rafmacalaba/data-use-mentions-extended huggingface dataset:
<br>|0.10<br>|0.08<br>|0.12<br>|a|om]|
||(0.21)|(0.26)|(0.08)|(0.08)|(0.07)|(0.08)|||
|Corruption pere. ind.|21 0*+*<br>(0.53)|1.10<br>(0.95)|1.317<br>(0.28)|Lar**<br>(0.36)|Lager<br>(0.28)|1.5<br>(0.37)|4|21|
|Democracyscore|0.00**|0.03|0.049**|O.01|0.04**|0.01|aT|18.8|
||(0.04)|(0.04)|(0.01)|(0.01)|(0.01)|(0.01)|||
|Durab.ofregime|0.08**|-0.00|0.07***|0.04**|O.08***|0.05**|22.6|30.4|
||(0.03)|(0.03)|(0.02)|(0.02)|(0.02)|(0.03)|||

Note * - significant at 10% level, ** - significant at 5% level, *** - significant at 1% level. Abbreviation: DI - decentralization index. Corruption perception index (source - Transparency International), GDP per capita (source - WDD), GG consumption (source - Penn World Tables
large areas of mainly uninhabited desert that characterize Mali, Niger, and Chad. Nonetheless, the relatively low correlation between the geospatial estimates and the census estimates in non-sampled areas observed in Burkina Faso raises the prospect that the estimates for these areas could significantly change when upcoming censuses are collected and combined with survey data to produce updated poverty maps. Given the scarcity of evidence on out-of-sample prediction accuracy in the literature, we recommend treating the out-of-sample estimates in the remaining four countries with a high degree of caution.

There are several additional avenues for further research to inform these types of data integration efforts. These include additional empirical work to validate both point and uncertainty estimates against estimates using recent census data. Zonal statistics derived from geospatial data can be highly correlated. Initial results from current research indicate that the approach used for geospatial data processing and model building with geospatial data can impact the quality of the produced estimates. Model estimation also matters, it should be possible to improve upon existing methods for estimating mixed models with sampling weights. In addition, exploring the use of machine learning methods to capture complex relationships could improve estimation especially for out-of-sample areas. Despite room for further improvement, the modelbased estimates of the type calculated in this paper can provide interim estimates of the spatial distribution of poverty with acceptable uncertainty measures that cannot be obtained with survey data alone.

23
28 country’s history.<sup>46</sup> Furthermore, since we run separate regressions for female and male workers, the cohort FE are gender-specific. See Web Appx. Section H for details.<sup>47</sup> Differences in the returns to experience are preserved if we include 10 industry FE and/or 10 occupation FE (Web Appx. Table A.6).<sup>48</sup> For the returns to education, the occupation FE disproportionately reduce the returns for women in richer nations, which might indicate selection. At the same time, the ability to enter better (i.e., higherreturn) occupations is part of the returns to education. In addition, overall patterns in the returns remain, and our simulation results should be largely unaffected.<sup>49</sup> A related concern is whether there are differences in self-employment between men and women, as there could be issues with how self-employed individuals calculate and self-report the amount of salary taken from the business. Using the I2D2 data, we find that women are globally less self-employed: The self-employment rate is 36, 18 and 6% for women in the LICs, MICs and HICs, respectively, vs. 44, 33 and 13% for men. If the salary of self-employed individuals includes some of the returns to capital, we may overestimate the returns to experience of men, and the gender gap in the returns. However, the returns are similar when excluding the self-employed (Web Appx. Table A.6).

Since women are more likely to be selected in contexts where they work less, Web Appx. Table A.6 shows that differences in the returns are preserved if we drop country-year-samples with disproportionately high non-employment rates for women, in particular samples with rates above the median (54%, which is also the mean) or 25th percentile (44%) in the sample.<sup>50</sup> Alternatively, we drop
’, ‘rehabilitation’, ‘self-help’, ‘rural animation’ and ‘sustainable programming’ (Betts, 2021; Easton-Calabria, 2022; Easton-Calabria and Omata, 2018; UNHCR 2024b). Despite refugee self-reliance, in its various forms, existing for over a century, self-reliance has rarely been measured, and in the rare instances where it has, these measures have been deficient, failing to capture the central tenet of refugee self-reliance: independence from aid (Betts, 2021; Schön, 2020; Hoogeveen and Hopper, 2024).

The most cited measures of refugee self-reliance are the ‘Self-Reliance Index’ (SRI), developed by the _Refugee Self-Reliance Initiative_ who proclaim their measure to be “the first global tool to measure the progress of refugee families on their journey to self-reliance" (SRI, n.d.)., and Betts et al.’s (2018, 2020) measure of refugee self-reliance, which is used to assess how well-adapted refugee settlements are to supporting refugees. Despite representing the pre-eminent (if not only) recognized measures on refugee self-reliance, neither measure adequately accounts for independence from aid, thereby failing to capture the true notion of ‘self-reliance’. For instance, both the SRI and Betts et al. (2018, 2020) account for food security in their measures, but do so by measuring food consumption only, with no consideration given to the source of this food consumption and whether food security needs can be met independently of aid. While both measures include information on independence from aid, this information does not inform the other metrics used by the authors to calculate self-reliance, with refugees deemed to be ‘self-reliant’ in food security, public goods, health, education and other domains once a certain outcome is achieved, regardless of whether these outcomes can be achieved in the absence of external assistance.

(2024), who present their own, multi-dimensional measure of refugee self-reliance, while this paper offers a more simplified measure of self-reliance, one that is achievable given current
<!-- Start of picture text --> 2000 2002 2004 2006 2008<br>Source: UN COMTRADE (2008), World Development Indicators (2008), and World Bank staff calculations<br>4,000,00<br>3,000,000<br>2,000,000<br>Embodied productivity of exports<br>1,000,000<br><!-- End of picture text --> Figure 4: Embedded productivity of export basket, Syria, 2001–2007, calculated from 4-digit HS lines. EXPY calculated with per capita gross domestic product in constant 2000 U.S. dollars (maroon line) and constant 2005 PPP-adjusted international dollars (navy line).

winners” that was common in the East Asian growth experience between the 1980s and early 1990s (World Bank 1993).<sup>19</sup> How likely is Syria to break away from the relatively low levels of embedded productivity in its export basket? To better understand the potential diversification paths behind Syria’s export basket, we formalize the ease of transition to other export products. We first compute the proximity between two hypothetical goods _p_ and _q_ , which is an inverse measure of the distance between these goods, as conditional probability that a country exports product q (product p) given that it already exports product p (product q)(Hidalgo, Klinger, Barab ́asi & Hausmann 2007): where _ρ_ is an indicator variable that measures, for a given country _c_ in product _p_ , is given

> 19However, it would be an exaggeration to instead argue the opposite extreme, that there was no government intervention in the economy. Certain sectors, especially the agricultural and oil sectors, enjoyed government subsidies and price guarantees for their output, and in some cases was dominated by state-owned enterprises.

18
fluctuates between 25 to 30 degrees Celsius. The period between February and April is the hottest during the year (this period corresponds to the dry season). Northern Nigeria presents more variability in terms of temperature that ranges between 22 and 33 degrees.

# Figure 6

> 19 Specifically, Odekunle (2004) used 40 years of daily rainfall data from five weather stations (Ikeja, Kaduna, Illorin, Ondo, and Kano) representing different climates, to predict the date of onset and cessation of rains. The point of onset corresponds to the time when cumulative rainfall reaches 7-8% of the annual total rainfall, whereas that of rainfall cessation corresponds to 90%.

17
The results show that geographic targeting with any of the indicators is a significant improvement over an untargeted regime in which resources are distributed equally across all districts. There is, therefore, substantial potential for geographic targeting in Peru. However, targeting outcomes are quite similar for all of the targeting indicators I consider, and differences in outcomes between indicators are not significant at conventional levels of significance.

The rest of the paper proceeds as follows. Section 2 briefly describes alternative geographic targeting indicators available in Peru. Section 3 describes the methodology I use to compare indicators. It also describes altemative performance measures, identifies formulas that can be used to allocate resources to districts, describes data requirements, and states the assumptions made for the simulation exercise. Section 4 summarizes the results of the analysis. Section 5 draws conclusions.

# **2. Geographic targeting indicators in Peru**

In 1997 there were 13 administrative regions, 24 departments, 194 provinces, and 1812 districts in Peru (Webb and Fernandez Baca 1997, p. 112). Recent discussion about the geographic targeting of government programs has focused on the use of district-level averages. Districts can be quite small in Peru: According to the 1993 Population and Housing Census, the average district population was about 12,600 inhabitants, but some, predominantly rural districts had less than 200 inhabitants.

# _Infant mortality_

The infant mortality rate measures the fraction of children ever born who do not reach the first year of age. In Peru, as in many other developing countries, one would be loathe to estimate infant mortality on the basis of seriously incomplete death registries. To address this problem, demographers have developed indirect methods to estimate mortality at early ages (Hill, Zlotnik and Trussell 1983; Brass and Macrae 1984 and 1985; Trussell and Menken 1984). The Peruvian National Statistical Institute (INEI) used one such method--the preceding births technique--to estimate infant mortality in Peru.

The preceding births technique requires women to report the total number of children ever born and
it may be optimal to work at a specific location and in _face-to-face_ (F2F) contact with the public or co-workers, suboptimal work arrangements are also feasible for some occupations, particularly during a pandemic.<sup>2</sup> Another caveat of using criteria where at least one sufficient condition has to be satisfied to categorize jobs is that it is not clear how to choose the number of conditions to consider when several alternatives are available. If only one condition needs to be satisfied to classify an occupation as not being able to be done at home, then the more conditions that the researcher adds to the list, the higher are the chances that at least one of them will be satisfied by a given job. For example, one of the data sets used in this paper includes a battery of questions to measure F2F contact. Two of these questions are “How often does your job usually involve sharing work-related information with co-workers?” and “How often does your job usually involve instructing, training or teaching people, individually or in groups?” A priori, both are valid proxy variables for F2F work, but while almost 100 percent of people respond “very often” to the first question in most countries, there is substantially more variation in the responses to the latter. More generally, the more questions we consider to measure F2F, the higher the fraction of workers that would be classified as having an F2F-intensive job. Discarding questions and data based on this empirical observation is somewhat arbitrary.

There are two studies that are exceptions to the one-sufficient-condition criteria. Mongey et al. (2020) construct WFH and physical proximity measures for the United States using O*NET data. For the WFH measure, they use the same set of task variables as Dingel & Neiman (2020a, 2020b), but instead of defining binary indicators, they allow both the WFH and physical proximity measures to vary between 0 and 1. Leibovici, Santacreu, & Famiglietti (2020) construct a contact-intensity measure for the United
/mark><sup>30</sup> <mark>To capture the impact of</mark> **<mark>information and transaction costs</mark>** <mark>, the set of variables in ITIT ITtIT T d tT T TItIT IT tT</mark> i <mark>includes having common ethnic language, having common religion, previously having a common coloniser, previously being in a colonial relationship, previously being the same country,</mark><sup>31</sup> <mark>the average bilateral stock of migrants in 2013,</mark><sup>32</sup> <mark>the difference in rule of law,</mark><sup>33</sup> <mark>the difference in GDP per capita and the average GDP per capita. To capture</mark> **<mark>trade policy barriers and regulatory measures</mark>** <mark>, the set of variables T TdI T qI q</mark> i <mark>includes being in a free trade agreement and being part of the European Union.</mark><sup>34</sup> <mark>They also include the difference in regulatory quality</mark><sup>35</sup> <mark>and, where applicable/available, the OECD's and World Bank's STRIs and OECD's STRI heterogeneity.</mark>

**<mark>Governance Quality</mark>**<sup>**36**</sup> <mark>includes the average rule of law and the average regulatory quality.</mark>

<mark>The regressions are run on data from 2017 and include 30 countries, which is the largest sample for which all variables are available. The estimation is based on within-2-digit-sector variation. The R-squared decomposition is computed using Shapley and Owen values.<
where j=0 is in school, j=1 is in school and in labor force, j=2 is in labor force, and j=3 is staying inactive. The relative risk ratios (RRR) are presented.

# **4.2.    Results**

Table 2 presents the results for male youth and female youth activity decisions. Two of the findings are common for male and female youth. First, household heads’ education and employment status play a significant role in determining youth activity decisions. Youth in a family with a better-educated head and/or employed head (in either the agricultural sector or the non-agricultural sector) are more likely to be in school and less likely to be in the labor force or be inactive. Second, the ratio of working individuals to nonworking individuals in a household has a significant and positive effect on youth’s activity decisions, both in statistics and in magnitude. This ratio reflects two specific effects: the income effect and the network effect. The network effect in this context refers to youth who are exposed to greater job opportunities if there are more employed individuals in the family.<sup>10</sup> Since the income effect is the opposite of the network effect (a wealthier family is more likely to keep youth in school), this finding suggests that the network effect outweighs the income effect and the family network can be instrumental in helping youth to find a job and start to work. This finding is consistent with findings from the Pakistan Investment Climate Assessment (PICA) survey that about 50 percent of firms hire employees through a network of family or friends (Hou 2008).

The male youth decision model also shows that older and married male youth are more likely to work. Male youth in families with more young children (0-5 or 6-14 years old) or female youth (15-24 years old) are more likely to work. On the contrary, male youth in a family with more adults or more male youth (15-24 years
12 correlated shocks. In order to better understand how these propagation mechanisms affect the Ras Gas project and its bond yields we use the JP Morgan emerging market bond regional indices, i.e., Asia, Middle East, Europe and Latin America. We summarize the direct and indirect effects via Kepco credit spreads of the various variables on Ras Gas yield spreads and their first differences in the following table:

|Dependent Varia|ble|_Ras Gas Y_|_ield Spread_|_Changes in_|_RG Spread_|
|---|---|---|---|---|---|
|Effect||Direct|Indirect|Direct|Indirect|
|Variable|Description|Coefficient|Coefficient|Coefficient|Coefficient|
|RGS(- 1)|Lagged Ras Gas spread|persistent||||
|BRENT|(Log) oil price|indeterm.|+|indeterm.|+|
|BRENT<14|(Log) oil price below USD 14|insign.|+|indeterm.|+|
|BRENT: 14-23|(Log) oil price: USD 14 to 23|indeterm.|+|+|+|
|BRENT>23|(Log) oil price above USD 23|indeterm.|+|indeterm.|+|
|KORELES|Kepco yield spread|+||+||
|KORELES(-I)|Lagged Kepco spread|insign.|persistent||persistent|
|KEPCO|(Log) Kepco stock price|insign.|-|indeterm.||
|KRW|(Log) Korean Won FX rate|+|+|insign|+|
|KOSPI|(Log) Korea Stock Price Index|insign||insign||
|KR rating|Korean country rating index|+|+|insign.|+|
|ASIA|Emerging debt returns Asia|||||
|EUROPE|Emerging debt returns Europe|||||
we present event study estimates using the "imputation" estimator by Borusyak et al. (2021) which ensures consistency in the presence of the TWFE and also deals with issues of spurious identification and negative weighting (Acemoglu et al., 2022; De Chaisemartin and D’Haultfoeuille, 2020b).

Finally, in the main analysis, we focus exclusively on the "second-generation" SMCs to Africa. This is motivated by the fact that: (i) the "first-generation" SMCs had relatively low bandwidth capacity and hence low internet speeds. Bandwidth cost also remained relatively expensive. On the other hand, the "second-generation" SMCs brought faster Internet speeds at low cost to the continent, and marked the beginning of rapid expansion in Internet connectivity in Africa (Hjort and Poulsen, 2019); (ii) the arrival of the "first-generation" SMCs (1997-2002) predates the start of our FDI data (2004), hence limiting the application of our before-and-after design, and (iii) the staggered arrival of the "second-generation" SMCs also enables causal identification of impact as used in Hjort and Poulsen (2019). Therefore, in our quest to examine the effects of high-speed Internet connectivity on FDI, focusing on "second-generation" SMCs offers the best option. However, including countries that already received the "first-generation" SMCs in the analysis while assigning treatment status to the arrival of the "second-generation" 12
vidual i at time period t: The coefficient β is a measure of (im)mobility. A value of β of unity indicates that incomes move in step, with no convergence of incomes. If β is greater than unity, there is divergence, and β less than one indicates some convergence of incomes. Gottschalk and Spolaore (2002) consider two aspects of economic mobility. ‘Origin independence’ measures the degree to which future incomes do not depend on present income. β equal to zero combined with no individual fixed effects in the error term, ui,t would indicate full original independence. They also consider a second aspect, ‘reversal’, which is the degree to which ranks are reversed over time. A value of β less than zero would indicate some reversal, with individuals with above mean income experiencing a fall in income and poorer individuals getting richer. The socially optimal level of β will involve a trade-off between the degree of aversion to inequality (which favors lower values of β) and the degree of aversion to unpredictability of income (which favors values of β closer to one). Consistent measurement of β is needed to assess the degree of mobility.

However, in practice one observed data which are measured with error. One thus observes: We wish to place relatively weak assumptions on the measurement error εi,t. In particular, Bound and Krueger (1991) compare the Current Population Survey to Social Security Administrative records in the United States and find that the measurement error in earnings is positively autocorrelated over two years, and is negatively correlated with true earnings. These findings violate standard classical measurement error assumptions, and since similar validation studies are not available for developing countries, we wish to allow generally for the possibility of autocorrelation and correlation with true earnings.

Substituting (2) into (1) gives the equation to be estimated in terms of 6
Policy Research Working Paper 8855

# **Abstract**

An online survey experiment spanning 50 countries finds sizable improvements in tax morale when (a) the salience of anti-corruption efforts is increased and (b) citizens are allowed to voice their expenditure preferences to the government. These results hold very broadly across a uniquely large and diverse sample of respondents from all continents.

The findings are consistent with theories emphasizing the role of democratic accountability, as well as of perceptions of legitimacy and “retributive justice,” in generating voluntary tax compliance. Implications and avenues for further research are discussed.

This paper is a product of the Governance Global Practice. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at tpeixoto@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
use aggregate data in the United States to study how post-consolidation job loss is increasing in the human capital relatedness of consolidating firms. Similar to Lagaras (2017) and Lee, Mauer and Xu (2018), we find that job loss is higher among target workers at firms that have higher human capital relatedness (and therefore are more likely to have efficiency gains) and further find that this job loss is higher for the specific types of workers whose skills are replicated in the acquirer. We further are able to complement this work by demonstrating through our comprehensive income measures (including non-labor income) that even in the generous social safety net environment of the Netherlands, affected individuals tend to be underemployed and have lower total income, even four years after their firm is acquired.

We also contribute to the literature on the longer-term impacts of job loss (e.g., Couch and 3