rafmacalaba/data-use-mentions-extended huggingface dataset:
# 1. Introduction

Natural disasters have an impact on poverty through many different channels (economic growth, health, schooling, behaviors) that are difficult to quantify. It is nonetheless possible to assess a fraction of the full effect. Here, we quantify the short‐term impacts that natural disasters have on poverty through people’s income when they are hit.

To do so, in this study we built a counterfactual scenario of what people’s income would be today in the developing world in the absence of natural disasters. This scenario is based on the same methodology as in Rozenberg and Hallegatte (2015) and the _Shock Waves_ report (Hallegatte et al. 2016).

It uses household surveys of 1.4 million households, which are representative of 1.2 billion households and 4.4 billion people in 89 developing countries.<sup>1</sup> The household surveys were formatted for the GIDD model, using the I2D2 database (Osorio‐Rodarte, Cruz, and Bussolo 2015). Here we used an updated version of the database, harmonized in 2012, and using 2011PPP USD for household income. Therefore, we use 1.90 USD 2011PPP per day as a threshold for extreme poverty in this study.

Depending on where they live and work, what they consume, and the nature of their vulnerability, we calculated the additional income that each household in the survey could earn every year on average in the absence of natural disasters. We then assess the average number that are living today with less than $1.90 per day only because they have been affected by a disaster.

# 2. Estimating income for farmers and nonfarmers

The model first attributes one of the following mutually exclusive categories to each person in the household surveys database: (1) agriculture worker; (2) manufacturing worker; (3) services worker; (4) adult not in the labor force; (5) elderly (above 65 years old); (6) child (under
All study GPs, including control GPs, continued to receive all other activities from the MFI. The intervention began in February 2015. Care was taken throughout the study period to ensure that the integrity of the research design was preserved. Authors conducted briefing sessions with the branch staff of the MFI before the start of the intervention, provided a pictorial reminder of the GPs where sanitation credit could not be offered, and monitored the disbursement of sanitation credit to control GPs using the MFI’s administrative monitoring system. As a result, contamination of the control group was very limited: a small number of loans was given out in the control group a few months after intervention roll-out, but this was swiftly stopped once noticed by the research team.

# **3.2 Data**

Our analysis draws on three sources of data. The first is an extensive household survey collected by the authors. This is linked with administrative loan data from the MFI partner. The final source of data is credit bureau reports, providing information on loans taken by sampled clients from all micro-finance providers in the study areas.

## **3.2.1 Primary Survey Data**

A survey on a sample of clients that had been active at the time of the roll-out in February 2015, and their households, was conducted in the period August to September 2017, about 2.5 years after sanitation loans were first made available. 2,841 clients (on average 24 per GP) were interviewed by a survey company (with interviewers blind to the outcome of the randomisation): 1,253 in the treatment and 1,588 in the control group.<sup>17,18</sup> Overall, we sampled around 75 percent of all clients active at the time of the intervention launch. Our sampling strategy focused on including clients from the same lending centre (kendra), in order to allow us to collect information on joint liability groups. Though it is not a random sample of clients, our
distorted equilibrium’s average firm size coincides with the empirical one (i.e., until the dots in Figure 3 are all lined up in the 45-degree line).

Formally, given the estimate of _γi,_ we guess a value of _τi_<sup>_E_and solve for the</sup> distorted competitive equilibrium under distortion pair � _τi_<sup>_E, γi_</sup> �. We compute the equilibrium average size ratio with respect to the undistorted economy and compare it against the average size in the data relative to the US. Guided by the theoretical results, we update the guess of _τi_<sup>_E_</sup> upwards if the average size still falls below the data and update it downwards if it rises above. 30 The results are plotted in Figure 4.

Figure 4: Model-Based Entry Tax Rate versus GDP per Capita <!-- Start of picture text --> Kenya<br>India<br>Salvador<br>Ethiopia ColombiaChile<br>Ghana BulgariaPeruRomaniaHunPortugary gBelgiumal<br>FranceFinland<br>Latvia Italy<br>Spain<br>5 6 7 8 9 10 11<br>log GDP per capita<br>2.5<br>2.0<br>1.5<br>1.0<br>0.5<br>log(1+TauE)<br>0.0<br>−1.0<br><!-- End of picture text --> Note: The figure plots the model’s estimate for the entry tax _τ_<sup>_E_</sup> against the log of GDP per capita. Data for GDP per capita correspond to the year 2014 and are drawn from the Penn World Table version 9.0.

The figure shows that entry barriers are sizable in the least developed economies and decrease to roughly zero in the most advanced ones. The model backs out mild entry subsidies for Latvia, Spain,
>79.2|
|Other Consumer Goods|53.5|58.4|67.1|70.0|72.9|72.2|<br>73.5|<br>73.3|
|Fuels|43.3|56.6|41.3|39.6|25.5|40.2|<br>55.3|<br>34.6|
|All Goods<br>|50.4<br>|55.7|62.6|64.6|65.0|66.8|<br>69.8|<br>69.7|

1/ Include EU-25, EFTA, Romania and Turkey. Source: Based on Bulgaria’s data reported to the UN COMTRADE Statistics.

As a result, Bulgaria has been increasingly integrating into pan-European markets for more processed goods. These markets took 64 percent of Bulgarian exports of machinery in 2003, up from 61 percent in 1999 and 79 percent of automobiles and parts in 2003, up from 55 percent in 2000. However, the latter accounted for a miniscule part of Bulgaria’s total exports.

# **C.** _Level of technology embodied in EU-oriented exports and competitiveness_

Although, not surprisingly, low technology activities continue dominating Bulgaria’s EU15 oriented exports, products of medium to high technology emerged in 2002-03 as levers of Bulgarian exports (see Section B above for the filter used to identify exports according to technological level). These products registered growth exceeding the growth of EU-oriented
shipping days, three-month for 30 to 59 shipping days, and four-month for more than 60 shipping days.

- (iii) For landlocked exporter and/or importer countries, we add the number of days needed to transport goods by road from (or to) the closest port to (or from) the capital using the shortest road distance from Google Maps as in Akbar et al. (2018) and Zarate (2021).

# **Product vulnerability measures**

We rely on several data sources to construct proxies for production resilience which we map to our HS4 product categories. First, we use data from US NBER-CES Manufacturing Industry Database on the unskilled labor intensity of production: the ratio of unskilled (blue-collar) employment to capital for each 6-digit 1997 NAICS industry in 2011 (the most recent year available).

Second, we rely on OECD’s harmonized input-output tables for 2011 to compute sectoral imported input contents following Hummels et al. (2001).<sup>3</sup> We compute the reliance of production on imported inputs as the ratio of imports over the sum of output plus imports minus exports by ISIC 2-digit industry and exporting country. Using a measure with country variation (from the input-output table) accounts for different countries’ sources of different inputs.

Third, we use export data from UN COMTRADE at the exporting country-HS4-year level combined with the aforementioned OECD harmonized input-output tables to construct measures of (i) the reliance on China as a supplier of inputs for production of each sector and (ii) the

> 3 OECD input-output tables are available for 63 countries (all 36 OECD countries and a variety of other countries including several developing countries). Since our monthly trade data cover exports for an additional 158 countries with no OECD input-output tables, we assign to each of those countries the input-output table from the country that is most similar in terms of three dimensions: level of development captured by GDP per capita, size captured by population and economic structure captured by share of manufacturing value
20 economic growth that took place during the last decade may have caused a generalized improvement in economic conditions that improved child survival.

The rapid decline in infant and under-5 mortality that has taken place in recent years in many countries in Sub-Saharan Africa is an important and largely unrecognized trend that merits further analysis to understand its underlying causes. This study presents some modest findings suggesting that it is likely that the rise in usage and ownership of ITNs played a role in the decline in infant mortality in Kenya, which constitutes a small part of the much broader phenomenon of the reduction in under-5 mortality across many countries. The broader story, and in particular the role of economic growth, could be better analyzed in a study similar to this one, but using data across many countries. That analysis remains as a project for future work.

# **Annex**

**Data description and imputation procedures – DHS microdata**

The data used in the analysis is from the Demographic and Health Surveys (DHS) conducted in Kenya in 2003 and 2008-2009 (hereafter 2008). The DHS surveys collect information from women aged 15-49 years on their full birth histories, children's health status, and household characteristics, among other things. We focus on individual mortality outcomes of children born 12-35 months before the interview. An attempt was made to reach the highest possible precision when restricting the sample. Thus, the sample was created using data on the day of birth and day of interview. For observations with unknown day of birth, data on the month of birth were used. Our full sample comprises 4827 observations. Due to missing values on explanatory variables, a total of 159 observations was excluded from the analysis, yielding the final sample of 4668 observations. The 2295 observations from the DHS 2003 and 2373 observations from the DHS 2008 correspond to actual live births that took place in Kenya in April 2000-August 2002 and November 2005-February 2008, respectively.

Child mortality is measured at individual level by a dummy variable which takes the value 1 if a
Data for the transition economies clearly show the role of market forces in shaping firm dynamics (Figure 2). At the beginning of their transition to a market economy, both gross and net firm flows were large compared to industrial and other emerging economies: in some of the transition economies a large fraction of firms were closed down and replaced by new small ventures, and this process accounted for more than 10 percent of total employment. As the transition moved forward gross and especially net flows declined to reach, at the end of the 1990s, values fairly close to those observed in other countries.

**Figure 2: The evolution of gross and net firm flows in transition economies, business sector Panel A:  Gross firm flows**

<!-- Start of picture text --> Slovenia Hungary<br>50.00 50.00<br>45.00 45.00<br>40.00 40.00<br>35.00 35.00<br>30.00 30.00<br>25.00 25.00<br>20.00 20.00<br>15.00 15.00<br>10.00 10.00<br>5.00 5.00<br>0.00 0.00<br>92 93 94 95 96 97 98 99 94 95 96 97 98 99<br>Gross firm flows Net firm flows Gross firm flows Net firm flows<br>Latvia Romania<br>50.00 50.00<br>45.00 45.00<br>40.00 40.00<br>35.00 35.00<br>30.00 30.00<br>25.00 25.00<br>20.00 20.00<br>15.00 15.00<br>10.00 10.00<br>5.00 5.00<br>0.
in-kind education services; women of childbearing age have greater health care needs; households with older, non-working older male members may qualify for old-age support.

The employment status of household members plays a role too. For instance, the employment status of a married couple can influence effective marginal tax rates on “secondary” income. Who takes part – and how frequently – in social reproduction can influence the impact that education service provision has: preschool children require more care while school age children require less, but school-age girls may be called on to provide some or all the care of younger dependents. And if women (rather than men) are more responsible for social reproduction, they may not look for paid employment.

# Household Typologies: Bringing Care and Social Reproduction into the Picture

The size and organization of the household are observable in household budget surveys, income and expenditure surveys, living standards measurement surveys, and other survey instruments used in standard CEQ assessments. We propose, therefore, that the CEQ assessment toolkit be adapted to estimate fiscal policy impacts on households according to their demographic (sex and age) and employment-disaggregated characteristics.

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4 <!-- Start of picture text --> Pension Assets Relative to the Economy<br>(%of GDP)<br>80s<br>60<br>40<br><!-- End of picture text --> Notes: (I) Data pertain to year-end 1994 for Indonesia and year-end 1991 for other countries. (2) For Singapore, Sri Lanka, Kenya and Malaysia, only national provident funds are covered.

Sources: World Bank, _Averting Old Age Crisis,_ and data supplied by the government.

Given Indonesia's already high domestic saving rate, wider use of pensions may not make much of a difference in raising the volume of savings. Studies of pensions' impact on saving have not been conclusive, but they suggest that the overall effects are not large and depend on the type of pension schemes adopted (see box 3). Nonetheless, as more saving is channeled through pension mechanisms, the demand for long-term financial instruments may be expected to rise. The resulting financial services that emerge to fulfill this demand would contribute to capital market development. Domestic placements of stocks and bonds, whether private or public, would have better prospects. Domestic financial markets would offer more financing options to investors, and thereby lessening the reliance on external debt.
5 following the seminal work of Krueger, Schiff, and Valdés (1988; 1991), which covered between 15 and 25 years prior to 1985 for just 17 developing countries.<sup>4</sup> Fortunately, a new database of agricultural distortions has been developed recently by the World Bank (Anderson and Valenzuela 2008, updated and extended by Anderson and Nelgen 2012b). This new data complements and extends the OECD’s PSE/CSEs and the Krueger, Schiff, and Valdés studies. It builds on those earlier databases by providing similar estimates for other significant (including many low-income) developing economies, by estimating new and more comprehensive policy indicators, and by providing measures of price distortions also for non-agricultural tradables.

The new World Bank database includes estimates for 82 countries, which together account for between 90 and 96 percent of the world’s population, farmers, extreme poor living on less than $1.25 per day, agricultural GDP, and total GDP. The sample countries also account for more than 85 percent of agricultural production and employment in each of Africa, Asia, Latin America, and the transition-economies region of Europe and Central Asia, as well as for all of agricultural production and farm employment in OECD countries. In the data set, the spectrum of per-capita incomes ranges from some of the poorest countries (Zimbabwe and Ethiopia) to some of the richest (Norway). Not all countries had annual data for the entire 1955–2010 period, but the average number of years covered is 45 per country. (The full list of developing countries by region, plus lists of the transition economies and high-income countries in the data set, is provided in the Appendix Table.) Nominal Rates of Assistance (NRAs) and Consumer Tax Equivalents (CTEs) are computed for 75 different farm products, with an average of almost eleven per country. This product coverage represents about 70 percent of the gross value of agricultural production in each of the focus countries and just under two-thirds of global
prices using the deflators available in the VHLSS.

> 35 According to the panel individuals in the VHLSS, the workers who moved from the informal wage and selfemployed sectors to the formal sector increased their hours worked by 8.3 percent and by 24.3 percent respectively. Unfortunately, the income changes for those who moved from self-employed to formal sector jobs are not reflected in the paper because no 2002 wage information was available for self-employed individuals.

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same as in equation [1]. Specification [5] is an OLS regression run only for SLBs with step-up penalties following specification [2]. Specification [6] is a logistic regression run for all SLBs for which CO2 emission data is available.

**<u>Table 7: Bond-Level Regression Analysis for Target Period with CO2 Emissions</u>**

||(1)<br>Model 1|(2)<br>Model 2|(3)<br>Model 3|(4)<br>Model 4|
|---|---|---|---|---|
|CO2Emissions (tens of<br>millions tonnes)|0.005***|0.007***|0.008***|0.013***|
||(0.001)|(0.002)|(0.002)|(0.003)|
|Investment grade dummy||0.120**||0.163***|
|||(0.050)||(0.052)|
|Amount issued (US$ billions)||0.094||0.117|
|||(0.086)||(0.088)|
|Tenor (years)||-0.005||-0.001|
|||(0.008)||(0.007)|
|Total assets (US$ billions)|||-0.001|-0.002***|
||||(0.001)|(0.001)|
|Leverage (%)|||-0.221|-0.064|
||||(0.156)|(0.165)|
|Public organization dummy|||-
.112)||(0.0950)|(0.0958)|(0.108)||(0.0526)**|(0.0532)**|(0.0630)***|
|IDN exports per worker *||||0.313||||0.418||||-0.258|
|Share of hhlds with computer||||(0.284)||||(0.273)||||(0.195)|
|Observations|195|195|195|195|195|195|195|195|195|195|195|195|
|R-squared|0.940|0.941|0.941|0.941|0.961|0.962|0.961|0.961|0.934|0.935|0.935|0.936|

Source: Authors’ calculations based on Sakernas 2005-2010 and 2011-2015, Susenas 2005-2010, 2015-2016 Philippines STEP survey, and 2011-2015, and UN Comtrade database 2005-2010.

Notes: IV regressions. IV: Global demand for foreign products excluding Indonesian products. Indonesian exports per worker in thousands of USD at 2010 prices and global demand for foreign products in millions of USD at 2010 prices. ICT variable at the province level is the share of households with computer. Province controls include the age structure of the population, share of urban population, real GDP per capita, minimum wage level, gender and educational composition of employment. All models control for province and year fixed effects. Robust standard errors between parentheses clustered by province. ***, **, and * indicate significance at 1%, 5%, and 10% confidence levels, respectively.

44
assets (Smith and Stulz, 1985; Froot et al., 1993) or they might try to time the market, issuing floating rate debt when the yield curve is steep (Faulkender, 2005). Although we do not directly test and compare these views, we do find that international bond issues have a higher fraction of fixed rate contracts, which seems to suggest that investors in international markets have a lower preference for interest rate risk. Taken together, these results indicate that firms issue very different types of bonds across different markets.

Fourth, the paper contributes to a large literature that studies financial integration using price-based measures.<sup>9</sup> This literature builds from the premise that under full financial integration the law of one price should hold. That is, securities with identical cash flows should command the same price irrespective of the market where they are issued, and thus the literature interprets pricing differentials as evidence of market segmentation. A key empirical challenge to this type of analysis involves identifying comparable assets across markets (Levy-Yeyati et al., 2009; Japelli and Pagano, 2010). Our sample of corporate bond issues around the world helps address this challenge, as many firms issue debt securities both at home and abroad, allowing us to compare borrowing costs between issues conducted by the same firm in different markets.

The rest of the paper is organized as follows. Section 2 describes the data and presents descriptive statistics. Section 3 characterizes the main non-price features of corporate bond issues in domestic and international markets. Section 4 analyzes how firms that issue debt abroad use domestic and international bond markets following their internationalization. Section 5 discusses whether differences between issues at home and abroad depend on the firms‘ country

> 9 Several studies use stock market data to analyze market integration (see, among many others, Bekaert and Harvey, 1995; Soydemir, 2000; Masih and Masih, 2001; Scheicher, 2001; Carrieri et al., 2007). Other papers focus on the (covered and uncovered
trajectories they had not considered before or to change their view on their abilities to do successfully the ones they knew.

In parallel, a set of observational studies based on panel data consistently show positive correlations between aspirations and outcomes later in life, even when controlling for confounding factors. For the case of education, young people aspiring to go to college in Ethiopia, India, Peru, and Vietnam were more likely to attend postsecondary education as young adults (Favara, Chang, and Sánchez 2018). Higher aspirations also correlate with better academic outcomes: students in France with higher educational aspirations at the beginning of ninth grade also have better test results at the end of the grade and a higher probability of assignment to an academic track than a vocational track in grade 10 (Guyon and Huillery 2021). Similarly, in Brazil college aspirations of ninth graders are highly correlated with class attendance in eleventh grade, students’ performance in twelfth grade, and with a lower probability of dropping out during secondary school (Gagete-Miranda 2020). Following the theory, a plausible channel is that children with high educational aspirations exert more efforts in their studies, perform better and complete more years of schooling. It is also likely that, along the way, adolescents’ better schooling outcomes reinforce their aspirations and vice versa.

# **Labor market outcomes**

Higher aspirations correlate with better labor market outcomes. The higher aspirations leading to increased education are likely the channel through which aspirations correlate with better labor market outcomes. For example, in Great Britain, individuals who were 16 years old in 1986 who aspired for better quality jobs had higher earnings 26 years later in their mid-careers (Green et al. 2018).

International child sponsorships have been found to increase aspirations and labor market outcomes. This is a program whereby sponsors from high-income countries provide a monthly cash transfer and pay for mentoring and social activities with church and community volunteers. It has been found to raise children’s hope and self-efficacy, which are thought to be some of the