rafmacalaba/data-use-mentions-extended huggingface dataset:
consumption will translate into higher carbon emissions than would take place if the grid was cleaner.

In Figure 1, we take the World Development Indicators database for the year 2018 and graph the log of carbon dioxide emissions per-capita with respect to the log of GDP per-capita. For the 181 nations, the income elasticity estimate is 1.26. The figure’s dots are weighted by national population and India and China stand out for their contribution to emissions. In this cross-sectional figure, higher income nations have a less positively sloped elasticity than middle-income nations. In Figure 2 for 174 nations, we graph the percentage change in percapita carbon dioxide emissions from the year 2000 to 2018 with respect to the log of national per-capita GDP in 2000. The slope is -.34 in this case. The poorer nations that are urbanizing and industrializing have a larger growth in carbon emissions than richer nations. Together, these two figures highlight the challenge that lower-middle-income nations pose for creating a low carbon emissions coalition. As these nations grow richer, their carbon emissions increase.

One possible offsetting force is the recognition of the co-benefits of reducing reliance on coal fired power. <mark>Barrows, Garg and Jha (2019) quantify the air pollution externality associated with coal burning in India. Cesur, Tekin and Ulker (2017, 2018) use data from Turkey to document the local air pollution gains as the nation increases its reliance on natural gas for generating power and closed coal fired power plants. In developing nations, the value of a statistical life increases as economic development takes place (Costa and Kahn 2004). This means that the Pigouvian damage to India from air pollution created by its own coal fired power plants increases as the nation grows richer and more people live in a vicinity of the power plants. At least up until this point, this local benefit of substituting away from coal has not been a sufficient incentive.</mark>

# **Electric Vehicles Adoption in California**

In the developing world, people are purchasing
affecting household well-being. For the elasticity of demand, we used -0.15 in this analysis,<sup>3</sup> which influences the estimated changes in quantity of electricity consumed (and in the next section, the fiscal effect on government revenues and spending).

As discussed, Iranians spend around 2.1 percent of their budgets on gasoline at pre-reform prices, with the middle of the distribution spending the largest share. On average, people will lose about 2.8 percent of their expenditure due to higher gasoline prices (Figure 6). Consistent with this, the increase in gasoline prices will affect the middle of the distribution. The poor will also experience a non-negligible loss in expenditure. The poorest 10 percent will lose about 2.0 percent of expenditure and the second poorest decile about 2.3 percent of expenditure.

Figure 6. The direct impact on well-being from increase in gasoline prices by deciles, % of total expenditure <!-- Start of picture text --> 0.0<br>-0.5<br>-1.0<br>-1.5<br>-2.0<br>-2.5<br>-3.0<br>-3.5<br>%<br><!-- End of picture text --> Source: Authors’ calculation using forecasted HEIS 2018/2019.

In terms of poverty and inequality, Table 5 shows pre-reform and post-reform estimates. Without mitigation, poverty would be expected to increase by 1 percentage point due to the direct impact of higher gasoline prices. Inequality, measured by the Gini Index, is also expected to increase modestly by 0.1 point.

Table 5. The direct impact on poverty and inequality after increase in gasoline prices

||Pre-Ref|Post-Ref|Change|
|---|---|---|---|
|Welfare (per capita), (IRR)
Figure 5: Correlation between household consumption and the share of land allocated to coffee <!-- Start of picture text --> 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1<br>Share of land allocated to coffee in 2011 Share of land allocated to coffee in 2011<br>95% CI 2011 2013 95% CI 2011 2015<br>.6 .6<br>.4 .4<br>.2 .2<br>0 0<br>-.2 -.2<br>Log food consumption (adult equivalent) Log food consumption (adult equivalent)<br>-.4 -.4<br><!-- End of picture text --> Note: This figure shows the correlation between log household adult equivalent consumption and the share of land allocated to coffee in 2011. The effect of rainfall and price inflation (year fixed effects) are removed before plotting. The figure shows that in 2011, when coffee price boomed, there is a significant positive correlation between household consumption and the fraction of household land allocated to coffee. This fact is totally reversed in the years 2013 and 2015, when international coffee price is about 50% less than its 2011 level (see figure 1).

expenditure is stronger than the effect on non-food expenditure.

The coefficient estimates in panel A can be interpreted as percentage change in consumption following a 1% change in coffee price for a household that allocates all its farm land to coffee (for the most exposed household). In equation 3, the effect of a percentage change in coffee price is given by _β_ 1 _×_ LandShareCoffee _i_ , which varies across households depending on the fraction of farmland allocated to coffee. For a household that allocates all its farmland to coffee, LandShareCoffee _i_ = 1, the effect of a percentage change in coffee price is given by _β_ 1. For a household that does not produce any
----------`|

``` Notes: This table presents four regressions, where each column reports the findings from an OLS regression. The dependent variables, measured in 2011, are: Bank Development equals claims on the private sector by deposit money banks as a share of GDP; Interest Margin equals net interest income divided by total bank assets; Overhead Costs equals total bank overhead costs as a share of total bank assets; and, Nonperforming Loans equals officially reported nonperforming loans as a share of total banks assets. The regulatory indexes are measured in 2011: Capital Regulatory Index measures the extent and stringency of regulatory requirements; Private Monitoring Index measures the degree to which regulatory policies encourage and facilitate private sector monitoring of banks; Official Supervisory Power Index measures the extent to which official supervisory agencies have the authority to take specific actions to prevent and correct problems; Entry Restrictions Index measures the number of specific legal requirements for obtaining a banking license; and Restrictions on Activities Index measures regulatory restriction on the degree to which banks can engage in securities, insurance, and real estate activities plus restrictions on banks owning and controlling nonfinancial firms. Though unreported, the regressions also control for the legal origin of each country by including three dummy variables for Common, French civil, and German civil law countries, as well as a constant term. Heteroskedasticity-consistent standard errors are in parentheses under the estimated coefficients. To designate statistically significant benchmarks, *** indicates significance at the 0.01 level, ** at the 0.05 level, and * at the 0.10 level.
```
change specific measures simply because they happen to be included in an aggregate indicator that they wish to influence. Of course, we do not argue that _onl_ y perceptions data are relevant for measuring governance. Rather, as we discuss in more detail in Section 2.2 below, our point is simply that this type of data brings valuable insights that can be used in conjunction with other types of information to measure governance across countries and over time.

The individual indicators from the 35 data sources are assigned to the six dimensions of governance and are combined into six aggregate indicators using a statistical methodology known as an Unobserved Components Model (UCM). The statistical methodology converts the data sources into common units and constructs a weighted average that combines the information in each of the data sources. The methodology also produces margins of error that capture the unavoidable imprecision involved with measuring governance across countries. This imprecision is not unique to the WGI, but rather is likely to be pervasive in any efforts to measure governance and institutional quality across countries. A key attribute of the WGI is that these margins of error are explicitly reported alongside the estimates of governance and should be considered when comparing estimates of governance across countries and over time using the WGI. In contrast, in many other measures of governance and institutional quality, they are left implicit.

The WGI are designed to enable broad cross-country and over-time comparisons of perceptions of governance, reflecting the synthesis of views across many existing data sources, and with due regard for margins of error. At the same time, there is a wealth of information in the individual data sources themselves that can usefully be explored for understanding the factors behind overall patterns summarized in the aggregate indicators. For this reason, the component data of the WGI are readily available through the WGI website, and users are encouraged to consult this data alongside the aggregate indicators. In addition, the WGI are not designed to be a tool to evaluate specific governance reforms in individual economies – for this purpose, the WGI should be supplemented with
financing options of small firms. Our empirical tests address the broader question of the choice of public companies, with alternative financing venues (such as equity and public debt) to use secured L/Cs.

# **_4.1 Data Description_**

A sample was randomly drawn of 850 publicly traded manufacturing firms that were listed in Compustat in 1996 and were traded between the years 1991 and 1996.20 To identify firms with secured revolving L/C loans, we searched in LEXIS/NEXIS (a private legal information provider) for our sample firms for UCC liens outstanding against _accounts receivable.21_ The UCC lien includes the date of the filing, the debtor's name, the creditor's name, and a description of the collateral. The inclusion of this information allowed us to distinguish between loans secured by fixed and "floating" assets (such as accounts receivable). Firm-level data was collected from Compustat and CRSP.<sup>22</sup>

# **_4.2 Variable Descriptions_**

# _A. Size, Age, and Growth Variables_

We find in previous literature that size and age significantly affect a firm's ability to obtain external financing. This result is also predicted in our model, which finds that more informationally opaque firms should be more likely to require collateral. Summary statistics of our sample support these findings: The median size of assets of firms without secured L/Cs is $174.22 million while the median size of firms with secured L/Cs is only

> 20 This represents 65% of all manufacturing firms listed in Compustat (SIC codes beginning with 2 or 3). Summary statistics for this subsample are significantly insignificant from the full sample.

> 21 In order to claim priority to a secured asset in the case of default, a lender must legally file in court a UCC lien against the asset(s). Consequently, we can acertain that any outstanding liens would be included in Lexis/Nexis. In addition, SEC 10-K
Policy Research Working Paper 5653

# **Abstract**

Evidence is crucial in strategic planning for HIV response as well as the monitoring of results. This paper presents a simple tool that can be used to analyze the methodological quality of HIV data, its scope and limitations, and whether it can be accurately compared with other evidence. The tool, utilized as a questionnaire or checklist, first identifies the type of document containing the data; the status and means of its publication; the epidemiological design used; and the priority population. Next, the document is analyzed against a verification list based on eight methodological criteria: 1) objective; 2) inclusion and exclusion criteria; 3) sample size; 4) sampling technique; 5) error-reduction strategies; 6) data analysis technique; 7) limitations; and 8) confidence intervals and/or statistical significance. The paper also presents the results of implementing the tool in three Latin American countries.

This paper is a product of the Global HIV and AIDS Program, Health, Nutrition and Population; Human Development Network. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http:// econ.worldbank.org. The author may be contacted at rrodriguezgarcia@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._
those focusing on its relationship with FDI, are considerably less abundant. Moreover, those that consider developing nations show conflicting results (Abadie & Gardeazabal, 2008; Enders et al., 2006; Li, 2006; Oetzel & Oh, 2014; Powers & Choi, 2012). Again, several of these authors ignore other forms of political violence and risk in their empirical strategies, which could largely explain the mixed results.

In Table 3, we include measures for _terrorism_ , _political terror_ and _assassinations_ in our regression models to test our assumption that political violence must be both relatively continuous and detrimental to returns on economic activity. We measure terrorism using the number of deaths during terrorist attacks from the Global Terrorism Database (GTD). This database, developed by the National Consortium for the Study of Terrorism and Responses to Terrorism, is based on reports from a variety of open media sources (LaFree & Dugan, 2007). We prefer this proxy to the number of terrorist attacks because it measures not only the prevalence of attacks, but also their intensity. The number of terrorist fatalities is highly skewed; hence, we transform the measure using the natural log of the inverse hyperbolic sine function. We measure political terror with the widely used Political Terror Scale (Wood & Gibney, 2010), an index constructed based on information from three sources: Amnesty International Yearly Country Reports, the U.S. State Department Country Reports on Human Rights Practices, and the World Reports of Human Rights Watch. The index ranges from 0 in the case of a strong rule of law to 5 in the case of widespread political terror. We measure the numbers of assassinations using the Cross-National Time Series data developed by Banks (2015).

The results confirm that terrorism, political terror, and assassinations in a country do not affect its total greenfield FDI inflows (Figure 2, columns 1-3). The coefficient of the conflict variable BRD is negative and significant at the 10% level in two of the three regression models (columns 1-2
as low as $50. Investors place orders by completing a purchase request form that includes basic personal information (name, social security number, billing address). The information is transmitted to the Financial Management Service Collection system, which is run by a private firm called Govolution that obtains credit approvals and authorizes transactions while customers are online.

Govolution creates daily batches of all approved transactions and passes them on to Mellon Bank, the U.S. Treasury’s merchant bank. The bank debits customers’ credit cards and transmits the funds to the Bureau of Public Debt. Customers receive the securities in paper form. Every day the Bureau of Public Debt conducts reconciles the information in its customer service database with the Mellon Bank’s deposit files. Of the three online systems, this one is the most costly to administer, because the securities are in paper form and credit card purchases are more expensive than ACH payments. This system will be abandoned at the end of 2003 in favor of the new TreasuryDirect discussed below.

# _New_ TreasuryDirect _system_

The new TreasuryDirect system, introduced in October 2002, is an end-to-end purchase and delivery system for electronic securities. It currently allows investors to buy series EE and I savings bonds for a minimum of $25. Investors can open accounts online with a Web browser that supports 128-bit encryption. Payments are processed through an ACH, and investors’ identities are verified online using the Pay.gov authentication engine. (Pay.gov is an electronic transaction management system run by the Financial Management Service that offers electronic financial services—including access control and customer authentication—to other government agencies.) Investors’ personal data are cross-checked across a number of databases to which Pay.gov links. Verification takes about 20 seconds and can be done 24 hours a day, 7 days a week.

9
.......................... 16|
|**C.**<br>**Historical trends and patterns of forced displacement: Insights from available global**<br>**data 17**|
|**D.**<br>**Data on asylum-seekers, refugees and IDPs: sources, applications and credibility .. 31**|
|Data collection: Sources for refugees, asylum-seekers and IDPs ...................................................... 31|
|Registration of refugees and asylum-seekers ............................................................................. 33|
|Registration of IDPs ..................................................................................................................... 33|
|Profiling of IDP situations .........
of reducing machismo and assess how these changes impact the success path to citizen participation. This approach also allows us to evaluate the robustness of the results regarding the influence of reduced machismo on participation.

These methods are informed by the review of technical strategies to mitigate gender biases in AI presented earlier. The gender blinding, deproxing, and shifting/scaling strategies align with data and algorithmic bias mitigation techniques in the literature, such as adversarial debiasing and counterfactual data augmentation, aimed at reducing gender bias in AI models. The WOMENonly and MEN-only models further explore the literature's emphasis on examining genderspecific bias and ensuring fairness across demographic groups, consistent with recommendations for balanced datasets and inclusive AI. The focus on societal gender bias as an overarching factor aligns with calls for considering broader social contexts in AI assessments, as highlighted by Baeza-Yates (2018) and Smith and Rustagi (2021), who stress the need for algorithms to account for societal biases.

# **_3.3 Data and variables_**

This study uses data from the 2023 Latinobarómetro Survey (Latinobarómetro Corporation 2023), an annual survey designed to assess individual perceptions of socioeconomic and political issues. Covering 17 countries in Latin America and the Caribbean, it is the largest regional database on citizen attitudes toward democracy. The survey employs a stratified random sampling method, weighted to accurately represent each country's population. The latest data available during the preparation of this study, released in December 2023, includes 19,205 observations, representing over 600 million people in the region. However, it does not include data from Nicaragua, Haiti, Trinidad and Tobago, or other small Caribbean nations. Data collection was conducted face-to-face from February 20 to April 18, 2023.

The dependent variable in this study is citizen participation, specifically in the context of working to address community problems. The primary independent variable is a composite gender bias score, derived as the first component of a principal component analysis (PCA) based on four indicators that capture the prevalence of gender-biased social norms
The original sale deed and a photocopy are produced before the district sub-registrar at the district-level, and the sub-registrar at the tehsil level, for registration. The clerk compares the photocopy with the original and attaches a certificate. The purchaser then deposits the registration fee (2 percent of the value of the transaction) and is expected to collect the registered document at a later date. However, such registration is voluntary and the validity of the sale deed is not the concern of the registering officer. It is estimated that about 10 percent of all registrations are illegal, in which government land or land belonging to someone other than the vendor is sold to unsuspecting purchasers. Such cases tend to he in urban areas where information asymmetries are high. In the rural areas, land is almost always inva1 jably bought and sold within a village in which people know each other<sup>20</sup> .

The value of the property sold/purchased is verified (from a valuation register) at the time of registration to ascertain that it is not below the current market price. The highest value at which a particular type of property in a particular area is registered in the last three years constitutes the present market value of that property. This verification is necessary to prevent under-valuation, and thereby depresses the future 'market' rate<sup>2</sup> 1.

Other activities of the sub-registrar's office include: _Preservation of document copies:_ Four types of registers are maintained at the registration offices: Book 1 contains the certified photocopies of documents relating to immovable property. Book 3 is concerned with wills. Book 4 consists of documents dealing with the power of attorney, adoption of movable assets, etc. Book 2 records all transactions that are disallowed by the registrar's office, for example, in the event that one of the parties is a minor, stamp duties and registration fees have not been paid, or the transaction falls outside the jurisdiction of the Indian Stamp Act, 1899.

_Issue of
2017|Enquête Gabonaise pour l'Évaluation de la Pauvreté|
|Gambia, The|2015-2016|Integrated Household Survey|
|Ghana|2016-2017|Ghana Living Standard Survey|
|Guinea-Bissau|2018-2019|Enquête Harmonisée sur le Conditions de Vie des Ménages|
|Liberia|2016|Household Income and Expenditure Survey|
|Malawi|2019-2020|Integrated Household Survey|
|Mali|2018-2019|Enquête Harmonisée sur le Conditions de Vie des Ménages|
|Niger|2018-2019|Enquête Harmonisée sur le Conditions de Vie des Ménages|
|Nigeria|2018-2019|Living Standards Survey|
|Senegal|2018-2019|Enquête Harmonisée sur le Conditions de Vie des Ménages|
|South Africa|2017|National Income Dynamics Study|
|Tanzania|2017-2018|Household Budget Survey|
|Togo|2018-2019|Enquête Harmonisée sur le Conditions de Vie des Ménages|
|Uganda|2012-2013|Uganda National Panel Survey|

We exclude gender from the list of circumstances because the outcome, consumption, is measured at the household level and does not capture within-household resource 9