rafmacalaba/datause-encoder-data huggingface dataset:
9 the poorest region, and least .ikely to be<sup>found in the south. Female-headed households in</sup> the more developed southeastern and southern<sup>regions are also less likely to have children.</sup> Nonetheless, given the tremendous regional<sup>differences in Brazil in income, economic</sup> structure, and culture, it is striking that the<sup>differences in prevalence between regions are not</sup> stronger.

Only one-third of urban female-headed households<sup>correspond to the Moynihan</sup> stereotype of a single mother and her<sup>children.1I Over one half of female-headed</sup> households have no minors living in the household.<sup>Of those without minors, 40 percent are</sup> single, while 44 percent have an adult child<sup>living in the household. Where there are minor</sup> children in the h, ,sehold, another adult is also<sup>iikely to be present. On the whole, female-</sup> headed households tend to have slightly<sup>fewer adults than the average for Brazil, and the</sup> adults are more likely to be women. Among<sup>all female-headed households, the largest group</sup> comprises single women. Divorce' is the most<sup>usual route to female-headedness for those</sup> with minors in their household (39 percent), but<sup>30 percent of female heads with under-age</sup> children never married, and 28 percent are widowed<sup>(perhaps providing for their</sup> grandchildren). The heads of the Moynihan-type<sup>households are among the youngest in the</sup> group, and the most likely to have been divorced.

The economic characteristics of female-headed<sup>households are different from</sup><sup>**the**</sup> average in Brazil on a number of dimensions<sup>(Table 5). Although the per capita income of</sup> urban female-headed households is 89 percent<sup>of that of all urban households, the average</sup> income of female heads is 50 percent of the average<sup>in urban Brazil. This discrepancy</sup> " Moynihan (1965) was one of **the** first to bring to<sup>national attention in the Un.ted States the problems of</sup> **poor** single mothers with children among African-American households, sparking an intense debate regarding public policy **ard** female headship. Among other<sup>things, Moynihan was accused of racism and of stereotyping</sup> women in his pioneering work (see Wilson and Neckerman,<sup>1986, for a discussion). Nonetheless, his work is</sup> credited with raising the issue of household structure<sup>and poverty,</sup><sup>**and**is still widely discussed in the United</sup> States today.

**12** In the Brazilian **survey,** the classification "divorced'<sup>includes couples who have separated but have not</sup> legally terminated **the** marriage.
**Labor Market Impacts and Responses: The Economic Consequences of a Marine Environmental Disaster**<sup>_∗_</sup>

Trung Hoang<sup>_†_</sup> Duong Trung Le<sup>_‡_</sup> Ha Nguyen<sup>_§_</sup> Nguyen Dinh Tuan Vuong<sup>_¶_</sup>

**Keywords** : environmental disaster, coping mechanisms, satellite detection, fisheries

**JEL Classification** : J30, O13, Q52

> _∗_ We would like to thank Rabah Arezki, Ritam Chaurey, Ian Coxhead, Ousmane Dione, David Flath, Seema Jayachandran, Solomon Polachek, Anh Pham, David Slichter, Susan Wolcott, participants at the NEUDC 2018 (Cornell University) and the Development Workshop at the University of Wisconsin-Madison for helpful comments. All remaining errors are our own.

> _†_ Email: hoangxuantrung3012@gmail.com. Vietnam Academy of Social Sciences.

> _‡_ Email: dle1@binghamton.edu. Binghamton University - SUNY.

> _§_ Email: hanguyen@worldbank.org. Office of the Chief Economist for the Middle East and North Africa. The World Bank.

> _¶_ Email: nguyen.vuong@wisc.edu. University of Wisconsin - Madison.
existing literature and d) jointly testing whether the institutional framework, investor protection and trade openness play a role in fostering the impact of financial openness on domestic financial sector development.

Our main findings suggest that domestic financial markets are enhanced by the higher integration of countries into world capital markets. In general, rising financial openness leads to deeper local capital markets by: (i) enlarging the size and activity of financial intermediaries (that is, generating an expansion in private credit, financial deposits and bank assets), (ii) improving the efficiency in the banking system, and (iii) contributing to the deepening of local stock market and private bond markets. These effects are economically significant in countries with moderate to high levels of institutional quality, investor protection and trade openness.

This paper consists of the following sections: Section 2 describes the data and methodology. Section 3 discusses our regression analysis and evaluates the role of the structure of external assets and liabilities in driving the impact of financial openness on domestic financial development. Section 4 discusses whether these different effects are driven by cross-country or cross-region differences in the level of institutional quality, the degree of investor protection, and the extent of trade openness. Finally, section 5 concludes and suggests further avenues for future research.

# **2. Data and Methodology**

This section describes the definition and sources of the data used for our empirical assessment and an outline of the econometric estimation technique used.

## **2.1 The Data**

We have collected annual data on financial depth, financial openness and other determinants of domestic financial depth (income per capita, inflation, openness, institutions, etc.) for 1974-2007 (our full sample period). The list of countries classified by region and the level of income is presented in Table A.1.<sup>4</sup> Our dependent variable aims to capture the level of _domestic financial development_ . Given the multiplicity of aspects surrounding the concept of domestic financial development we use a wide array of indicators developed by Beck, Demirgüç-Kunt and Levine (2000). We update

> 4 We have ignored the Bretton Woods period to focus on the recent period of increasing integration to the world markets of goods and assets.

6
# **3.  The Political Geography of Methane Monitoring**

# **3.1 The Spatial Distribution of Methane Emissions**

Methane emissions come primarily from fossil fuel extraction and processing, livestock grazing, irrigated rice production and waste disposal. Table 4 shows that the spatial distribution of methane emissions sites is hugely skewed. Of 6.5 million cells in the EDGAR 10 km global raster, only 142 (0.002% of total cells) account for 10% of global methane emissions and 21,057 (0.325%) account for 50%.<sup>7</sup>

**Table 4:  Spatial clustering of global methane emissions**

|EDGAR<br>Decile|Cells|Cum.<br>Cells|Cum.<br>%|
|---|---|---|---|
|1|142|142|0.002|
|2|578|720|0.011|
|3|1,775|2,495|0.039|
|4|5,817|8,312|0.128|
|5|12,745|21,057|0.325|
|6|22,364|43,421|0.670|
|7|37,919|81,340|1.255|
|8|64,334|145,674|2.248|
|9|124,529|270,203|4.170|
|10|6,209,797|6,480,000|100.000|

Figure 4 displays the global distribution of the 21,057 cells that account for 50% of methane emissions. The map reveals widely-scattered cell clusters in all global regions except South and East Asia, which also have very large clusters in some subregions. Figure 4 motivates a cluster-concentrated strategy, because the cost-effectiveness of emissions-reducing interventions rises with spatial clustering.<sup>8</sup> Table 4 poses a corollary challenge for the global community: The Global Methane Pledge is only likely to succeed if significant reductions can be achieved in the spatial clusters that account for 50% of global methane emissions. Beyond those clusters, methane emissions sites become progressively more scattered and interventions more costly.

# **3.2 Local Accountability**

This paper highlights potential benefits from combining “top down” satellite monitoring of emissions changes with “bottom up” estimates of emissions magnitudes. However, these benefits can only be realized by effectively-administered interventions. Effective administration will in turn require the informed participation of governing institutions at the appropriate geographic scale. In this case the best match is provided by the second-level administrative units whose territories include important methane emissions sites. Accordingly, this paper develops and illustrates a strategy for satellite

> 7 We include the full global grid in these calculations, because many large methane sources are offshore oil and gas extraction sites.

> 8 Monitoring, regulatory enforcement and abatement investment all tend to be lower-cost for activities that are concentrated in relatively small areas.

10
**Figure 4: Income Distribution of Participants**

<!-- Start of picture text --> 10<br>8<br>8 7<br>6<br>6<br>4<br>4<br>2 2 2<br>2 1<br>0<br>0<br>In‐house Public DMS Commercial<br>LIC / LMIC UMIC HIC<br><!-- End of picture text --> Source: World Bank Survey on Debt Management Systems Figure 5 below shows the distribution of system ability to process different debt instruments. All systems seem to have no issues capturing the most common debts instruments, such as bills, bonds and floaters. Fees and project-finance loans also receive high marks across all three groups of systems. Interest and cross-currency swaps received the lowest scores on average, but so did inflation-linked instruments, guarantees, on-lent debt, and receivables for commercial software packages (public DMS and commercial).

Looking closer at the survey details provides possible explanations for these results. While the more common debt instruments represent ordinary course of business for most countries, other instruments may not be used and/or are only dealt with periodically. For instance, some developed countries use swap instruments to hedge risks in their respective debt portfolios. Most of these countries indicated that they successfully handle interest rate and cross currency swaps regardless of the system they use. At the same time, other countries that do not use swaps as instruments scored low on coverage of these instruments in their respective DMS. These results are not surprising and mainly due to the absence of these instruments from some DMO portfolios. The more complex transactions such as the derivatives are only undertaken and captured by developed countries DMS (e.g. Denmark, New Zealand). Another interesting observation is that countries using an in-house system have a better general coverage of the instruments they use. Possible reasons could be that the off-the-shelf systems do not fully accommodate their scope of needs and/or they already possess the necessary level of sophistication and support in-house.

23
Other processes examined, such as registering a patent, developing new products, or attracting new investors, do not appear to be changed significantly. These could be more difficult to detect since they are more heterogeneous across enterprises, or require a longer time to change than is observable in the treatment period. To measure human resource management practices, we created an index using Principle Component Analysis (PCA) based on the six questions listed in Appendix 1<sup>18</sup> . We are not able to reject the null hypothesis of no effect on this index (-0.062, s.e. = 0.152). In summary, since the content of the consulting was tailored to each firm’s needs it is perhaps not surprising that we do not see improvements in most individual processes, nor the collection on average.

# **4.3 Entrepreneurial Spirit**

We constructed an entrepreneurial spirit index, developed in collaboration with IPPC. This index is based on the answers to the eight questions listed in Appendix 1, which intend to capture entrepreneurial attitudes of the principal decision maker, and is generated using PCA, and then a standardized index using the Kling et al. (2007) method. Thus the indices are a combined measure of answers to a set of questions on the enterprise owner’s beliefs about their ability to control the success of their business (or whether they are merely subject to external forces outside of their control) and on the owner’s drive for success.

Table 6 reports the results. We find a positive and statistically significant impact using the PCA method (0.237, s.e. = 0.140) and positive but not statistically significant impact using the Kling et al. method (0.130 standard deviation increase, s.e. = 0.103). The increase in this index might reflect the fact that enterprise owners set new goals as part of the program and that consultants helped to provide motivation and strategy for how to achieve these goals. In addition, enterprise owners’ increased confidence in their ability to control the success of their business could be driven by having better command of management tools such as marketing and bookkeeping.

We cannot distinguish whether the training had a direct effect on entrepreneurial spirit (e.g., enterprise owners set new goals as part of the program and that consultants helped to provide motivation and strategy for how to achieve these goals), or whether the improvements in the business that led to higher productivity then improved the spirit of the entrepreneurs. Two of the questions used

> 18 All PCA indices in this paper were created in Stata using the “pca” command. This command computes the leading eigenvectors from the eigen decomposition of the covariance matrix of the variables used to create the index.  We choose the first eigenvector as our PCA index. In other words, the PCA index is a weighted linear combination of the underlying variables, where the weights are optimal in the sense that they give the index the largest possible variance.

15
The literature on non-fundamental contagion also has an empirical branch. Kaminsky and Schmukler **(1999)** find that spillover effects unrelated to market fundamentals are quite common, and spread quickly across countries within a region. Valdes **(1998)** examines the degree to which comovement of Brady-bond prices is unexplained **by** fundamentals. Interestingly, contagion in his paper is symmetric, applying both on the downside during crises and on the upside during periods of rapid capital inflow. **A** different line of empirical work on non-fundamental contagion examines whether crises are spread **by** particular investor groups. For example, Choe, Kho, and Stulz **(1998)** use transaction data in the Korean equity market to examine whether foreign investors destabilize prices. They find evidence of herding **by** foreign investors before Korea's economic crisis in late **1997,** but these effects disappear during the peak of the crisis, and there is no evidence of destabilization. Since their data include only transactions on the Korean Stock Exchange, these authors cannot examine the transmission of crisis across countries.

# **11.4. Measuring Contagion Trading**

Our approach to testing for contagion is different from the literature reviewed above. Data on individual portfolios allow us to address contagion in a new way-from the trading-strategy perspective. We will use the term contagion trading to mean the systematic selling (buying) of stocks in one country when the stock market falls (rises) in another." To do this we introduce a new measure-a contagion trading measure. Our contagion trading measure is based on the methodology outlined above for measuring momentum trading. Like the momentum measures, we present contagion trading measures at three different levels: whole-fund contagion trading **(C),** manager-only contagion trading

> 11Notice that this definition does not take account of the fundamental-versus-non-fundamental distinction introduced above. The appendix introduces a regression-based approach that allows us to test for contagion with controls for various fundamental factors.

12
the amount of housework reported – are not the result of survey respondents becoming better at reporting their time use or being more likely to report housework.

In columns 3 – 7, I find evidence to suggest that relative to the mothers of those who are ineligible to receive the stipend program, the mothers of those who are eligible experience an increase in the amount of time they spend on housework. Columns 3 and 4 contain no controls and report estimates from pooled OLS and fixed effects regressions respectively. In columns 5 – 7, I introduce three sets of sequentially augmented controls– basic, extended and full. The basic specification controls for differences in household size and composition with a set of indicator variables for the number and gender of household members of various ages. I include separate controls for the number of men, the number of women, the number of teen boys (ages 13 to 17), teen girls, preteen boys (ages 5 to 12) and preteen girls as well as the number of male and female infants (those children under the age of 5).

The extended set of controls adds to the household size and composition variables a series of indicator variables that measure the current and relative wealth of the respondents. I include an index of household wealth – which is the score of the first principal component of an index derived from whether or not a household owns items from a list of assets.<sup>16</sup> The LEAPS survey asks households to rate their wealth relative to five years ago as well as their harvest relative to one year ago. Responses to both these questions were categorical and as such indicator variables were included to capture their inherent non-linearity. The full set of controls adds a set of indicators for mother and father’s age as well as indicator variables for quarter of interview. If some seasonal differences confound the intent to treat effects of the program, controlling for quarter of interview addresses this issue.

> 16 Households were asked if they owned any of the following: beds, tables, chairs, fans, sewing machines, air coolers, air conditioners, refrigerators, radio cassette players, TVs, VCRs, and watches. Reponses were combined using principal components analysis. The first principal component is a standard normal variable.

17
we incorporate income and consumption data for 12 Nigerian households based on both location in Nigeria (North, South, etc.) and rural versus urban. We can, therefore, examine the impact of the removal of fuel subsidies on both the Nigerian economy, the government’s fiscal balance and trading patterns, as well as on the incomes and consumption patterns of the 12 different households. Given the recent social unrest in Nigeria as a result of this policy change, we also examine the extent government can allay the detrimental effects of the removal of the subsidy on the poor, by combining the removal of the fuel subsidies with other policies aimed at assisting the poor and or domestic producers of petroleum products.

# **2 Methodology**

In this study, we use a global applied general equilibrium (AGE) model to examine the impact on the Nigerian economy of removing the subsidy on imported petroleum products. Such models are firmly rooted in microeconomic theory of utility and profit maximization as well as product and factor markets being in equilibrium. The parameterization typically is such, that medium to long term adjustments to exogenous shocks (such as a subsidy removal) can be depicted, whereas such models are less suitable to depict year to year adjustment processes. The MyGTAP modeling framework, developed by Walmsley and Minor (2013), offers a platform for the analysis of domestic policies within a global framework, by allowing for the inclusion of detailed data on Nigerian households to be incorporated into the GTAP database (Narayanan et al., 2012). In this section we review the MyGTAP modeling framework and the changes made to the GTAP database.

## **2.1 The MyGTAP Model**

The MyGTAP model is an extension of the standard GTAP model (Hertel, 1997). The standard GTAP model employs simple, but well recognized assumptions about product technology, competition, and consumer and government behavior. For example, production technology exhibits constant returns to scale and substitution between primary endowment factors, such as land, labor, and capital, with intermediate inputs used in fixed proportions. Imports are modeled as differentiated products between the domestic and imported goods. Imported goods are differentiated by country of origin as specified by the Armington assumption. The government consumes goods and services in fixed proportions. Consumer demand for goods and services incorporate both income and substitution effects, allowing for changes to the consumption bundle due to changes to prices and real income. The standard GTAP model assumes one “regional” representative household, which gathers all factor income and taxes that are then distributed to savings and government and private consumptions.

7
# **Figure S4: Receiver Operating Characteristic (ROC) Curves**

<!-- Start of picture text --> Random Forest Logistic, stepwise BIC<br>Credit Bureau<br>0.0 0.2 0.4 0.6 0.8 1.0 0.0 0.2 0.4 0.6 0.8 1.0<br>False positive rate False positive rate<br>CDR<br>0.0 0.2 0.4 0.6 0.8 1.0 0.0 0.2 0.4 0.6 0.8 1.0<br>False positive rate False positive rate<br>1.0 1.0<br>0.8 0.8<br>0.6 0.6<br>True positive rate 0.4 True positive rate 0.4<br>0.2 0.2<br>0.0 0.0<br>1.0 1.0<br>0.8 0.8<br>0.6 0.6<br>True positive rate 0.4 True positive rate 0.4<br>0.2 0.2<br>0.0 0.0<br><!-- End of picture text --> <mark>Random Forest Weekly Ensemble OLS FE, stepwise BIC CDR</mark> <!-- Start of picture text --> 0.0 0.2 0.4 0.6 0.8 1.0 0.0 0.2 0.4 0.6 0.8 1.0<br>False positive rate False positive rate<br>1.0 1.0<br>0.8 0.8<br>0.6 0.6<br>True positive rate 0.4 True positive rate 0.4<br>0.2 0.2<br>0.0 0.0<br><!-- End of picture text --> _<mark>Note:</mark>_ <mark>C</mark> DR represents Call Detail Record, and BIC Bayesian Information Criterion. <mark>Cells computed based on out of sample predictions resulting from 5 fold cross validation. Source: authors’ analysis from telecom data.</mark> 5