rafmacalaba/data-use-mentions-extended huggingface dataset:
# **IV EMPIRICAL STRATEGY**

# **IV.A Measures of Taliban, U.S. Allies, and Contested Territories Exposure**

For each individual in our sample, we construct a measure of exposure to Taliban ( _ET_ ), exposure to U.S. allies ( _EA_ ), and exposure to contested territories between the two sides of the conflict ( _EC_ ) using the data from 2017 until 2021. For this purpose, we employ the district of origin and the location of the Taliban, U.S. allies, and contested territories during this period.<sup>12</sup> Consequently, we construct _ET_ , _EA_ , and _EC_ as: Panel A of Table 1 presents descriptive statistics for these variables. The variables were constructed so that they can only take a maximum value of one and a minimum value of zero. For the case of Taliban exposure, for example, _ETi_ can be interpreted as the average share of territorial control that the Taliban had in the province of birth of individual _i_ during the five years between 2017 and 2021. The refugees in our sample have had more exposure to U.S. allies territorial control (mean: 0.60), than Taliban exposure (mean: 0.25), and exposure to contested territories (mean: 0.16). This is intuitive as most refugees are fleeing the Taliban and its policies, hence we expect to have fewer refugees from regions that have been dominated by the Taliban completely throughout the period of study. Fig12Appendix B.B describes in detail how we construct each of the treatment variables.

18
countries and El Salvador is not the exception. Indeed, no municipalitylevel measures of income, let alone other measures of economic development, are consistently available over time for the universe of Salvadoran municipalities. While the Multipurpose Household Survey (EHPM) does provide income data for some municipalities, its coverage is limited to 50 municipalities. Nonetheless, even for these so-called self-represented municipalities some years are missing for the period under analysis. That is, for the period 2001-2018 the EHPM allows the construction of an unbalanced panel with 772 municipality-year observations, excluding 78 municipality-year observations due to the lack of data. In response to the lack of GDP figures on a consistent basis at the subnational level, the seminal work by Henderson et al. (2012) proposes the use of a proxy that cover periods or regions for which GDP data are not available at all or not available in a timely fashion: density of nighttime lights (NTL density from now on). Henderson et al. (2012) show that NTL density indeed works well as a proxy for economic development at the

> 4Figures A.1 and A.2 depict the evolution of all the attitudinal measures by each of the four Salvadoran macro regions.

9
Some agencies are _statutory commissions_ in that they do have<sup>a separate legislative</sup> existence. They can be non-asset owning (legally distinct but not able to<sup>own assets in</sup> any sense) or asset owning (legally distinct and the owner of its assets). Their objectives are often enshrined in a charter and their functions are defined by<sup>the legislation,</sup> including the Minister's powers of direction. They can often be budget dependent (subvented) with significant revenue earnings. They can have legal competence<sup>to enter</sup> into contractual relationships. Such bodies tend to be established for regulatory purposes, although in some presidential systems they can also be service providing.

_Trading bodies_ also have a separate legislative existence, and can be established under commercia **l** aw in which case their charter and their articles of association<sup>define</sup> functions. They can be budget dependent, subsidized, but with significant<sup>revenue</sup> earnings. They generally have full legal competence to enter into contractual relationships - they can assume corporate liability and can be sued.

In the present series of BNPP surveys, those in Bangladesh, Bolivia,<sup>East Caribbean and</sup> Guyana covered officials from the first three types of organizations.

13
from the gravity estimations given the supply and demand from each region. The remaining imbalances, which are generally very small, are moved to stock changes if the commodity has stock changes in national SAM. If not, they are moved to household consumption by adjusting household savings. As those are pretty small, they do not cause significant changes.

The estimated flows from commodity accounts of the importing region to commodity accounts of the exporting region are then moved to household demand and intermediate demand accounts of importing region. So, the SAM treats commodity flows as if households and activities of the importing region are buying commodities from the commodity accounts of the exporting region. We assume the share of each importing region in the commodity flows from each exporting region is equal to the share of household or intermediate consumption

> 5EU-SILC is a cross-sectional and longitudinal sample survey, coordinated by Eurostat, based on data from the European Union member states.

7
7, Denmark at 0.8, and Sweden at 1.0).

# **2.2 Migration**

We focus on bilateral migration flow data across EU28 and EFTA countries between 2008 and 2018. These data are from Eurostat. Across the sample, countries differ both in terms of inflows and outflows of migrants, as shown in Figure 2. Larger migration outflows are observed in Eastern (Romania and Poland), Central (Germany and France), and Southern (Italy, Spain, and Portugal) European countries. The countries with the largest inflows are the U.K, Spain, Italy, and Switzerland.<sup>11</sup>

> as well as business regulation and the public perceptions of corruption (Treisman 2007).

> 8Both WGI CC and WGI GE are part of a larger set of Worldwide Governance Indicators, which include: _i_ ) Voice and Accountability; _ii_ ) Political Stability and Absence of Violence / Terrorism; _iii_ ) Regulatory Quality; and, _iv_ ) Rule of Law. See the World Bank.

> 9Besides the corruption index, there are 11 other indicators within the ICRG’s Political Risk classification. See the International Country Risk Guide.

> 10There is substantial variation in corruption levels both cross-sectionally and over time for year fixed effects to be included in the gravity model.

> 11When looking at average migration inflows, a few large countries (including Germany, Greece, Poland, and Portugal) have missing data from Eurostat.

5
# **1 Introduction**

The Italian Regional and Environmental Computable General Equilibrium of the Department of Finance (IRENCGE-DF) Model is a (recursive) dynamic single-country computable general equilibrium (CGE) model. It was developed by the Italian Ministry of Economy and Finance (MEF) and the World Bank (WB). The IRENCGE-DF model is based on the MANAGE WB model of the World Bank, which is, in turn, based on the MANAGE model as in Van Der Mensbrugghe (2021). It is developed under the project "Assistance for the assessment of environmental tax reforms (20IT41)" by the World Bank for the Italian Ministry of Economy and Finance (MoEF) and funded by the European Commission. Several modeling novelties are integrated: in addition to the standard features of a single country CGE model, the IRENCGE-DF model is dynamic, using the neo-classical growth specification. Labor growth is exogenous, and capital accumulation derives from savings/investment decisions. Finally, the model has a vintage structure for capital that allows for putty/semi-putty assumptions with sluggish mobility of installed capital. IRENCGE-DF is composed of two modules: i) the environmental part, designed to focus on energy, emissions, and climate change at the national level; and ii) the regional part, built to evaluate shocks at the regional level.

In this paper, the regional module of the IRENCGE-DF model is briefly reported. One of the biggest issues in building regional CGE models is the lack of specific regional data for building a proper Social Accounting Matrix (SAM). Our work represents a key contribution to the existing literature on regionalized SAMs: we show a step by step construction procedure for a completely new regional SAM. This matrix includes all economic and fiscal flows so that it represents an important source of information to use as input data for simulating the effect of the abolition of business tax (IRAP) in Italy through the IRENCGEDF model.

The model can be calibrated to a regional SAM that follows a standard set of conventions representing the
Policy Research Working Paper 7554

# **Abstract**

Using household surveys for 24 countries over a 10-year period, this paper investigates why the elderly are more averse to open immigration policies than their younger peers. The analysis finds that the negative correlation between age and pro-immigration attitudes is mostly explained by a cohort or generational change. In fact, once controlling for year of birth, the correlation between age and pro-immigration attitudes is either positive or zero in most of the countries in the sample. Under certain assumptions, the estimates suggest that aging societies will tend to become less averse to open immigration regimes over time.

This paper is a product of the Office of the Chief Economist, Europe and Central Asia Region. 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://econ.worldbank.org. The authors may be contacted at hwinkler@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
subsidiaries. The authors find that at the two-digit industry level, there are considerably more horizontal (subsidiaries in the same industry as their parents) than vertical (subsidiaries that supply their parents with inputs) FDI. However, disaggregating to the fourdigit level reveals that many of the foreign subsidiaries in the same two-digit industry as their parents are, in fact, located in sectors that produce highly specialized inputs to their parents’ production. Thus, contrary to the conventional wisdom, the authors find that the number of vertical multinational subsidiaries is larger than commonly thought.

Among the few studies using input-output data for countries other than the U.S, Hummels, Ishii, and Yi (2001) define a measure of vertical specialization that captures a country’s role in the fragmentation of production into multiple stages in multiple locations. The authors use input-output tables from ten OECD nations and four other countries to measure a country’s vertical specialization as its exports weighted by the share of imported inputs in its total output. Trefler and Zhu (2010) use 20 input-output tables from the Global Trade Analysis Project (GTAP) to reassess Vanek’s (1968) factor content of trade predictions in 41 countries.

# **3. Tackling Reverse Causality: An Identification Strategy**

Aid flows are expected to have an impact on exports, but a country’s exports may also affect the aid the country receives. It is plausible that donors target industries in recipient countries where exports are expanding or declining. As mentioned above, Brenton and Uexkull (2009) find that exports have increased owing to the effect of donor-funded export development programs in a number of countries. However, although the programs have preceded stronger export performance, causality cannot be clearly determined. Factors like the initial size of the 8
match to the corresponding funds from EPFR Global by name and family. We are able to match about 90% of the funds in our cleaned sample, ending up with 896 and 106 equity

> 10 Over the years, several papers have used the different versions of the EPFR data to analyze mutual fund investments in emerging and developed countries. See, for example, Kaminsky et al. (2001), Borensztein and Gelos (2003), Gelos and Wei (2005), Broner et al. (2006), Fratzscher (2011), and Jotikasthira et al. (2012). 11 Our sample covers mainly open-end mutual funds. While EPFR Global data contain some closed-end funds, their importance is relatively small. Moreover, many of the closed-end funds they cover allow for monthly or quarterly subscriptions and redemptions, and are therefore not truly closed.

> 12 We conducted two basic cleanings. First, we removed fund-time periods where the data was reported at a frequency other than monthly. This excludes some funds that report quarterly data during part of the sample period. Second, we excluded funds that report data for less than 12 months in the entire sample (unless they are present until the end of the sample period).

> 13 Equity mutual funds contain nine types of funds (of global and regional nature). There are a total of 965 mutual funds with 6,867,500 usable observations. Instead, bond mutual funds encompass two types of funds (global and global emerging markets), and include a total of 111 mutual funds. The total number of observations (country weights and cash) for bond funds is 561,500.

7
Rican households approximately 7.3 times as much as MFN tariffs.

# **8 Conclusion**

We study the consequences for PR of the JA, a U.S. law that requires vessels carrying waterborne freight to be U.S.-built, -owned, -flagged and -crewed. Data on port arrivals show a dearth of tanker, bulk, liquid and general cargo vessels in the JA fleet serving PR. We develop a theory that allows the effects of the law to have different consequences for trade among final and upstream products.

Among final products, we find reduced bias toward U.S. sources among products that are sea-shipped, heavy and/or difficult to transport in containers. Among upstream products, there is a large bias against sea-shipped products from all sources. The latter finding is consistent with JA having shifted the structure of PR’s production away from processing sea-shipped inputs over the long run, although other policies may have contributed to the outcome.

Since our evidence of the effects of the JA is strongest among final products, we focus our calculation of welfare costs there. Structural estimates of JA trade costs imply simple average tariff equivalents of 30.6 percent. In a simple calculation we estimate that tariff equivalent trade costs of this magnitude imply a burden of the policy on Puerto Rican households that is equivalent to 1.1 percent of expenditure, or about $203 per person annually. Our work also points in the direction of much larger dynamic losses from the JA. These include an estimated 3 percent increase in the cost of private investment, along with suggestive evidence that the Puerto Rican industrial structure has evolved to limit its use of sea-shipped imported inputs.

40
sector (6.78 percent). The fraction of unemployed respondents is massive and almost equal to 40 percent. Looking at the sample of women, the fraction of unemployed partners decreases at 10.2 percent and working in the mines is the most common type of occupation (14.9 percent) after self-employment in agriculture (17.2 percent). The discrepancy between the fraction of miners in the men sample and the fraction of partners working in the mines in the women sample likely reflects the absence of miners during the survey. Indeed, as previously highlighted, DHS enumerators selected individuals present in the household in the night before the survey and, due to their temporary migration to South Africa, miners are obviously less likely to be present. Therefore, the proportion of miners might be severely underestimated and the sample of interviewed miners not fully representative.<sup>10</sup> We also expect a fraction of former mineworkers among the unemployed respondents. Indeed, as stated in the previous section, the average low level of formal education among formerly miners limited their chances to be employed in other occupations. The highest share of miners is recorded in Zimbabwe (4.95 percent), while the highest fraction of women with a partner employed in the mines is in Lesotho (31.5 percent). The mining activities are different in Lesotho and Swaziland compared to Zimbabwe, which is characterized by

> 9In Lesotho, the average age at the first sexual relation is 15 years old for men and 17 years old for women (author’s calculations based on Lesotho Demographic and Health Survey, 2004). 10For example, data from the Lesotho Census 1996 reveal a fraction of male miners equal to 10%, while the same figure collected during the Census 2006 is equal to 4.8 %. Given the decreasing number of miners over time (see figure 2), we would expect a percentage of miners in Lesotho in 2004 between 10% and 4.8%, at least two times
000|
|2005|7,456|2,229|0.001|701|−254|0.000|
|2006|7,589|1,717|0.005|725|−285|0.000|
|2007|7,634|2,287|0.000|915|−262|0.000|
|2008|6,469|1,546|0.000|985|−209|0.021|
|2009|6,720|1,699|0.000|1,037|−177|0.012|
|2010|6,496|673|0.111|1,042|−309|0.000|
|2011|7,012|1,191|0.003|1,180|−125|0.184|
|2012|7,190|1,201|0.003|1,203|−298|0.001|
|2013|7,013|−17|0.962|1,223|−369|0.000|
|2014|7,512|319|0.370|1,286|−347|0.000|
|2015|7,969|924|0.014|1,256|−432|0.000|
|2016|8,170|188|0.606|1,293|−476|0.000|
|2017|7,956|−696|0.072|1,302|−545|0.000|

_Source:_ Based on National Household Survey data. _Note:_ Monetary values are expressed in Peruvian sol in 2017 prices using CPIs of the WDI database.

# **Propensity Score Matching Results**

The conditional independence assumption requires that the selection be solely based on observables. Any differences in outcomes between treated and control individuals
We contribute to that literature by being the first to evaluate the achievement effects of a large-scale tuition elimination policy for secondary education in Africa. The present study extends work by one of this study’s authors (Gajigo 2014), who used household survey data to find large enrollment gains from the same program. We use administrative data on the universe of standardized test scores in The Gambia from 1998 to 2012; we are the first researchers to obtain and analyze this data. We also contribute to the broader literature on efforts to close the gender gap in access and learning. Several other studies have evaluated similar programs targeting girls (Kim et al. 1999a, 1999b, and Chaudhury and Parajuli 2010 for Pakistan; Filmer and Schady 2008 for Cambodia; Kremer et al. 2009 for Kenya; Baird et al. 2011 for Malawi; Begum et al. 2012 for Bangladesh; and the previously mentioned Kazianga et al. 2013 and Muralidharan and Prakash 2013 for Burkina Faso and India, respectively), with a consensus finding that reducing the cost of attendance leads to gains in enrollment. Of these, however, only Baird et al. (2011) examines learning outcomes among secondary school students as we do, using a program more local in scope than our setting.

In the next section, we describe the education system in The Gambia and the girls’ scholarship program. Sections III–IV present the methodology and data we use for analysis. Section V presents results, and Section VI concludes.

# I. EDUCATION IN THE GAMBIA AND THE GIRLS’ SCHOLARSHIP PROGRAM

In the Gambian education system, the first 9 years are formally known as the Basic Cycle. This includes six years of primary school (grades 1–6) and three years of Upper Basic School (middle school, grades 7–9). High school, known locally as Senior Secondary School, consists of grades 10–12. The West African Senior School Certificate Examination (WASSCE, hereafter the Grade 12 exam), instituted in 1998, is
</sup> Moreover the attrition does not seem systemic, but instead appears driven largely by difficulties associated with tracking people as addresses were not recorded and the initial waves of the survey did not use GIS mapped data. Simple probit models (not presented here to conserve space) suggest that location and survey wave are the strongest predictors of attrition; age, education and employment status have little explanatory power. Hence we would expect little systematic

> 26Of the 1164 individuals interviewed in 2004, 622 were still in the sample in 2010.

26
, but they also benefit less from the faster adoption of more productive assets, likely resulting in some asset erosion over time and lower consumption levels (though to a lesser extent than in the case of regular rainfall failure). The damage from frequent exposure to localized floods is again less severe among those further away from the urban centers, as they experience less asset loss, while receiving more immediate disaster relief. Riverine floods can cause substantial welfare damage (23 percent), especially among those not frequently exposed, who tend to be better served by disaster relief, at least when living close to the urban centers. Finally, the largest damage is inflicted by hurricane force winds, with both regular exposure and proximity to the urban centers exacerbating the welfare losses substantially.

# **6 Concluding Remarks**

Understanding how natural disasters affect human welfare is an increasingly pressing concern, not least in Vietnam, which ranks among the most disaster prone countries in the world. This study illustrates a methodology to study the welfare effects of such events in a country specific setting using spatially disaggregated disaster maps derived from primary meteorological data combined with nationally representative geo‐referenced household survey data. By deriving the spatially disaggregated event and hazard maps directly from the meteorological data, issues of endogeneity in estimating the effect of such events on consumption are mitigated. The event and hazard maps provide also useful tools for policy and project planning. In addition, in estimating the welfare effects, spatial correlation was also accounted for. While the latter is routinely ignored, this is less suitable in empirical examinations of the household welfare effects of spatially disaggregated
Beyond the traditional theoretical explanations of economic models, other explanations, either non-standard or not well explained by the economic science, have been reviewed by Schiff and Winters (2004) who surveyed alternative rationales spanning from domestic policy anchoring, importing good regulatory practices, supra-national coordination to achieve regional policy goals, hegemons exporting regulatory standards, to foreign policy consideration. The rest of this section reviews in more detail the economic societal and political economy motives to conclude a PTA.

# **2.1** **<u>Economic motives</u>**

# **_2.1.1 Market access: A lesser driving force?_**

Market access mercantilism is the traditional force behind the push for trade liberalization. Led by the false logic that import barriers should be lowered only if reciprocal access abroad for exports is granted, countries mutually agree to liberalize their market resulting in most cases in welfare enhancing liberalization. In a globalized world, countries seek to gain competitive advantage over their neighbors by negotiating special – preferential – market access with key destination markets.

**Figure 1. MFN tariff rate, weighted mean, all products (%)**

<!-- Start of picture text --> 26<br>21<br>16<br>11<br>6<br>1<br>High income: nonOECD High income: OECD Lower middle income<br>Upper middle income Low income<br><!-- End of picture text --> Source: World Development Indicators 7