rafmacalaba/data-use-mentions-extended huggingface dataset:
with soap and water nor in households with access to improved water sources, compared to those without access. Diarrhea prevalence appeared to be uncorrelated with income, but it varied noticeably by geographic location. On average, 4 percent of children had presented ALRI symptoms in the previous 48 hours, and 6 percent in the previous seven days. ALRI prevalence increased for children living in households with unimproved sanitation and those with unimproved water sources. As with diarrhea, similar percentages of households had presented ALRI symptoms in the previous seven days, irrespective of whether they had a handwashing station stocked with soap and water. In addition to these, three-quarters of the samples taken from children younger than two years old indicated the presence of anemia (the proportion was slightly lower for households with improved sanitation).

Finally, the average child was breastfed for 12 months, although more than 60 percent of caregivers gave their children instant formula during the first three days of life. Vitamin A was given to 23 percent of the children and iron supplements to 22 percent. On average, children living in dwellings without improved sanitation, an improved water source, or soap and water at a handwashing station tended to have a lower average z-score for each anthropometric measure included in the analysis as well as for child development indicators (including communication, social-personal, and gross motor skills).

# **5   Balance and Attrition**

## **5.1   Baseline Balance**

Random assignment of the study participants to treatment and control groups ensures that in probability the groups will be similar in their observable and unobservable characteristics. In this section we check that the randomization was performed adequately, resulting in comparable groups.

Appendix 1 shows the mean comparison tests<sup>38</sup> across treatment/control groups for an exhaustive set of variables included in the baseline survey. We compare the characteristics

> 38 The standard errors used in those tests were clustered at the district level, allowing the possibility of intradistrict correlation.

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array of goods and services.<sup>7</sup> The Survey on Social Consumption (SCS) on Health gathers basic information on health, and the role of public and private health providers. It started on a regular basis since 1995 and the most recent waves correspond to years 2004, 2014 and 2017/18. Similarly, the SCS on Education generates indicators on levels of education, school attendance and incentives received by students. The most recent waves were collected in 2007/08, 2014 (January to June) and 2017/18. In both SCSs, household consumption is captured through a single question on “usual monthly expenditures”. Finally, the Periodic Labor Force (PLB) Survey was launched by the NSO in April 2017. This is a continuous survey that collects information about employment and unemployment. Quarterly reports are produced, and only two annual reports have been produced so far: 2017/18 and 2018/19. As in the case of the SCS, it includes a single question on household consumption expenditure.

Two surveys collected by non-government agencies are also available. The India Human Development Survey (IHDS), compiled by several independent research institutions: The National Council of Applied Economic Research (NCAER), the University of Maryland, Indiana University and the University of Michigan. It is a panel survey whose first wave was collected in 2005/06, its second in 2011/12 and the third is scheduled for 2023. In 2017, a subsample round was collected in only three states: Bihar, Rajasthan, Uttarakhand. Finally, the Consumer Pyramids (CP) data set is a continuous survey designed to measure household well-being in India, with a panel survey conducted three times per year since 2014. It is collected by the Center for Monitoring the Indian Economy (CMIE), a private data collection agency.

Using these alternative surveys, the remainder of this section reports summary statistics on recent trends in living standards.

# **2.1. Official data sources*
outside of financial crisis periods - we estimate an alternative specification that links time-varying firm foreign shocks to time-varying firm outcomes using data for the entire sample period before and after the GFC (2004-2017) controlling in some cases for firm fixed effects.<sup>39</sup> This specification captures firm-level adjustment in employment, wages and other performance measures during crises but also during growth and recovery periods. The results show that firms experiencing a negative foreign shock decrease significantly their total employment and wages (see Appendix Table D4) as well as their inputs and productivity (see Appendix Table D5). The impacts on firm employment and wages are also qualitatively similar when alternative time-varying shock measures are used (see Appendix Table D6).

# **Occupational Restructuring, Productivity, and Technological Change Effects**

> 39The specifications are described in Appendix D and control for time-varying measures of import shocks or real exchange rate shocks computed using the same formula as the firm foreign shocks. For the measure of import shocks, GDP growth in destination countries is replaced by GDP growth in countries from which imports are sourced. For the measure of real exchange rate shocks, GDP growth in destination countries is replaced by the change in the bilateral real exchange rate between Brazil and the destination countries. Bilateral real exchange rates are computed based on bilateral nominal exchanges rates from the International Monetary Fund’s International Financial Statistics and consumer price index data from the World Development Indicators.

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, a 36 percent response rate representing six of the seven journals contacted.

# **Methods**

The team employed a mix of qualitative and quantitative methods to answer the research questions. We applied:

- Qualitative methods to separately analyze responses from the 33 structured and semistructured interviews; the 16 responses to the journal editor survey; and the set of 30 World Bank impact evaluations that contained a value for money analysis.

- Statistical methods to separately analyze the sample of 236 impact evaluations drawn from 3ie’s repository; the 30 World Bank impact evaluations that contained a value for money analysis; and the 497 responses to the policymaker survey.

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# **4 Conclusion**

This paper used new data on the content of trade agreements and a structural gravity general equilibrium model to quantitatively assess the economic impacts of deep trade agreements. Based on a clustering of 278 PTAs, comprising 906 provisions grouped in 18 policy areas, we have shown that a group of PTAs is associated with a much larger trade elasticity to PTAs. This confirms that using an average effect of PTAs disregarding the depth of trade agreements is misleading. We then simulated a series of full general equilibrium counterfactual situations for endowment economies, revealing the economic impacts of the intensive and extensive margins of PTAs. Illustrating the method with the example of countries in the Latin America and the Caribbean region, and with countries in the East Asian & Pacific region we showed that deepening existing PTAs is more promising for these countries than signing new ones.

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4 integral part of the reform strategy in that it was intended to soften the distributional impact of any tariff increases brought about as a result of the transition to the new model. In the context of the proposed private-sector participation, it was also hoped that, by reducing the bills of the lowest-income customers, the subsidy scheme might go some way towards attenuating the commercial risk faced by the future concessionaire.

A study was therefore commissioned with a view to providing detailed proposals for how such a new subsidy scheme might function.' The subsidy study comprised three components.

- A household survey designed to collect evidence of water consumption, willingness to pay for water and sanitation services, attitudes towards water privatization and other socio-economic parameters.

- The construction of a simulation model which would permit analysis of the financial costs and socio-economic impacts of alternative subsidy systems. The model, which drew upon the results of the household survey and a number of other data sources, would be used to inform the choice between alternative subsidy designs.

- a A review of the legal and institutional framework of the water and sewerage sector in Panama. The objective of this exercise was to put forward a concrete proposal for the administration and operation of the subsidy scheme, as well as an assignment of responsibilities between the various institutions in the sector.

From this starting point, the subsequent sections explain the general methodology that was applied in order to devise a new subsidy system for Panama, illustrating each stage of the process with data collected during the course of the subsidy study.

'The subsidy study, entitled 'Diseflo de un Sistema de Subsidios y Exenciones para el Sector de Agua y Alcantarillado' was awarded by the Ministerio de Planificaci6n y Politica Econ6mica to a consortium headed by Oxford Economic Research Associates Ltd (UK) and comprising ESA Consultores (Honduras) and EMG Consultores (Chile).
In sum, the results from these simulations suggest that one can reject the hypothesis that there are no gains from further international diversification by holding more stocks within and across countries. In other words, the investment practices documented in the first part of the paper seem indeed to be restrictive. Although there is some heterogeneity in the results depending on the strategy used, the simulated global funds consistently yield higher returns and no greater volatility than the actual global funds, even when comparing funds within the same families.<sup>35,36</sup>

# **B. Benchmarking through a Tracking-Error Model**

Next we consider a different optimization strategy since the objective of most mutual funds is not necessarily to minimize the variance given some expected return, or to maximize returns given some variance. In particular, the performance of mutual funds might actually be evaluated in comparison to benchmark indexes. Moreover, managers might be compensated according to this relative performance. Thus, portfolio decisions should incorporate these managerial incentives. Furthermore, different mutual funds might follow different investment goals. It is possible that some mutual funds follow more passively benchmark indexes while others are more active in seeking returns. Therefore, the difference in returns between the actual global funds and the simulated global funds could, in principle, be explained by different investment practices across global and specialized funds. We address these two related issues in this sub-section.

We first test whether benchmark effects are important in explaining the gains from further international diversification found in the previous exercise. For the case of the variance minimization, we modify the objective function to take into consideration a benchmark index.<sup>37</sup> The benchmark is the appropriate MSCI index ( _B_ ), specific for each global fund as described in the Morningstar database or in the fund’s website. Instead of minimizing the variance of the portfolio, we minimize the variance of the difference

> 35 For robustness, we also perform these simulations with a more restricted sample. We use rolling windows of
effect of migration on trade and their findings will serve as the benchmark for comparison for the results of this paper.

The implementation of fixed effects has successfully been used to solve a number of puzzling results in the gravity model literature. For example, Glick and Rose (2002) proffer a solution to the puzzle found by Rose (2000) whereby currency union membership was associated with an increase in trade of approximately 300%. Glick and Rose reduce this to around 100%, when pair-wise fixed effects are implemented. Similarly, Baier and Bergstrand (2007) control for countries selecting into trading and entering free trade agreements with one another. Once pair-wise fixed effects are included in their estimation these authors convincingly explain the large variation – including negative results - apparent in previous studies examining the effect of RTAs on bilateral trade flows. The current paper implements trading-pair fixed effects to control for international bilateral ties (amongst other unobserved pair-wise factors) to examine the trade-migration nexus.

The present paper is the first to implement a panel spanning several decades to investigate direct-links ( _a la_ Gould) and third party effects ( _a la_ Rauch), both separately and simultaneously; while also crucially controlling for unobserved pair-wise factors such as bilateral ties, which may influence both trade and migration. The focus also moves away from a single country (and her trading partners) and towards groups of countries. More emphasis is placed upon the relationship between trade and migration in the context of developing countries while the longer time dimension of the panel is also superior since most papers investigate immigrant-links in the years after 1980.<sup>10</sup> Significantly, the comprehensive migration data allow the effects of immigration _and_ emigration on trade to be assessed simultaneously, the absence of one of which tends to overestimate the importance of the other.

The paper is structured as follows. The following section discusses the underlying mechanisms which are purported to drive the links between trade and migration and restates the basic framework so as to emphasize the role of the transaction costs – as
# **2. Data and Main Variables**

# 2.1 _Data description_

The main data source we use is firm-level survey data collected by the World Bank’s Enterprise Surveys (ES). In some specifications, we complement the ES with World Development Indicators, World Bank.

The ES are nationally representative surveys of the non-agricultural and non-financial private economy. A common sampling methodology – stratified random sampling – is followed in all the surveys along with a common questionnaire.<sup>1</sup> The sample for each country is stratified by industry, firm-size, and location within the country. Weights are provided in the survey and used in all our regressions so that the sample is representative of the target population.

Throughout, the sample used is a pure cross-section in that each country and firm is included only once. The most recent round of ES available for the country is used. The firms were surveyed between 2006 and 2018. For our baseline results for the main corruption measure, the sample consists of 41,203 firms. Of these, 21,823 belong to the manufacturing sector and the remaining 19,380 are in the services sector. The firms are spread over 124 countries and 7 industries (2-digit ISIC rev. 3.1). For later reference, the baseline sample includes 705 countryindustry pairs. The sample size drops slightly to 41,117 when using the petty corruption indicators due to missing data.

# 2.2 _Estimation methodology_

The baseline regression exercise involves estimating the following equation:

> 1 Details of the sampling methodology and other related information are available at www.enterprisesurveys.org.

9
38

# **References**

- Aggarwal, S., B. Giera, D. Jeong, J. Robinson, and A. Spearot (2022). Market access, trade costs, and technology adoption: Evidence from northern Tanzania. _Review of Economics and Statistics_ , 1–45.

- Amarasinghe, D. and J. S. Bandara (2005). Input output tables for Sri Lanka – 2000. Research Studies: Macroeconomic Policy Series No. 16, Institute of Policy Studies, Colombo, Sri Lanka.

- Artuc, E., S. Chaudhuri, and J. McLaren (2010). Trade shocks and labor adjustment: A structural empirical approach. _American Economic Review 100_ (3), 1008–1045.

- Artuc, E., G. Falcone, G. Porto, and B. Rijkers (2024). Protectionism, evasion and household welfare: Evidence from nigeria’s import bans. _Available at SSRN 4931914_ .

- Artuc, E., G. Porto, and B. Rijkers (2023). Crops, conflict and climate change. Working paper.

- Atkin, D., J. Blaum, P. Fajgelbaum, and A. Ospital (2024). Trade barriers and market power: Evidence from Argentina’s discretionary import restrictions. NBER working paper 32037.

- Baquedano, F., Y. A. Zereyesus, C. Valdes, and K. Ajewole (2021). International food security assessment, 2021–32. GFA-32, US Department of Agriculture, Economics Research Service.

- Beaman, L., D. Karlan, B. Thuysbaert, and C. Udry (2013). Profitability of fertilizer: Experimental evidence from female rice farmers in Mali. _American Economic Review 103_ (3), 381–386.

- Behrman, J. R. and A. Deolalikar (1989). Is variety the spice of life? Implications for calorie intake. _The Review of Economics and Statistics_ , 666–672.
)|(0.12)|(0.20)|
|Observations|818|407|411|

This table reports the results of conditional logit regressions on which program was selected. Odds ratios are reported. “Impact” refers to the estimate of the effect associated with the program; “Quasi-Experimental” indicates whether the study associated with the program was quasi-experimental; “Experimental” indicates whether the study associated with the program was an RCT; “Different country, same region” indicates whether the study associated with the program was described as done in a different country in the same region; “Same country” indicates whether the study associated with the program was described as done in the same country; “Recommended by local expert” indicates whether the program was recommended by a local expert; “Small C.I.” refers to the estimates having small confidence intervals. The omitted categories are “Observational”, “Different region”, and “Large C.I.”. The number of observations represents the total number of choices made across individuals. Standard errors are provided in parentheses. * pă0.10, ** pă0.05, *** pă0.01.

11
that students are required to complete the same number of classes (20) every year. We use the term “classes completed” (or “performance”) to denote the number of classes completed _in a given year_ . We use “cumulative classes completed” (or “cumulative performance”) in a given year as the total number of classes completed _over all years_ up to (and including) that one. A student is on track for on-time graduation when she has completed her on-track requirements, equal to accumulating 20, 40, 60, 80, and 100 classes by the end of years 1 through 5 respectively.

It is useful to classify students into tiers based on their cumulative performance relative to the corresponding year’s on-track requirement. Tiers 1 through 4 correspond to students who complete the following percentage of the on-track requirements for the year: 95 percent or more for tier 1, (85, 95] percent for tier 2, (65, 85] percent for tier 3, and 65 percent or less for tier 4.<sup>4</sup> (See Appendix Table A2 for further details on tier classification). Importantly, a student can change tiers over time—catching up to a higher tier or falling behind to a lower one.

# **4 Stylized Facts**

The data has distinctive features that our model seeks to capture. We describe them below.

_Fact 1: Students of higher income or ability are more likely to enroll in college._ Although the overall enrollment rate is 32 percent,<sup>5</sup> enrollment rates vary widely among student types (see Table 1), and rise with income and ability. On average, the enrollment gap between the highest and lowest income brackets is equal to 55 percentage points (pp)—similar to the 50-pp gap between the highest and lowest ability. Free college may therefore have ample room to raise enrollment.

**Table 1: Enrollment Rates by Income and Ability.*
<mark>The estimated equation is: ln�T</mark> i <mark>�= α + β ∙T T T T t</mark> i <mark>+ γ ∙ITIT TtTI tITI T d bT dIT IT t</mark> i <mark>+ δ ∙ITIT ITtIT T d tT T TItIT IT tT</mark> i <mark>+ φ ∙GTGT T I qITqItq</mark> i <mark>+ ρ ∙T TdI T qI q</mark> i <mark>+ ε</mark> i <mark>. To capture the impact of</mark> **<mark>transportation costs</mark>** <mark>on total trade frictions, the set of variables in T T T T t</mark> i <mark>includes the log of population-weighted distance, and a binary variable indicating if both trading partners are landlocked.</mark><sup>26</sup> <mark>To capture the impact of</mark> **<mark>infrastructure and border costs</mark>** <mark>, ITIT TtTI ITI T d bT dIT IT tT</mark> i <mark>includes the average quality of trade- and transport-related infrastructure,</mark><sup>27</sup> <mark>the average quality of port infrastructure,</mark><sup>28</sup> <mark>the average share of population using the Internet,</mark><sup>29</sup> <mark>the average lead time to import and the average Trading across Borders index.</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
# Figure 1. Actual and potential growth in EMDEs

A. Actual GDP growth <!-- Start of picture text --> A. Actual GDP growth B. Potential A. Actual GDP growth GDP<br>growth<br>Percent 2000-2021 average Percent<br>8 7 Potential growth<br>6<br>4 5 2000-2021 potential growth<br>4<br>0 3<br>2<br>1<br>-4<br>0<br>2000-10 2011-21 2022-30 2000-10 2011-21 2022-30<br>World EMDEs World EMDEs<br>2010 2012 2014 2016 2018 2020 2022 2010 2012 2014 2016 2018 2020 2022<br><!-- End of picture text --> Sources: Haver Analytics; Penn World Tables; UN Population Prospects; World Bank. Note: EMDEs = emerging market and developing economies.

A. Aggregate growth rates are calculated using GDP weights at average 2010-19 prices and market exchange rates. B. Period average of annual GDP-weighted averages. World sample includes up to 53 EMDEs and 30 advanced economies.
Democrats or Independents but not among Republicans. Udalov and Welfens (2021) demonstrate that Internet use is positively associated with several dimensions of environmental concern, including knowledge and pro-environmental behaviors, in high-income and low-income countries. <u>Diehl et al. (2021)</u> find that reliance on social media is associated with a decreased climate skepticism, based on survey data from 20 countries. At the same time, the media can also be a source of climate change disinformation <u>(Ejaz et al., 2023). These patterns are crucial for</u> understanding the relationship between age and climate action because younger cohorts tend to use digital communication tools more than older adults do (Seifert and Cotten 2021).

# **3. Theoretical framework**

We start from the assumption that the age-related variation in support for climate policies is determined by the length of exposure to climate change, the intensity of climate change impacts on wellbeing, and the effectiveness of mitigation and adaptation measures. The expected exposure of the elderly to climate change is shorter than that of younger people, but the risks from the effects of climate change increase with age at any given time.<sup>5</sup> Older demographic groups are at higher risk of being affected by natural disasters like droughts, floods, and hurricanes <u>(Harper 2019).</u> Comorbidities and frailty increase the adverse effects of air pollution and exposure to high temperatures by older people (Gamble et al. 2016).

A simple theoretical framework illustrates how the interplay between the length of exposure to climate change impacts and the intensity of such impacts affects an individual’s attitudes toward climate change. Consider an individual who lives for periods. In every period , she derives utility ) from consuming and faces the cost of climate change ) caused by pollution stock . Function tt TT tt UU(cc is increasing and strictly concave in consumption, that is, tt tt , , and function tt is