rafmacalaba/data-use-mentions-extended huggingface dataset:
Capital markets in the South remain fragmented and very imperfect. Besley discusses Gershenkron's conjecture (1962) about the relation between economic development and the development of financial intermediaries, which is supported by data assembled by Goldsmith (1969), who has discovered that the ratio of the value of financial instruments to wealth rises during economic development. This evolution, which had been held back as governments seized control of the "commanding heights of the economy", should unfold rapidly now that capital markets are being liberalized.

# 9.5) Foreign Capital and Its Intermediation

Chapters by Eaton, Cardoso, and Dornbusch and Helleiner discuss North-South capital flows and review their history. Jimenez's and Krueger's chapters examine how effectively planners allocate foreign capital and domestic saving to profitable investment opportunities.

Eaton provides a cogent overview of the relevant theory. Reading him, one cannot avoid pondering the fact that the North-South flow of private investment remains very low in view of factor scarcities in the two parts of the world. The stock of Northern funds in the South is not insignificant, it is true, and Cardoso and Dornbusch36 note that it amounted to 30 percent of US GNP in 1987; only 15 percent was foreign investment however. Expanding this stock could accelerate development. Even today<sup>37</sup> , world capital flows are much smaller in proportion to GNP than before the first World War. An upsurge followed the first oil shock, but this ended in disaster in Latin America and in countries such as Morocco, which borrowed to postpone adjustment, but countries that managed their affairs recovered rather fast from the 1982 debt shock.

The gradual vanishing of the foreign exchange constraint that the two gaps model highlighted has improved the South's ability to absorb foreign capital. In 1962, the year of publication of Chenery and Bruno's seminal article, Cairncross38 already wondered whether it is appropriate to view a shortage of foreign exchange as a limiting factor in development, as distinct from a shortage of production factors. One
including the level of education, related work experience, on-the-job training, and job-related professional certifications.

The SDS modifies the Education and Training questionnaire in several ways. The SDS uses the Vietnam’s education classification taxonomy, asks for field of studies required for the job, shortens the length scales used for work experience and training, and removes the question about apprenticeships given their infrequent use in Vietnam.

**Module IV.** Module IV collects demographic information on respondents, including age, gender, education, experience, and type of employer.

_Targeted occupations_

**The SDS survey selected occupations that are in-demand and/or relevant for the growth of strategic sectors of Vietnam’s economy.** While in the long run it would be ideal to survey all occupations in Vietnam, given resource constraints the SDS pilot focused on 30 occupations. . The 30 selected occupations represent 31 percent of 2018 employment.  . Occupations selected for the SDS had to meet several selection criteria.

- <u>Minimum sample. Occupations had to have a minimum sample of 20 respondents in the latest</u> rounds of the Labor Force Survey (March and September 2021) in Vietnam’s major employment centers (Ha Noi, Ho Chi Minh City, Da Nang, Vinh Phuc, and Dong Nai).

- <u>Exclusion of residual occupations. Occupations could not be “residual occupations,” that is,</u> an occupation with “not elsewhere classified” in its title.<sup>10</sup> These occupations tend to have vague descriptions.

> 10 This is all 4-digit occupations ending in 9.

7
Delaporte & Pena, 2020) to assess the ability to working from home. For example, Hatayama et al. (2020) utilize data from 53 countries on the task content of jobs to assess the amenability to working from home and find that lower income countries and male, less educated and self-employed workers have jobs less amenable to working from home. Other studies considering the issue of remote work and closures predicted a job crisis disproportionately affecting lower income and female workers, who tended to hold more jobs requiring faceto-face interactions (Avdiu & Nayyar, 2020). The IMF (2020) also found that the high proportion of jobs involving personal contact and low amenability to working from home in Latin America made that region’s jobs particularly vulnerable to loss relative to sales losses – largely due to exits from the labor force.

Some recent studies have also quantified adverse impacts on employment in developing countries, such as India (Beyer, Franco-Bedoya & Galdo, 2021; Deshpande, 2020; Dhingra & Machin, 2020) and Nigeria (Avenyo & Ndubuisi, 2020). Other studies such as Khamis et al. (2021) and Kugler et al. (2021) have conducted cross country analysis using data from high-frequency phone surveys (HFPS) conducted by the World Bank, covering countries across all developing regions. The former estimates that 19 percent of workers in lowincome countries, 37 percent in lower-middle-income countries, 41 percent in upper-middle-income countries, and 26 percent in high-income countries experienced a work stoppage.The latter finds that larger shares of female, young, less educated, and urban workers stopped working than others. Gender gaps in work stoppage were particularly pronounced and stemmed mainly from differences within sectors rather than differential employment patterns across sectors.

As the crisis continues to unfold, more papers have turned to the importance of labor demand shocks. Using real-time surveys, a number of researchers have documented the impact on layoffs by private firms of sales loss, closures, or liquidity issues (Bachas, et al., 2020; Bartik et
by sales of distributors after October 2004. We take a simple average of the monthly values to aggregate it into quarterly and annual series.

We use **GDP** compiled from the income perspective for our analysis. Total income of an administrative region consists of employee remuneration (salary plus social contribution), operation surplus, mixed income, and taxes (net of subsidies). We obtained country, region, and FU level GDP/income data from the country’s System of Regional Accounts (SCR) 2020 that is produced by the Brazilian Institute of Geography and Statistics (IBGE) in collaboration with the State Statistical Offices, State Government Departments, and the Superintendence of the Manaus Free Zone. The SCR, revised in 2015, is compatible with international methodologies of the System of National Accounts 2008 (IBGE 2020). We collected three income series, _i.e._ , total income, employee remuneration, and other income (operation surplus plus mixed income). The data is available at annual frequency from 2010 to 2020.

Estimates of **greenhouse gas (GHG) emissions** are focused on those that arise from fuel combustion for road transportation covering all vehicles ( _e.g._ , cars, trucks, buses, and motorcycles) that respond to prices of automobile fuels. During combustion, carbon (C) stored in the fuel is oxidized and released as carbon dioxide (CO2) and, to the extent of incomplete combustion, methane (CH4), carbon monoxide (CO) and non-methane volatile organic compounds (NMVOCs). In addition, minor emissions from nitrogen (N2) oxidation result in nitrogen oxides (NOx) and/or nitrous oxide (N2O) depending on process temperature (de Azevedo, T., Costa Junior, C., Brandão Junior, A. et al., 2018).

We obtained emission data from the latest version of System for Estimating Greenhouse Gas Emissions (SEEG version 10, 2022). An initiative of Climate Observatory, SEEG
|**Variable**|**Obs**|**Mean**|**Std. Dev.**|**Min**|**Max**|
|---|---|---|---|---|---|
|lypc|121|8.05|1.17|5.25|10.03|
|rule|162|-0.04|0.92|-2.17|1.91|
|lpats_pop|127|-11.79|3.14|-17.98|-4.66|
|lmort|76|4.70|1.22|2.15|7.99|
|lip|116|0.83|0.62|-2.30|1.46|
|eurfrac|172|0.20|0.36|0|1.00|
|oilprueba2|183|0.20|0.40|0|1|
|cen_latabs|173|25.69|17.12|0.42|67.47|
|landlock|191|0.20|0.40|0|1|
|ssa|201|0.25|0.43|0|1|
|lcts|150|2.92|0.75|0.83|4.44|
|malfal94|149|0.29|0.41|0|1|

# **Description**

lypc Log (Income per capita in 2000, 1985 U.S.$ PPP) Source: Calderón, Fajnzylber, and Loayza (2005) rule Rule of Law index. Source: Kaufmann, Kraay, and Zoido-Lobatón (2002) lpats_pop Log (patents granted in the U.S. and Europe/ total population). Sources: USPTO, EPO, and World Bank.
# **9. References**

‐ ‐ Abadie A., Athey S, Imbens G.W., Wooldridge J.M., 2020. Sampling Based versus Design Based Uncertainty in Regression Analysis. Econometrica. 88(1):265–96.

Abadie, A., Imbens, G., 2006. Large Sample Properties of Matching Estimators for Average Treatment Effects. Econometrica 74(1):235-267.

<mark>Akresh, R. (2009). Flexibility of household structure child fostering decisions in Burkina Faso. Journal of Human Resources, 44(4), 976-997.</mark> Alix-Garcia, J., Walker, S., Bartlett, A., Onder, H., Sanghi, A., 2018. Do refugee camps help or hurt hosts? The case of Kakuma, Kenya. J Dev Econ. 130:66–83.

<mark>Altindag, O., O'Connell, S.D., Sasmaz, A., Balcioglu, Z., Cadoni, P., Jerneck, M. and Kunze Foong, A., 2019. Targeting humanitarian aid using administrative data: model design and validation.</mark> _<mark>Available at SSRN 3444974</mark>_ <mark>.</mark> Anderson, M.L., 2008. Multiple inference and gender differences in the effects of early intervention: A reevaluation of the Abecedarian, Perry Preschool, and Early Training Projects. J Am Stat Assoc. 103(484):1481–95.

Angrist, J.D., Imbens, G.W., Rubin, D.B., 1996. Identification of Causal Effects Using Instrumental Variables. J Am Stat Assoc 1;91(434):444–55.

<mark>Aronow, P.M., Samii, C. and Wang, Y., 2019, July. Design-based inference for spatial experiments with interference.</
is known as conditional probability. It is called so because it defines the effect of having one characteristic instead of another (for example, being a woman) upon a particular employment transition (for example, finding a job), under the condition that all the other characteristics (age, education, and so forth) remain the same. Conditional probabilities are of analytical interest because they indicate whether certain traits involve propensities to lose or gain employment. This kind of probability is computed through an econometric technique using the same panel data described in the previous section.<sup>7</sup> Estimates for the conditional probabilities of becoming jobless before, during the recession and the recovery are shown in table 3.7. The table shows evidence about five main messages. First, males always had a lower probability of losing a job, rather than keeping a job, than females, but this advantage became larger during the recovery. Males were 2.9 percent less likely to become jobless, rather than keeping a job, than observationally equivalent females during the recovery, compared with 1.3 percent during the recession or 1.55 before the recession.

7 The conditional probabilities presented in this section were estimated through a multinomial logit model. The model estimated the transition probabilities of four possible states between two periods: staying in a job, staying jobless, finding a job, and losing a job. The base category is keeping a job; thus all the interpretations have to be made with respect to this category. The estimation made use of rotating panels from ENOE for the second quarters of 2008-2009 and 2009-2010, for individuals aged 18 to 65. Further details about the estimation procedures are available from the authors upon request.

23
participant his name and caste before randomly assigning him to a treatment and sending him to a large classroom, where participants were entertained for up to an hour while waiting for all the cars bringing participants from other villages to arrive. The focus of the experiment was on the effect of three conditions that varied the publicness and salience of caste identity in the session, which was always led by a high-caste young woman experimenter: _Caste Not Revealed_ (the control condition). A session was composed of 3 H and 3 L. No personal information about the participants was revealed.

_Revealed Mixed_ ( _i.e_ . caste revealed in a mixed-caste session). The composition of a session was the same as in the preceding condition, but now the experimenter began a session by saying that she would like to confirm some information with each participant, who should nod if it is correct. Then the experimenter turned to each participant and stated his name, village name, father’s name, grandfather’s name, and caste.

_Revealed Segregated_ ( _i.e._ caste revealed in a segregated session) _._ This was the same as the preceding condition except that a session was composed of either 6 H or 6 L.

The priming mechanism reflects a way in which caste identity is actually made salient in classroom settings. This increases the external validity of our results. Although an individual’s caste is widely known in a village, publicly referring to a child’s caste is not uncommon in rural schools. There is anecdotal evidence of teachers telling low-caste children to not drink from the tap at the school, lest it pollute the water for others. While implementing this study, we came across some such instances. Caste is commonly recorded in school enrollment books, often using different colors for high and low castes, to identify caste-targeted entitlements such as stipends and uniforms provided by state governments. In villages, people are frequently called by their caste names. Following the common usage in this area and also the way
# _3.1 Experimental design_

In order to evaluate the impacts of Jeevika, the rollout of the project was randomized across 180 panchayats, randomly selected from within 16 blocks in seven districts where Jeevika was planning to scale up. In each of the study panchayats, one or two villages were then randomly selected for data collection.

Since the intervention was targeted to poorer households, within each of the study villages, hamlets in which the majority of the population belonged to a scheduled caste or scheduled tribe were identified. Households were then randomly selected from these hamlets to be interviewed. A baseline survey was administered during July to October of 2011 to 8,988 households across 333 villages in 179 panchayats.<sup>6</sup> Following the baseline survey, panchayats were randomly assigned to an early rollout group or a late rollout group, after stratifying the sample on administrative block and the panchayat-level mean of outstanding high cost (monthly interest rate of 4% or higher) debt held by households at baseline. The project began in the early rollout panchayats between January and April 2012, and the follow-up survey was completed between July and September 2014. Implementation in late rollout areas began after the 2014 round of data collection. Baseline and follow-up surveys included detailed questions on debt, asset holdings, consumption expenditures, livelihood activities, and women’s mobility, role in household decisions, and aspirations. In addition, in each village, a focus group discussion was conducted, through which data were collected on village-level attributes such as local sources of credit, interest rates from each source, local wage rates, and the presence of or distance to markets and other institutions and amenities.

# _3.2 Analysis_

The SHG intervention is expected to lead to a series of potential impacts, which we classify as direct, indirect and downstream. One or more direct impacts (increased SHG membership; increased utilization of credit though SHGs) is a necessary but insufficient condition for the intervention to lead to indirect effects on informal credit markets. Changes
patterns of cross-country exchange rate co-movements. Section IV presents the argument that the _de facto_ US dollar-pegged exchange rate regimes were indeed one of the factors behind the crisis and develops a scope for future exchange rate arrangements in emerging East Asia. It proposes a "soft" currency basket system where the US dollar, the Japanese yen and the euro play more balanced roles than in the pre-crisis period. Section V summarizes the paper and offers an agenda for future research.

# 11. **EXCHANGE RATE ARRANGEMENTS OF THE LDC'S IN THE 1990S**

This section reviews the exchange rate arrangements of almost all developing countries in the world for the 1990s and obtains some stylized facts and general conclusions.' It focuses particularly on the role played by the world's major currencies, such as the US dollar, the Deutsche mark, and the Japanese yen, as international anchor currencies for other countries' exchange rate stabilization.

# **1. "Reported" Exchange Rate Arrangements**

The Intemational Monetary Fund (IMF) regularly publishes exchange rate arrangements reported by its member countries according to its own classification scheme. Table 1 presents the overview of the developing world's exchange rate arrangements reported by LDC members, for the period December 1980 through September 1998.2 Exchange rate arrangements are classified broadly into three categories: (a) a fixed rate arrangement; (b) limited exchange rate flexibility; and (c) a more flexible rate arrangement.<sup>3</sup>

> ' See International Monetary Fund [1997] for discussions of exchange rate arrangements in developing countries. 2 This table is compiled from the IMF's International Financial Statistics (various issues) by removing industrialized countries.

Beginning January 1999, the IMF introduced a new classification of categories that include: exchange rate 3
# **5 Counterfactuals**

To evaluate the effect of international integration and the income distribution on sustained poverty reduction, we simulate several counterfactual economies and compare them to the status quo (with current levels of international integration and equality). The first is a counterfactual closed economy without international integration, in which _λ_ 2 = _λ_ 3 = 0. This could be understood as the development policy doomsday scenario, in which comparative advantage from trade becomes irrelevant for sustained poverty reduction. The second is a counterfactual maximum equality economy, in which the share of the population in the middle class is calculated using Equation 10 and the current national GDP per capita, but a Gini coefficient of 0.20, the value for Slovakia in 1992, the lowest in the sample. This could be understood as a scenario where national income stays the same, but government redistributes income to about the extent achieved in the Czechoslovak Socialist Republic, which dissolved in 1989. The third is a fully integrated counterfactual, in which the relative population and income of the integrated market are equal to the relative population and income of the whole world. This could be understood as a maximal trade liberalization scenario in which the country signs deep trade agreements establishing and protecting economic integration rights with every country. Table S2 in the Online Supplement reports estimates of the status quo market size for each country period in our data set, as well as each counterfactual market size. All these scenarios should be thought of as polar cases that serve the purpose of helping us quantify the contributions of equality and international market size towards poverty reduction, rather than realistic policies on the table. We note however that in principle, our framework with the detailed information on specific provisions of trade agreements it provides, could be used to also assess the effects of specific liberalization measures (e.g., signing specific provisions of trade agreements with particular countries).

We summarize these results in two figures. Figure 5 shows the estimated status quo market size, calculated as _Mitλ_<sup>
on individual expenditures 0.4

> VAT on alcohol and tobacco 0.5

> VAT on motor vehicles 0.6

> SCT on energy products 0.7

> VAT on energy products 0.7

> SCT on alcohol and tobacco 2.1

> All indirect taxes 6.2 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 Increase in poverty rate, percentage points

Source: Own estimates based on Turkey 2016 HBS. Note: Marginal contribution to poverty is the difference between the poverty rate without the particular fiscal intervention and the poverty rate of all income components together.

32
<!-- Start of picture text --> 1990 2000 2010 2020<br>year<br>GFM - treat GFM - no treat<br>25<br>20<br>15<br>10<br><!-- End of picture text --> Source: Authors’ using data from ICTD revenue database

# **3. Empirical analysis**

# **3.1. Empirical model specification**

Following the literature on tax revenue mobilization (Gnangnon and Brun, 2017; Gupta, 2007; Leuthold, 1991; Yogo and Njib, 2018), we specify a panel fixed effect model to estimate the impact of the Global Forum membership on tax revenue collection performance. Algebraically, the empirical model is specified as follows:

# Taxit =  δGFMit + βXit + θi + μt + εit **(1)**

where Taxit represents the tax revenue in proportion of GDP for country i in year t. Data on the outcome variable (tax revenue) are extracted from the government revenue database (Prichard et al, 2014) developed by the International Center for Taxation and Development (ICTD).

GFMit is a dummy variable which takes the value 1 in country i in year t if country i is a member of the Global Forum for the exchange of information for tax purposes and 0 otherwise.

Xit is the set of standard determinants of tax revenue including political, institutional, and economic variables.

θi is the country fixed effects; μt are time dummies, εit and the usual independent and identically distributed error term.

7
- that the predictions match well with those from costlier traditional surveys of the population.<sup>97</sup> Similar approaches have been used to produce granular maps of crop yields and malnutrition.<sup>98</sup>

- **Improved targeting of public health interventions and natural disaster relief.** Understanding who is most affected by natural disasters and predicting relocation patterns is key to effective humanitarian relief operations, public health interventions, and long‐term reconstruction efforts. Mobile phone data have been used to reveal who is most affected by natural disasters,<sup>99</sup> where people relocate in response to a disaster,<sup>100</sup> and the implications of relocation for the spread of disease.<sup>101</sup>

- **Natural Language Processing methods: text as data.** Traditional qualitative surveys require in‐ depth analysis of interviews coupled with participant observation in small groups.  These have recently been supplemented with the analysis of narratives from much larger samples by applying Natural Language Processing methods to existing texts. Such methods have been used to analyze Wikipedia pages to predict levels of economic development<sup>102</sup> , and to study discourse within village meetings in rural India.<sup>103</sup>

# **Challenges in harnessing digital data for development**

Governments have been at the center of traditional data collection efforts. In contrast, digital data is typically collected by firms, which focus on its commercial value rather than its potential social value. Moreover, data are “non‐rival”, meaning that a person’s call data records, location history, internet usage and medical records can be used by many firms (and governments) at the same time and for different purposes. Recent theoretical research shows that this may lead firms to respect data privacy less than is socially desirable, and they may also have incentives to inefficiently hoard data.<sup>104</