rafmacalaba/data-use-mentions-extended huggingface dataset:
therefore employ a strategy that is a bit unusual, we check to see how the method behaves in other Caribbean markets. We apply the same techniques to data from three Caribbean island nations - DOM, JAM, and BHS - and calculate implied � _τJA_<sup>_k_’s for</sup> those countries’ imports from the U.S.<sup>36</sup> If our estimating strategy were to falsely attribute some unusual feature of exports from the Southeastern U.S. to the JA, we would expect to see the same pattern of � _τJA_<sup>_k_’s for at least one of these countries.As</sup> the bottom of Figure 1 shows, none of the three countries’ imports exhibit the same pattern we observe in PR. Relative to PR, the predicted distribution of implied � _τJA_<sup>_k_’s</sup> is compressed for all three countries. In DOM, PR’s nearest neighbor, the distribution of predicted JA tariff-equivalents is tightly compressed around zero, except for some air-shipped products with large negative _τ_ � _JA_<sup>_k_’s.TheestimatesforJAMare</sup> somewhat noisier, with no significant tendency for _τ_ � _JA_<sup>_k_’storisewithweight.The</sup> BHS estimates are noisier still, but the distribution remains compressed relative to PR, and the relationship of _τ_ � _JA_<sup>_k_’s to weight is negative rather than positive.These</sup> estimates all support the argument that the shipping characteristics’ effects on PR’s imports reflect consequences of the JA rather than some artifact of our procedures.

Our estimates of _τ_ � _JA,t_<sup>_k_returnvaluesforallfinalproducts,includingthosethat</sup> typically travel by air. Since the reference air-shipped product is at the median of the weight-to-value ratio for air-shipped products, our procedures predict positive values of _τ_ � _JA,t_<sup>_k_forroughlyhalfoftheproductsthatarriveinPRbyair.To</sup> avoid attributing positive JA
country loses some of its most able individuals.<sup>9</sup> Alternatively, if the low-ability group acquires education, we obtain the same result as for individual heterogeneity (Section 2.2.1).

# 2.3. Unskilled Migration

Most analyses in the new brain drain literature examine the incentives to acquire education in the absence of migration and compare them to the incentives prevailing in the case of skilled worker migration. However, the reality is that out-migration of unskilled workers is substantial in most source countries, and their expected wage is higher under migration, just as is true for skilled workers.<sup>10</sup> Denote the migration probability of skilled (unskilled) labor by _p_ ( _q_ ), skilled (unskilled) variables by subscript _S_ ( _U_ ), and destination country variables by *. In the absence of migration ( _p = q_ = 0), the education benefit or skill premium is With a brain drain ( _p_ > 0, _q_ = 0), the expected benefit of education is

> 9 Stark (...) includes two groups in his model where, as assumed here, low-ability individuals do not acquire education when migration takes place, though high-ability individuals invest more in education when incentives improve. The model presented here assumes, as in most papers dealing with the brain gain, that individuals can only acquire a fixed amount of education.

> 10 The new data set on migration by educational attainment put together by Docquier and Marfouk (Chapter 5 in this volume), and which covers 174 countries for 1990 and 195 countries for 2000, indicates that, for 1990, the average migration share—i.e., the migration probability--of the middle and high-education groups put together is about _twice_ as large than in the low-education group. The recent immigration policy change favoring skilled migrants is reflected in the 2000 figures, with the share of the middle and higheducation groups about _2.5_ times larger than in the low-education group
<u>https://siteresources.worldbank.org/INTLSMS/Resources/3358986-1233781970982/58009881282216357396/7337519-1388758418241/GHS_Panel_Survey_Report_Wave_2.pdf.</u> NBS. 2016. _LSMS-Integrated Surveys on Agriculture: General Household Survey, Panel 2015/2016._ Abuja: NBS and Federal Ministry of Agriculture and Rural Development; Washington, DC: World Bank. https://microdata.worldbank.org/index.php/catalog/2734/related-materials.

NBS and World Bank. 2016. _Basic Information Document: Nigeria General Household Survey, Panel 2015/16_ . https://microdata.worldbank.org/index.php/catalog/2734/related-materials.

Nwankpa, M. 2014. “The Politics of Amnesty in Nigeria: A Comparative Analysis of the Boko Haram and Niger Delta Insurgencies.” _Journal of Terrorism Research_ 5 (1). <u>http://doi.org/10.15664/jtr.830.</u> OCHA (United Nations Office for the Coordination of Humanitarian Affairs). 2017. _Nigeria: 2018 Humanitarian Needs Overview_ . New York: OCHA.

<u>https://www.humanitarianresponse.info/sites/www.humanitarianresponse.info/files/documents/f iles/13022018_ocha_humanitarian_needs_overview.pdf.</u> Raleigh, C., A. Linke, H. Hegre, and J. Karlsen. 2010. “Introducing ACLED: An Armed Conflict Location and Event Dataset Special Data Feature.” _Journal of Peace Research_ 47 (5): 651–60. <u>https://doi.org/10.1177/0022343310378914.</u> Rockmore, M. 2017. “The Cost of Fear: The Welfare Effect of the Risk of Violence in Northern

- Uganda.” _World Bank Economic Review_ 31 (3): 650–69. https://doi.org/10.1093/wber/lhw025.

- Serneels, P., and
**Figure 6: Population differences between 2014 Census and 2014 HBS**

Share of total population by region <!-- Start of picture text --> 35<br>30<br>25<br>20<br>15<br>10<br>5<br>0<br>Nord Centru Sud Chisinau<br>Population Census Population HBS<br><!-- End of picture text --> Source: Authors’ estimates based on HBS and Population Census data.

The HBS questionnaire includes multiple questions about incomes, expenditures of households, as well as some social, demographic and labor market characteristics. The CEQ analysis relies as much as possible on information about social transfers and taxes reported in the survey. If the survey does not include questions on certain items, the values were either simulated or imputed. The numbers on total fiscal revenues and expenditures were taken from the administrative data provided by Ministry of Finance, Ministry of Health, Labour and Social Protection and National Bureau of Statistics of the Republic of Moldova.

In the analysis we include all existing social contributions and almost all direct taxes applied to households (this amounts to about 93 percent of total revenue collection for these types of taxes). For indirect taxes the coverage is also very high – 97 percent of total indirect taxes are reflected in the analysis. For social policy this ratio is 91 percent and for in-kind health and education services – 86 percent.

Most of the programs included in the analysis match the administrative numbers fairly well (Table 7). Direct taxes and social contribution cover 82-87 percent of the aggregate administrative numbers for those items. Some mismatch could be explained by the natural bias in the survey sample and some income misreporting at the top of the distribution. Contributory pensions are overestimated quite significantly, while other direct transfers show lower numbers than in aggregate statistics. This could be explained by some flaws in the sample frame, that does not fully reflect the current demographic structure of the population
performed in the following manner: in each of the 40 LGAs, 3 wards were selected<sup>11</sup> and then one enumeration area (based on the census) was sampled in each ward. All households living in that enumeration area were listed and 25 were randomly selected to be interviewed, for a total of 3,000 households. Around 80% of those were tracked in the follow-up survey and re-interviewed. For those not found, a new household was interviewed as a replacement.<sup>12</sup> The Government Officials panel dataset includes 948 observations - 474 individuals in each of the waves. In the first round, the following 12 government officials were targeted to be interviewed in each LGA: Mayor/Council Chairperson; Council Director; Council Internal Auditor; Council Economist; Council Human Resources officer; 3 Elected Ward Councilors; and 3 Ward Executive Officers. Government officials were assured their answers would be kept confidential, and in 95% of cases the respondent was alone for the entire interview. At the second survey, over 70% of officials still worked at the same LGAs and were re-interviewed even if working in a new position. For the remaining officials, the interview was conducted with the individual currently occupying the position of the respondent in the initial survey.<sup>13</sup> For most of these officials, PO-RALG oversees all decisions related to appointments, transfer, promotions, etc. As PO-RALG also implemented the project and commissioned the survey, this could create some bias in government officials’ responses. However, this potential bias would affect both treatment and comparison groups.

For both households’ and government officials’ surveys, our main difference-in-differences specification compares average changes in outcomes in project vs. non- project respondents, pooling together respondents that participated in both waves and replacements for those who could not be tracked. Our main estimates, in other words, treat the panel dataset as two separate cross-sectional surveys.<sup>14</sup>
<mark>Across Sections 4 and 5, we focus on three types of outcomes: those related to economic development, intrapersonal psychosocial processes, and relational psychosocial processes. Economic development outcomes include consumption (a proxy for poverty), food security, and women’s business outcomes. Intrapersonal psychosocial outcomes include beliefs about the self (e.g., self-efficacy), about one’s future (e.g.,</mark> positive future expectations for mobility), and psychological well-being (e.g., life satisfaction, depressive symptoms), which we situate as intrapersonal resources for goal pursuit. Relational psychosocial outcomes include social capital (e.g., social support, financial support, participation in community organizations), social influence (e.g., social standing, control over business decision-making), and social norms, which we situate as relational affordances for goal pursuit. All of these outcomes were measured in the policy experiment sample while a subset was measured in the mechanism experiment sample given timing constraints.

<mark>Further details on experimental design and outcome measures are provided in the Methods section in the Appendix.</mark>

# **<mark>3. Study 1: Descriptive Findings on Agency in Context</mark>**

The formative research phase aimed to understand women’s models of economic agency in rural Niger. In particular, we explored which factors women viewed as motivational, socially valued, and effective for advancing their economic mobility. We also sought to build ‘interpretive power’ around these models of agency, i.e., to understand them in relation to the affordances and constraints of the socioeconomic and cultural context (Brady et al., 2018).

First, in the baseline survey of the policy experiment, we found that, as is common in collectivist societies, behavioral interdependence was broadly practiced and valued. In survey responses, 90% of women agreed or strongly agreed that “when making a decision, it is
Boys are making greater gains in response to these improvements in education access, while girls’ primary intake rate continues to lag behind.

Available data shows that both under-five and infant mortality rates had a clear downward trend from 1990 to 2006—especially during 1990-1997 and 2003-2006. On the other hand, maternal mortality in Yemen in 1990 was generally believed to exceed 500 per 100,000 live births. The ratio had fallen to around 350 by the time the 1997 DHS was carried out, but has not shown much change since, as illustrated by a figure of 365 given in the DHS of 2003. Maternal mortality is the leading cause of deaths among women of reproductive age, accounting for 42 percent of all deaths; 77 percent of births took place at home, with less than 30 percent attended by a qualified person. The high neonatal mortality rate, at 37 per 1,000 live births, is closely correlated with the maternal mortality rate.

Yemen is also unlikely to meet the MDG target of a 50 percent reduction in the proportion of people without access to safe drinking water. The rate of progress in access to safe water has been slow and, without an improvement in the rate of change, the target is unlikely to be met. The same can be said about the target for access to improved sanitation.

The likely reasons for the slow pace of improvement for most MDG indicators include insufficient allocation of resources to MDGs and infrastructure, poor use of resources actually allocated to MDGs, and slow growth in household incomes. The persistence of high population growth further complicates the task of reaching the MDGs by requiring substantial increases in services provided simply in order to maintain current coverage rates. While there are opportunities for improving the contribution that economic growth and social policies make towards attainment of MDGs, the gap between the targets and what has been achieved suggests the need to adopt realistic and country-specific targets that actually can serve as guides to action.

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4 likelihood that foreign investments would be concentrated into a short period of time, and hence display spikes or discontinuities in foreign investment flows. Knickerbocker did not, however, study the influence of past presence. Recently, Head, Ries, and Swenson (1995) have shown that Japanese investors in the United States tend to "follow-the-leader," affirning the signalling value of others' behavior. Kogut and Chang (1996) have used firm-level data for Japanese multinationals investing in the United States and they find past presence to be an important predictor of new investments-however, they do not explore the influence of rivalry. The findings of this paper are also consistent with aggregate evidence of persistence in foreign investment. Wheeler and Mody (1992) found that U.S. investments into a country were strongly conditioned by existing stocks of foreign investment in that country (after controlling for a variety of factors, including market size) and speculated that agglomeration economies may be important especially where investors were likely to be engaged in the purchase of intermediate inputs from other investors. But even where agglomeration economies are unimportant, past presence can provide, or the presence of others can signal, information on business operating conditions which are critical to smooth functioning but which cannot be easily inferred from generally reported statistical indicators or from stated policy towards foreign investors. Also, subsequent analysis shows that Japanese investors are equally influenced by the stock of past investment (Mody and Srinivasan 1996). This study reinforces earlier micro and aggregate evidence on the value of private information but additionally distinguishes between the different sources of private information and demonstrates their complementarity with public information.

The setting for the empirical examination is investment by Japanese manufacturing firms in a number of key Asian countries in the early 1990s and the data is from a specially designed survey
In terms of income inequality, on the one hand, ROCs present, on average, higher values in the Gini index than NROCs  a difference of more than 2 percent. On the other hand, LOGCs, on average, have higher total income inequality, while HOGCs present the lowest. There is a substantial difference of 7 percent between the average Gini coefficient of LOGC and HOGC economies.

# **V. SIMULATION**

Our simulation procedure permits to make a dynamic assessment of income distribution by country. The Monte Carlo simulation method combines multiple paths of mean income growth with a variety of inequality trajectories to predict changes in income distribution. The practical exercises described in the sections below use household survey data of incomes and expenditures in the period 1980–2015.<sup>27,28</sup> Thus, given the scarcity of microdata for the study period, per capita consumption growth is initially used to construct synthetic observations of mean income between spells. As an alternative, GDP per capita growth was tested and used instead of per capita consumption growth.

The Monte Carlo simulation procedure consists of deriving simulated paths of the mean income and the Gini coefficient. To recover these paths, at each period , number of random draws are generated to complete the simulated sequences. These sequences tt= {2015, 2016, ... , TT} consist of global mean income growth 2015} } }, global real commodity prices nn nn nn 2015} } }, idiosyncratic shocks kk=1 in TT kk=1the mean-income growth {{gg , ... , {gg nn nn kk=1 TT kk=1 {{pp � , ... , {pp � �, and idiosyncratic shocks in the growth of the Gini coefficient nn nn cc,2015 cc,TT ��εε �kk=1, ... , �εε �kk=1 �. Each draw is generated using mean and variance sample statistics for nn nn cc,2015 cc,TT
A Tale of Two Cities-IDPs Plan for Their Durable Solutions in Darfur. Refugee Survey Quarterly, 39(4), 507-513.

- Doss, C. R., & Quisumbing, A. R. (2020). Understanding rural household behavior: Beyond Boserup and Becker. Agricultural Economics, 51(1), 47-58.

- Elu, J. U., & Loubert, L. (2013). Earnings inequality and the intersectionality of gender and ethnicity in Sub-Saharan Africa: The case of Tanzanian manufacturing. American Economic Review, 103(3), 289-92.

- Elzarov, Z. (2019). Emerging options for durable solutions in Darfur. Forced Migration Review, (62), 55-57.

- Flint, J., & De Waal, A. (2008). Darfur: a new history of a long war. Zed Books Ltd..

- George, R., Saeed, M., & Abdelgalil, S. (2019). Women at the forefront of Sudan's political transformation. ODI WP 566.

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rose in the Andean region, Brazil, and others in the Southern Cone, while it in fact fell in Mexico and Central America – the countries hardest hit by the 2008-09 global crisis; leading to an increase in poverty. World Bank (2014) reports additional trends obtained from the Labor Income Poverty Index (LIPI), which examines whether the per capita labor income of households is lower than the regional poverty line, i.e. the share of households who are incapable of satisfying basic needs based only on their income from labor. Based on quarterly and monthly labor surveys, these indices have the advantage of constituting very regular sources of information. As measured by the LIPI coefficient, poverty has declined in nearly all countries considered in the study since 2010 (except for Mexico, where it has increased since 2013). The rate of reduction, however, has flattened recently and the most up-to-date data suggest signs of a reversal, with increasing labor income poverty in Argentina, Brazil and Peru.

Despite the value of labor income indices, a multidimensional approach can add valuable information to assess job growth, and the sustainability of labor market trends. Multidimensional measures provide a new depth of information about the variable of interest. Notably, in terms of poverty, these estimations consider how individuals are deprived, not only by their absence of income, but by their lacking in other dimensions related to wellbeing, such as in terms of living standards, access to services, or housing. Indeed, poverty measurement efforts in Latin America are moving in the direction of complementary measurements of welfare as part of the shift worldwide towards a multiple dimension perspective over the past two decades. Within the region, Chile (2015), Colombia (2013), and Mexico (2010) have been 4
12.|Institutional Development ...........................|49|
|13.|Level and Mix of Extemal Funding ....................|49|
|14.|Government Objectives -- Poverty Commitment .............|50|
|15.|Consolidated Budget Per Capita Infrastructure Expenditures:<br>Summary and Conclusions .........................|51|
|D. A Com<br>Cen|parison of Analyses of Per Capita Infrastructure Expenditure Using<br>tral Budget vs. Consolidated Budget Data .................|55|
|REFERENCES ....|.........................................|59|
|ENDNOTES..|............................................|62|

# **LIST OF TABLES**

|Table 1|Correlation Between PCOM & Poverty Indicators .....<br>..<br>.........|14|
|---|---|---|
|Table 2|Means of Central Budget Infrastructure Expenditure Data ....<br>.......|15|
|Table 3|Means of Consolidated Budget Infrastructure
24 The remaining control variables include dummy variables on mother's education (no education, primary, secondary, and tertiary education), wealth quintile (calculated by the DHS and included in the dataset), area of residence (rural and urban area), and province (Kenya has 8 provinces).

# **Data quality considerations**

A number of data concerns can arise in child mortality data in the Demographic and Health Surveys. In the case the of Kenya surveys, these are discussed in the 2008 DHS report (Kenya National Bureau of Statistics and ICF Macro 2010). One possible issue is displacement of reported deaths, which occurs when an interviewer misreports a live birth within the last five years to a period outside that window, in order to avoid having to ask the long series of questions corresponding to births in the last five years. The DHS report finds some evidence that this took place in the 2008 DHS, but this does not affect results presented in this paper, which deal only with births in the one year prior to the survey.

Another potential data problem is omission of births of infants who did not survive. When this occurs, it is usually most pronounced for very young deaths, and thus a low proportion of very young deaths is taken as an indicator of such omission. In the 2008 DHS data, for the five years preceding the survey, the proportion of neonatal deaths occurring during the first week of life is high (82 percent) and the same as the proportion recorded in 2003, suggesting that early neonatal underreporting is minimal and unchanged over time. Similarly, for the five years previous to the survey, the proportion of infant deaths that occurred during the first month of life was high (61 percent), suggesting that underreporting of neonatal deaths was not a serious problem. This was a substantial increase from the 2003 and 1998, for which the corresponding proportions were 47 percent and 41 percent respectively. This increase is the consequence of the large decline in the number