20
redistributive impact of payroll taxation, including the effects of a social security financing reform. A better understanding of the behavioral responses to changes in taxation or spending is also warranted. The World Bank has previously worked with the UK Institute of Fiscal Studies (IFS) to design a model (MEXTEX) which examines the impacts of fiscal reforms on efficiency and equity in the case of Mexico, and this approach could usefully be adopted to Colombia. Improved access to anonymous tax payer data would also go a long way in improving our understanding of the dynamics of top earners and the implications for the distribution of income. In addition, little is known about taxes different from personal income and value added taxation, such as financial transaction, wealth and fuel taxes. On the expenditure side, there is a need for further information about a few specific programs, including agriculture.

71. **Finally, a political economy analysis to examine the feasibility of the proposed fiscal redistribution package would also be useful.** This paper has deliberately avoided the critical issue of the degree to which the proposed policy measures can be implemented given existing political economy and legal constraints that Colombia is facing. An evidence-based analysis such as the one presented here, however, would be a useful starting point for such an analysis.

26
(2006) later found discrimination against men in programmer or computer analyst positions in the UK, while men were 5.2 percent more likely to receive a favorable response than women for engineering jobs. Zhou et al. (2013) found discrimination against men in high ranked software positions. But in Sweden, Carlsson and Rooth (2007) find no differences in the callback rates for women and men in male-dominated professions. They attribute Sweden’s occupational sex segregation not to discrimination in hiring, but rather to factors on the supply side of the labor market. In a later study, Carlsson (2011) found that across the entire labor market in Sweden, women were 3 percent more likely to be invited for job interviews than men, but there was no statistically significant difference in response rates between genders in male-dominated occupations. Women were 4 percent more likely to be invited for interviews in female-dominated and mixed-gender occupations (Carlsson 2011).

This study focuses on potential gender discrimination in the labor market in Uzbekistan, and in particular the capital city of Tashkent. The approach follows a similar experimental design to that used by Bertrand and Mullainathan (2004), and Booth and Leigh (2010). To the best of our knowledge, this is the first study to examine gender discrimination in employment in the context of Central Asia.

# II. Experimental Design and Identification Strategy

The primary data used for this study come from an audit correspondence survey conducted in Uzbekistan in 2020. The experiment relies on fictitious applications and measures callbacks and email invitations by employers to the emailed fictitious job applications. The paper uses additional data from the Listening to the Citizens of Uzbekistan study conducted by the World Bank together with the Development Strategy Center of Uzbekistan and other partners. The basic design includes four steps: resume design, firm selection, resume submission, and response recording.

We selected six of the most in-demand occupations advertised on four major job boards in Uzbekistan for the selected periods of the survey in early 2020: accountant, office administrator (secretary
and different treatment of missing years, without preschool data in PODES. Subsequently, we explore the intensive margins, such as the types of occupations and sectors that women go into. Given that preschool only provides 3 hours of childcare per day on average, can it enable women to work in the formal sector with rigid hours?

# **_5.1 Work participation_**

Table 2 reports the regression results of our three empirical strategies with and without districtspecific trends in the most conservative PODES-restricted years. Columns 1-2 estimate the work participation of mothers with preschool-aged children on public (Panel A) and private (Panel B) 15
cross-country differences in the firm size distribution and productivity. The hypothesis that the availability of managerial know-how grows with economic development is supported by the evidence in Hjort et al. (2022), which exploits data from a global consulting company to show that the relative remuneration of middle managers is much higher in poor countries.

**More generally, a growing literature documents the key role played by managers for firm-level performance.** The World Management Survey has collected detailed firm-level information on managerial practices over the past two decades, showing a wide variation across firms and countries closely associated to differences in productivity (Bloom and Reenen, 2007; Bloom et al., 2014). Moreover, the randomized controlled trial in Bloom et al. (2013) supports the existence of a causal relationship between managerial practices and performance, as plants that were randomly provided with free managerial consulting saw faster growth in total factor productivity and a persistent increase in the probability of adopting modern management practices. Consistently with the literature on human capital and firms discussed above, managers’ education and know-how are commonly found to be positively associated with more effective managerial practices and firm-level upgrading (Bloom et al., 2014; Verhoogen, 2021).

# **3.5 Misallocation of Talent**

**A key factor mediating the impact of human capital on economic performance is the allocation of talent.** It is self-evident that workers vary widely in their comparative advantage for different occupations and tasks, as a function of their education, experience and idiosyncratic ability (Figure VII.e). Models of occupational choice such as Roy (1951) make it clear that frictions that prevent workers from pursing their comparative advantage are detrimental to aggregate productivity, partially undermining the positive effects of investments in the accumulation of skills (Figure VII.l). A growing literature attempts to quantify the extent of the misallocation of talent and associated productivity losses in various contexts.

**Several studies emphasize the misallocation resulting from discrimination and social norms against specific demographic groups
|35.5|—|25.0|25.0|
|Domestic water consumption|Liter/capita/day|72.4|49.1|54.5(*)|165.9|
|Revenue collection|% sales|92.7|88.8|96.73|100.0|
|Distribution losses|% production|34.3|25.5|20.94|26.8|
|Cost recovery|% total costs|56.0|59|98|80.6|
|Operating cost recovery|% operating costs|65|95|144|145|
|Labor costs|Connections per employee|158.6|225.6|284.0(*)|368.7|
|Total hidden costs as % of revenue|%|109|94.27|13.08|167|

_Source:_ Demographic and Health Surveys (DHS) and AICD water and sanitation utilities database (www.infrastructureafrica.org/aicd/tools/data). _Note:_ DHS figures on access are as of 1997 and 2005 and utility numbers are as of 2000 and 2008, except when indicated. (*) Figures as of 2005.

— = Not available.

Senegal’s urban water utility, SDE, has set an example among Sub-Saharan African countries with its good bill-collection record and reduced water losses. Together SONES and SDE provide a model of a strong public-private partnership. Water has been made available 24/7 in large urban areas and several smaller towns. Distribution losses have been kept around 21 percent, compared with 34 percent in other African low-income countries, and even well below of what is observed in African middle-income countries (table 9). SDE captures 95 percent of the revenue stream that it needs to operate effectively, a comparatively good performance by regional standards. Also, the utility’s collection ratio is 97 percent of its sales (table 10).
DHS. In all cases, the urban coefficient on open defecation is greater than the whole-country coefficient and the rural coefficient is smaller. Hausman tests (reported under the open defecation coefficients in columns 5 through 7) verify that urban coefficients are larger than rural coefficients from the corresponding specifications.

# **2.2.4 Mechanism: A gradient that steepens with age**

Height-for-age _z_ scores are computed by age-in-months so that, in principle, the heights of children of different ages can be pooled and compared. If international reference charts were genetically or otherwise inappropriate for some countries, we might expect a consistent gap across children of different ages, analogous to a country fixed effect. However, stunting in India and elsewhere develops over time: children’s mean _z_ -scores fall relative to the norm until about 24 months of age, where they flatten out. This is consistent with early-life health deprivation causing a steepening “gradient” between health and economic status, more steeply negatively sloped as children age (Case et al., 2002). If the association between height and sanitation were indeed the unfolding result of accumulating exposure to fecal pathogens, then it is plausible that the association would become steeper over the first two years of life, at a rate that flattens out.

Figure 5 plots the coefficients from estimating the basic equation 1 separately for collapsed means of children in four age groups: 0-5 months, 6-11 months, 12-23 months, and 24-35 months. Thus, as in the rest of this section of the paper, each coefficient is computed in a regression with 140 country means, but now these height means only include children in – – subsets of the age range. The independent variable country-wide open defecation is the same in each regression.

Two conclusions are visible in the figure. First, the gradient indeed steepens in age, at a rate that flattens. Second, the mean height of Indian children in the 2005 NFHS-3 is plotted for reference. The curve has a similar shape to the age pattern
agricultural activities collected from Mozambique in 2014 and 2015. We exploit the spatial location information of households across two different data sets to match household consumption data with production data from the set of nearest neighbors. In addition, we also incorporate disaggregated, market-level price data on major staples to simulate the welfare and poverty effects using observed price changes. As a result, in contrast to many previous studies, this allows us to analyze the spatial variation in the impact of food costs using actual prices faced by the households.

2
br>Textiles<br>Trade and Transport Services<br>Transport Equipment<br>Wearing Apparel<br>Wood Products<br>0 20 40 60 80<br>Direct LVAX share (%)<br>ZAF COL CHL PER THA TUR<br><!-- End of picture text --> _Source:_ Authors’ elaboration based on LACEX.

Figure 15 shows this comparison across all countries for 2001 and 2011 for the three largest South African export sectors. In machinery and equipment, South Africa’s labor content as a share of exports declined relative to the average in the other countries, although it remains still slightly above the level expected given its income per capita. In metals, the country has moved from being 24
Table 9: Change in population age structure, 1996-2011

|Dep. Var.: change in share|(1)<br>Age<br>0-9|(2)<br>Age<br>10-19|(3)<br>Age<br>20-39|(4)<br>Age<br>40-59|(5)<br>Age<br>60+|
|---|---|---|---|---|---|
|Homeland (=1)|-0.066|0.147**|0.041|-0.087|-0.047|
||[0.047]|[0.057]|[0.102]|[0.061]|[0.031]|
|Share Employed mining1996|0.025*|0.047|-0.039|-0.039**|-0.005|
||[0.014]|[0.034]|[0.043]|[0.016]|[0.014]|
|Homeland*Share Employed|-0.034**|-0.052|0.038|0.060***|0.002|
|mining1996|[0.016]|[0.033]|[0.043]|[0.020]|[0.013]|
|Observations|9,598|9,598|9,598|9,598|9,598|
|R-squared|0.443|0.557|0.359|0.418|0.396|
|1996 Controls|Yes|Yes|Yes|Yes|Yes|
|MunicipalityFE|Yes|Yes|Yes|Yes|Yes|

Notes: Data from the 1996 and 2011 population census at the
plications for quality, enrollment, and equity. _Economics of Education Review, 71,_ pp. 7-22.

- [51] OECD (2018). Education at a glance 2018: OECD indicators. Organisation for Economic Co-operation and Development.

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**<mark>-</mark>** **<u><mark>Table 3: Hypothesis 1 Household Sample Selection</mark></u>**

|(1)<br>VARIABLES<br>Vaccinated|
|---|
|Phone Survey Sample (Dummy)<br>0.00795<br>(0.00523)|
|Constant<br>0.272***<br>(0.00296)|
|Observations<br>33,432|
|R-squared<br>0.000|
|Weighted Vax Rate: ESS Sample<br>29.5|
|Weighted Vax Rate: Phone Sample<br>30.5|
|Note: Bivariate OLS regression of vaccination status on a dummy for living in a<br>household sampled for the phone survey. The dummy identifies respondents in a<br>general population sample from the Ethiopia Socioeconomic Survey (ESS 5) that live<br>in households that are also included in the phone surveys (vs. the entire general<br>population sample). Standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1|

# **Respondent selection**

Since the phone surveys’ main respondent was purposively selected, we hypothesize that vaccine uptake estimates from the sample of main respondents is biased upwards. We predicted that randomly selecting the household member to be interviewed or collecting (proxy-reported) data on the vaccination status of all household members would lead to lower estimated uptake.

Our results confirm this prediction (Table 4). In all three countries in which we have data on both the main and a randomly selected respondent, estimated uptake is significantly lower among randomly selected respondents compared to purposively selected main respondents. Effect sizes range between five percentage points in Malawi to 13 percentage points in Burkina Faso (Table 4, Panel A). Collecting
of the mortality ratios to a reference population. Hill and Upchurch (1995) use mortality rates in six Northern European cc'untries from 1820-1963 and adjust the differential to the average level of mortality. Svedberg (1990) uses mortality from Sweden in the 1980s. Klasen (1996) and Svedberg (1996) debate the use of mortality in Sweden in the 1980s versus that in the "North" and "West" Model Life Tables of Coale, Demeny and Vaughn (1983). Since girls appear to exhibit biologically higher survival capability a normalization to underlying "nratural" mortality rates would imply that an equal mortality ratio is an indicator of female disadvantage. We report acLual mortality differentials because we feel that any given choice of normalization and its interpietation are problematic.

Reference populatiors are presumably chosen in order to answer a question like: "If there were absolutely no geinder-based differential _treatment,_ what would the observed mortality ratios be?" One way to answer this question is to use the mortality rates of a historical reference population, say Northern Europe in the 19th century, not necessarily because there was no gender discrimination, but because medical technology was (at best) ineffective, implying that mortality rates would not reflect differences in health-seeking behaviors based on gender. However, this seems problematic as medical advances that led to mortality gains in some causes of death and not others might then appear as increases in discrimination. For exampl,., suppose in the historical period that one in ten boys died of disease and one in ten died of unavoidable accidents, and no girls died of disease and one in ten died of unavoidable accidents. Now suppose that advances in medical technology made it possible to cure all diseases, A country in which children only died of unavoidable accidents would have equal mortality Dutcomes, but when normed to the historical reference period, 22
undermining the benefits that farm blocks were expected to provide. Conversely, it may imply expansion of cultivated area beyond farm blocks that may be environmentally less sustainable.

Summary statistics on mode of acquisition in panel B of table 2 separately for farms that overlap and do not overlap with digitized parcels illustrate formal and informal institutions’ role in land administration and management. First, with 31% overall (57% of parcels without vs. 23% of parcels with overlap), a greater share of land was acquired from chiefs than from all government institutions together (30%), highlighting that traditional authorities continue to play a major role in land administration or management. Second, the difference is particularly pronounced for land that has title where 38% of parcels were inherited or purchased but 44% with vs. 17% without overlap with registered parcels, were acquired from a Government body. Third, formal institutions issued close to 80% of all offer letters (74% on overlapping and 83% on non-overlapping parcels) and the centralized nature of Zambia’s formal land institutions is illustrated by the fact that only 3% of parcels with formal documents were received from local government.

Before discussing descriptive statistics at parcel level, we focus on changes in output and key inputs with distance to the nearest resettlement or farm block, noting that resettlement blocks were established earlier, mostly on land taken over from European settlers whereas farm blocks were established later to solve the land assembly problem for commercial farmers (Roth 1995). Table 3 panel A suggests, based on listing data, that digitized parcels are larger than area utilized by individual farms, possibly due to informal subdivision or encroachment. Compared to 630 ha for digitized parcels that overlap with cultivated ones, the average size of used parcels is only 19 ha (table 2 panel B.1). Moreover, titled land that overlaps with digitized parcels is, with an average of 27 ha, almost double the size of land to which no formal document exist. Although not all the
Similarly, some proxies of economic development like the share of employment in industry and agriculture at the beginning of the sample period seem to be associated to the levels of mobility at the district level.

This paper contributes to several strands of the economic literature. First, it adds to the literature on intergenerational mobility in general (see Black & Devereux, 2011, for a survey) but specifically to the literature focusing on the geography of socioeconomic mobility that recently received more attention in part because of the work of Chetty et al. (2014), which shows important variation across commuting zones in the United States. Second, it adds to the recent wave of research that looks at intergenerational mobility in education (see Emran & Shilpi, 2021; Torche, 2019, for recent surveys focused on developing countries). This set of papers includes on the one hand those that use household survey data or opinion surveys. For example, Hertz et al. (2007), Narayan et al. (2018), and Van der Weide, Lakner, Gerszon Mahler, Narayan, and Ramasubbaiah (2021) that document IGM for a very large set of countries across the world,<sup>2</sup> and Neidh ̈ofer et al. (2018) that focus on 18 countries from Latin America. This paper expands over them in terms of country coverage of the region and cross-country comparability. In addition, these estimates use the same type of data of recent estimates available for Africa, allowing a cross-regional comparison that was not available.<sup>3</sup> On the other hand and more closely related to this paper, it contributes to the pool of studies using administrative data or census data. For instance, Asher, Novosad, and Rafkin (2021) study mobility among different marginalized groups and analyze geographic differences in India; Card, Domnisoru, and Taylor (2022) use 1940 census data to study the role of school quality in mediating upward mobility in the US; Van der Weide
women, representing a 12% increase from the control baseline of 35%. For men, the increase is 4.7 percentage points, or a 13.5% rise over the control baseline. Reassuringly, we do not observe any differences in timely payments between treatment and control for pre-intervention bills.

Our study reveals that the impact of the personalized tax letters extended beyond the targeted October 2020 bill. The bottom right panel of Figure 8 provides compelling visual evidence that the letters encouraged some neighbors to clear past-due debt from previous billing periods, particularly following the implementation of COVID-19 lockdown measures in Argentina in April 2020. Despite receiving the letters in early October, the intervention also prompted some taxpayers to pay their November and December bills on time. Crucially, the magnitude of the responses was similar for both men and women.

We further exploit the detailed granularity of our property tax data to examine the payment dynamics of the October 2020 bill by gender, both before and after the due date. To this end, we first rectangularize the dataset using the payment date variable to obtain a daily balanced panel of payments. For each individual _i_ , the payment indicator _pay_ billid_ is set to zero up until the day the payment is made, and equal to one thereafter. We then run the following fully saturated regression where _γd_ are day indicators spanning September 25th to October 31st, _Treatid_ is an indicator for those who received a letter, interacted with the day dummies, and _Xid_ are controls. We run this regression separately for women and men and plot the coefficients together in Figure 9. Intuitively, _βd_ captures the cumulative difference in payment rates between the treated and untreated neighbors for each day _d_ , providing insight into the dynamic effects of the intervention.

The top panel in Figure 9 presents the distribution of payment dates for the October 2020 bill among women and men, with most payments occurring before the due date on October 9th. The bottom panel reveals an immediate and statistically significant increase in the payment rate among treated units. Notably