rafmacalaba/data-use-mentions-extended huggingface dataset:
periods. Crude death rates were obtained from state data (urban area crude death rate – NITI Aayong, 2022).

_Figure 2: Relationships between temperature and all-cause mortality for demographic groups in India_ Note: Relative risk describes the ratio of excess mortality compared to the mortality rate prevailing at the Optimal Temperature (OT). The Optimal Temperature is defined as the temperature at which mortality rates are lowest. Source: Adapted from Fu et al (2018).

We adopt a Value of Life Years (VOLY) approach to translate mortality impacts into economic terms <mark>(Desaigues et al 2011). This economic term has been employed in prior studies to illustrate the overall expenses associated with premature deaths resultng from excessive heat (as demonstrated in studies by Ebi et al., 2004, and Chiabai et al., 2018).</mark> Previous studies we examined indicated that each heatwave-related death was estimated to result in a loss of life years ranging from 6 to 9. For example, the 2003 heatwave in France, which led to approximately 15,000 excess deaths, was associated with an estimated 100,000 lost life years, equivalent to an average of 6.7 lost life years per excess death (Keller 2015). In contrast, Bosello and Schechter (2013) adopted a fixed value of 8 years for their calculations for the Mediterranean region. When determining the value for lost life years in our study, we considered the fact that India's overall life expectancy is lower than that of France and the demographic structure of India is characterized by a predominantly young population. We calculated the total cost of heat-related impacts by multiplying the 8 lost years by the VOLY metric for India.

7
Although SRS represents the best currently available data source on international flight connections, it suffers from one major limitation: it provides information on bilateral capacity, not true origindestination traffic. For example, SRS reports that there are 74 flights per week from the United States to Australia. However, it does not allow us to identify the proportion of passengers on those flights who actually stay in Australia, and those who use Australia as a transit point only.<sup>6</sup> Although IATA compiles data on passenger numbers based on true origin and true destination, we prefer SRS as a data source because it is more comprehensive in terms of country coverage. It also includes cargo traffic, which is crucial for present purposes because of our interest in examining the links between air connectivity and trade. Indeed, the lack of true origin-destination flows is less problematic than it at first appears in light of the fact that for policy purposes, we are primarily interested in relating connectivity to cargo, not passenger, flows.

Previous work has shown that the international air transport network has many of the characteristics of a "small world network" in the terminology of the applied mathematics literature (e.g., Guimerà et al., 2008). Typically, small world networks have a relatively short average distance between nodes. Due to the presence of hubs which facilitate short connections between nodes, the number of direct connections between nodes tends to follow a power law distribution.

We find both of these properties in the SRS data. The average distance between nodes is 2.3, and the mode is 2. Over 80% of nodes can be reached from any other node in three steps or less (Figure 1), which is consistent with a general rule of thumb in the airline industry. (A three step journey corresponds to two intermediate stopovers between the origin and the destination.) Moreover, a

> 6 There is an obvious analogy here with the trade literature, in which re-exports and re-imports pose frequent measurement
without a household link to formal employment) compared to the counterfactual scenario where all operators are working out of free choice, all else equal based on observables. To the extent that Harare’s informal sector is homogenous (given what can be observed), this effect is thus applicable— it will be less generalizable in the absence of observing data on other characteristics, such as entrepreneurship or, say, a preference to work informally.

# VIII. Conclusions

Businesses in the informal sector may face differing risks of exposure to bribe requests than formal firms; it is not unreasonable to argue that such exposure operates differently outside of the formal economy. This paper puts forth a basic model where the informal sector’s risk of encountering a bribe occurs in an interaction characterized as unstructured harassment, as opposed to a rent extraction in the context of a formal firm soliciting an official service, such as a license or permit. The expectations of this basic model are that an inelastic ability to formalize—in short, a lack of opportunities outside informality—allows for more frequent extraction of bribe payments. Those with a greater ability to pay (in terms of sales) are also expected to encounter demands from corrupt officials. While evidence from a survey in Harare shows robust evidence for the former expectation, there is limited evidence for the latter.

Further work will surely require more data. Such relationships may vary under different circumstances, in different cities, and at different times. These data will hopefully be increasingly available. While this study investigates bribe exposure among heterogenous informal businesses, it does not have information on the size of those bribes; the model’s expectations are that businesses more able to pay will have larger bribes demanded of them. Under constraints of the exposure of corrupt officials, the expectation is that larger-sized bribes are initially preferable to more frequent, pettier rents. Without data on the size of such bribes, these expectations are not testable. While not the aim here, a similar model can be extended over repeated periods
positively affects greenfield FDI by the most diversified firms, suggests that if MNEs are able to absorb discontinuous risk, entry into conflict countries might even increase earnings. As such, MNEs might want to consider entry into conflict countries – taking into account sector and firm attributes, despite the large level of risk posed, with the intention of obtaining a competitive advantage.

The main limitation of this study is that the empirical analysis cannot establish a causal relationship between FDI and political violence; therefore, the results should be interpreted as conditional associations. Although it is unlikely that total FDI flows have a direct effect on the number of battle-related deaths, FDI in the natural resource sector might affect political violence – particularly separatist violence – by intensifying grievances or increasing the perceived gains of secession. However, finding sources of exogenous variation in political violence that can be exploited in a panel format is challenging. Therefore, we address the endogeneity problem by including fixed effects and a large set of control variables, including income and quality of institutions. In the robustness analyses, we also control for the discovery of large oil and gas reserves because it is likely that the discovery of valuable resources rather than the involvement of an MNE fuels conflict. This additional control variable does not change our main results.

Another limitation lies in the data sources used. The data on greenfield FDI flows are collected through Financial Times newswires, internal information sources, other media sources, project data acquired from industry organizations and investment agencies and data purchased from market research and publication companies. MNEs investing in conflict countries might actively avoid publication of the investment project in the media to avoid a public outcry. This selection effect could drive our results on the effect of political conflict on total greenfield FDI flows. To our knowledge, however, there are no FDI data sets that are not based on media coverage while simultaneously covering an equally large set of countries and allowing for disaggregation at the sector level. Nevertheless, it is unlikely that our results on sector heterogeneity are driven by sample selection
census tract data on education and wealth for 2007. Moreover, to disentangle mechanisms, we combine information from multiple sources on measures of social capital, land markets, and trust.

A review of the validity of the empirical design shows that all geospatial and economic variables observed prior to the Civil War vary smoothly around the boundaries of rebel-controlled areas. In particular, the use of geocoded data from multiple sources—including covariates that proxy state capacity, violence, demographics, agricultural production, and land concentration—confirm

> 3The only counterinsurgency strategy promoted by the Salvadoran government was the CONARA (Commission for the Restoration of Areas) in 1983. This initiative was implemented in two departments (San Vicente and Usulut ́an) but did not target guerrilla territory. It was similar to the Strategic Hamlet Program in South Vietnam and aimed to halt the influence of communism. However, the plan failed to produce the expected results and was quickly discontinued.

3
, and asked whether these lead firms were:

- improving conditions for women, small-scale farmers and farm workers;

- promoting equitable and sustainable access to and use of land and water;

- reducing emissions and helping farmers adapt to climate change; and

- being transparent about their supply chains and broader corporate activities.

Scorecards established by Oxfam reveal very different behaviors of lead firms vis-à-vis suppliers in the GVCs (http://www.behindthebrands.org/en-us).

# _(1) Responsible investment_

Stakeholders in host countries should carefully review supplier codes and guidelines and help with their implementation as appropriate. They should also create incentives for lead firms to comply with major principles for responsible investment and business. These include references such as:

- The UN Principles for responsible investment<sup>2</sup> :

- Principle 1: We will incorporate environmental, social and corporate governance (ESG) issues into investment analysis and decision-making processes.

- Principle 2: We will be active owners and incorporate ESG issues into our ownership policies and practices.

- Principle 3: We will seek appropriate disclosure on ESG issues by the entities in which we invest.

- 2 Available at www.unpri.org . In early 2005, the then UN Secretary-General, Kofi Annan, invited a group of the world’s largest institutional investors to join a process to develop the Principles for Responsible Investment. A 20-person Investor Group drawn from institutions in 12 countries was supported by a 70-person group of experts from the investment industry, intergovernmental organisations and civil society. The Principles were launched in April 2006 at the New York Stock Exchange (Source: http://www.unpri.org/about-pri/about-pri/history/).

38
*_GVC_forward_** and **_GVC_backward._**

Figure 6 shows the variation of GVC participation across all 61 countries. The mean value has not changed much in the eight years to 2017, it remains around 2.5 though the skewness has led to higher values of more sectors in 2017 (bottom panel of Figure 6). Appendix table 1 lists the classification of sectors.

> 4 There are four major sources most frequently used: The World Input-Output Database (WIOD), the Organization for Economic Co-operation and Development’s (OECD) IOT database and ICIO database, the Eora Multi-Regional Input-Output database, and the ADB’s MRIOT database. The WIOD only covers 40 economies including 6 Asian economies and goes to 2015; the OECD IOT and ICIO data covers 61and 74 economies, respectively, but the latest available data goes to 2015. The Eora database has a wider coverage of countries, but the structure of smaller countries is derived from similar countries, and not from country-specific national accounts. Moreover, sectoral data are highly aggregated.
>more years of<br>schooling|0.402|0.822|0.417|0.843|0.496|0.933|
|Landholdings|4.416|26.330|7.692|32.184|4.571|10.696|
|Frequency of Transport|7.873|5.990|8.375|5.211|9.300|5.990|
|Inaccessibility During<br>Weather Shocks<br>(Dummy)|0.127|0.334|0.146|0.354|0.156|0.363|

**Source:  Analysis of ENHRUM data**

33
give valuable indications as to problem segments (such as high rent or housing cost ratios) that could be addressed by public policies (such as rent allowances), or the impact of certain policy measures (such as removal of rent controls).

In-depth country-by-country rental sector analysis is advisable for all studied countries. The minimum empirical program should include stock and flow modeling, as well as pricing analyses along the lines presented in this chapter, with more detail on specific hypotheses. If household survey data are insufficiently detailed or incomplete, additional surveys in selected urban areas should be conducted. Supply factors such as investor types, regulations, and tax treatment should be addressed, too (see Chapter 4). A survey design template for such studies appears in Annex 2.

The costs of such empirical efforts can be easily justified by the social and private benefits that policy action in favor of a broader and better functioning rental sector would bring. It is particularly advisable for countries experiencing significant private rental sector shortages (Russia and Romania in the study), or facing controversial policy choices, such as the transition from rent control to a market-based system (Poland). Worth further exploration are the interactions between the rental sector and labor market mobility, also in light of the developing spatial economics literature. A better calibration of labor market effects might help governments determine the right focus and scale of rental sector policies.

# **Tenure Policy Research**

There are two relevant areas of future research in tenure policy: (i) detailed analysis of national rental housing policy frameworks; and (ii) cross-country policy studies deepening the understanding of actual practice.

Annex 2 contains a rental housing study template that combines elements of both empirical and policy analysis. In the policy section, it broadly follows the outline of this chapter. Such a template should be applied systematically in transition countries both to inform domestic policy debates and design, and to facilitate international comparison and exchange, including policy dialogue with the Bank.

There is also a need for better
as collateral. This means that, in general, households have an incentive to over- rather than underreport their land to the bank, whereas households in the vicinity of the program cutoff would have had to manipulate their documented land downward to benefit from the program. _Third_ , several mechanisms were in place to assure faithful implementation and prevent the ex-post manipulation of land documentation. As a transparency measure, all bank branches were required to publicly post the land records and debt relief details of all eligible individuals. Banks themselves had multiple levels of internal audits and the central bank and local regulators performed further audits. Finally, I test for robustness to corruption concerns by auditing official land documents using a statewide electronic database of landholdings. Electronic land records are administered by a central authority and cannot be amended by local administrators. Detailed results of these land audits are reported in the Supplemental Appendix. All results are presented for the sample of all surveyed households, as well as a robustness sample of households with audited and matching land records for which land manipulation can be ruled out. In 13
# **1 Introduction**

This paper estimates the long-run benefits of maternal care and childcare. The long-run outcomes are of interest for three reasons. First, many effects of an early-life intervention remain latent for a long period; outcomes at birth or during early childhood may not fully capture these latent effects (Miller and Wherry, 2018). Second, the effects of such a program on human capital formation, economic and labor market outcomes can only be fully understood during adulthood. Third, subsequent parental investment may lead to a catch-up in the long-run. Thus, early life differences in health may not lead to similar long-term differences (Crimmins and Finch, 2006; Sohn, 2017). There are a limited number of studies on the long-run impacts of maternal care and child care interventions because datasets that track individuals over long periods of time and collect detailed data on several dimensions of health, education, and labor market outcomes, are rare. This paper uses multiple waves of the Indonesian Family Life Survey (IFLS), a detailed panel of households spanning over a period of 22 years. The long-run panel nature of the dataset helps tracking individuals from childhood to adulthood.

This paper studies the Village Midwife Program, a central intervention in Indonesia for increasing access to antenatal care, postnatal care, and safe delivery services among reproductiveage women from families of all social backgrounds. The program was introduced in 1989 and was rolled out in a phased manner, with villages in poor and remote communities getting priority (Frankenberg and Thomas, 2001; Frankenberg et al., 2005, 2009; Cas, 2012). This paper uses a difference in difference strategy that combines the spatial variation in the rollout of the program with a temporal variation by comparing individuals who were old enough (five years and older) at the time of the roll-out of the program with individuals in their early life ( _in utero_ or in their first three years).<sup>1</sup> Thus, the comparison is between these two groups
opportunities than wealth levels: children age 6-15 belonging to vulnerable categories represent 45 percent of the total population of children of that age and receive only 37 percent of public benefits.

# **[Figures 3a and 3b about here]**

# **5.3 Redistributive Simulations**

Table 4 presents the results of the four simulated scenarios. Simulation 1 has an _increase in total government transfers by an additional 70 percent equally distributed to all children eligible to_ _attending public school._ This additional amount is the share of the budget that would be required to equalize the current salaries of teachers to regional standards advocated in the Fast Track Initiative, Education for All (see World Bank 2010). The simulation increases by 70 percent the current public transfer to each child eligible to attend public school.

Simulation 2 represents an _increase in transfers for all children eligible to attend public schools in the form of fee expenses recovery_ . In policy terms, the intervention conceived in this scenario is a voucher for each child eligible to attend a public school equivalent to the average monetary cost of households‘ contributions in the form of implicit fees to the public school (current fees are informal or implicit since they are officially eliminated). This does not necessarily imply that each specific household would be exactly compensated by the amount of fees paid as reported in the CWIQ but by the _average_ fees paid by children attending public school at age 6-15.

24
less likely to increase as a result of positive commodity price shocks. These findings are consistent with Andersen et al. (2017) that finds that exogenous shocks in petroleum income increase hidden wealth in offshore accounts for economies where institutional checks and balances are weak.<sup>8</sup>

# _4.2 Robustness Checks_

_Sector of activity and structure of the economy_ The estimates provided thus far are based on parsimonious specifications. In the following, we explore the robustness of the baseline findings along several dimensions. First, the structure of the economy may be an important predictor of billionaire net worth. Second, the sector of billionaire activity may also matter, to the extent that it varies over time. In tables A3 and A4, we replicate tables 1 and 2 respectively with the inclusion of the share of manufacturing and agriculture as a percent of GDP as additional covariates. The sign, significance and magnitude are relatively unchanged for the commodity price shock and resource rents coefficients.

The Forbes magazine database does include data on the billionaire sector of activity that encompass about 57 sectors of activity. However, this variable is measured with error given a single billionaire can be involved across multiple sectors. Furthermore, the 57 sectors do not seem to be mutually exclusive. We therefore recategorize the 57 sectors into 6 broad categories (see table A7) that include: (a) Agriculture (b) Extractives (c) Manufacturing (d) Services (e) IT and (f) Others. In tables A5 and A6 we present the results for commodity price shocks and resource rents respectively, after accounting for sector fixed effects for the narrow 57 categories, and the broad 6 categories. Our main results are robust. Indeed, the magnitude, sign and significance of the coefficients are similar to our baseline estimates.

> 8 See Ross (2015) for a summary of the literature on the relationship between institutions and commodity booms.

8
unemployed increased from 6% to 10%. These figures are in line with the decline in GDP per capita and the rise in unemployment rates reported in national statistics and the worsening regional conditions, reported in Table 6. Furthermore, the deteriorating objective economic conditions are reflected in deteriorating economic perceptions. Personal economic optimism declined from a 2.6 to a 2.4. Whereas in the period from 2010 to 2014 67% of the people felt their life was getting better, this share declined to 57% in the period from 2015 to 2020. Positive expectations regarding the local economy plunged from a 2.4 to a 2.0, with the percentage of people with positive expectations regarding the local economy declining from 55% to 42%. In addition, leadership approval plunged from 52% to just 23% of respondents approving the government; confidence in national institutions declined too.

At the same time, not all conditions deteriorated considerably. Social support declined but remained high (at 90%), while reported education levels, civic engagement, acceptance of diversity, digital access, satisfaction with socializing opportunities and health care, and perceived safety improved in the second half of the 2010s.<sup>20</sup> Yet, as shown in Figure 6, only improvements in digital access partly mitigated the negative effects of the economic crisis on SWB.

**Figure 5. SWB decline by demographic group**

<!-- Start of picture text --> SWB decline<br>0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.2<br>Age<br><30<br>30-45<br>45-60<br>60+<br>Gender<br>Men<br>Women<br>Partner<br>Partner<br>No partner<br>Education<br>Elementary<br>Secondary<br