rafmacalaba/datause-encoder-data huggingface dataset:
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- Accenture. 10 ways COVID-19 is impacting payments. `https://www.accenture.com/ _acnmedia/PDF-123/Accenture-10-Ways-COVID-19-Impacting-Payments.pdf` , 2020.

- Sumit Agarwal and Wenlan Qian. Consumption and debt response to unanticipated income shocks: Evidence from a natural experiment in singapore. _American Economic Review_ , 104(12):4205–30, December 2014. doi: 10.1257/aer.104.12.4205. URL `https://www.aeaweb.org/articles? id=10.1257/aer.104.12.4205` .

- Sumit Agarwal, Chunlin Liu, and Nicholas S. Souleles. The reaction of consumer spending and debt to tax rebates—evidence from consumer credit data. _Journal of Political Economy_ , 115(6): 986–1019, 2007. ISSN 00223808, 1537534X. URL `http://www.jstor.org/stable/10. 1086/528721` .

- Sumit Agarwal, Gene Amromin, Souphala Chomsisengphet, Tim Landvoigt, Tomasz Piskorski, Amit Seru, and Vincent Yao. Mortgage refinancing, consumer spending, and competition: Evidence from the home affordable refinancing program. Working Paper 21512, National Bureau of Economic Research, August 2015. URL `http://www.nber.org/papers/w21512` .

- Sumit Agarwal, Wenlan Qian, Bernard Y. Yeung, and Xin Zou. Mobile Wallet and Entrepreneurial Growth. _AEA Papers and Proceedings_ , 109:48–53, May 2019. URL `https://ideas.repec. org/a/aea/apandp/v109y2019p48-53.html` .

- Nader Alber and Mohamed Dabour. The Dynamic Relationship between FinTech and Social Distancing under COVID-19 Pandemic: Digital Payments Evidence. _International Journal of Economics and Finance_ , 12(11):109–109, November 2020. URL `https://ideas.repec.org/a/ ibn/ijefaa/v12y2020i11p109.html` .

- Laura Alfaro, Anusha Chari, Andrew N Greenland, and Peter K Schott. Aggregate and firm-level stock returns during pandemics, in real time. Working Paper 26950, National Bureau of Economic Research, April 2020. URL `http://www.nber.org/papers/w26950` .

- Titan M Alon, Matthias Doepke, Jane Olmstead-Rumsey, and Mich`ele Tertilt. The impact of covid19 on gender equality. Working Paper 26947, National Bureau of Economic Research, April 2020. URL `http://www.nber.org/papers/w26947` .

35
44 only observe differences in wages for a portion of<sup>the population</sup> receiving different amounts of education.<sup>In the first studies of</sup><sup>**the**association</sup> between education and labor earnings, private rates of return<sup>were calculated</sup> under the assumption that the more educated **benefited** froo schooling only to 1 9 the extent that they held<sup>a job in the labor force and reported earnings.</sup> Thus, if a year of additional schooling **raises the wage** rates of **mn** and women by the seae proportion and they both work full<sup>time in the labor force, then</sup> the life-cycle internal rate of return<sup>to the opportunity</sup> cost of attending school for that year is<sup>approximately</sup> equal to **the** proportional wage increment, and the returr is then<sup>identical</sup> for sen and women. But if<sup>women worked</sup> only half of the time in<sup>the labor force after completing</sup> their schooling while men worked all of<sup>the time, the conclusion</sup> was drawn that women earn only half of men's rate of<sup>return on their year of schooling.</sup> Becker (1964), in his seminal contribution on this subject, observes that the lower return to women's<sup>education</sup> due to their lower participation in the labor force is consistent<sup>with the smaller proportion of women than men</sup> attending college in the<sup>United States in the 1950s (Becker,</sup> 1964: 178). Subsequent empirical studies<sup>and surveys of the field that specifically</sup> addressed male-female differences in rates of return to education<sup>adopted</sup> Becker's methodology (Hines X al., 1970; Thais and Carnoy,<sup>1969;</sup> Psacharopoulos, 1973; Woodhell, 1973).<sup>The implicitassumption</sup> of **these** researchers **was** that schooling had no apprecLabl, effect on **the** productivity of persons working outsLid<sup>of the market labor</sup><sup>**force.**</sup> **20 But** thLs **assumption** has subsequently **been** challonged by **a** large **number** of **empirical**<sup>**studios**</sup> that indicate education increases **the** productivity of time in nonmarket production, particularly that of women (summarizod in Eichel, 1982; Haveman<sup>and Wolfe,</sup>
# **Table 2.  Intermediate Indicators of Empowerment: State Domain**

||**Sub-domain: Justice**||
|---|---|---|
|**Presence of rules (institutions)**|**Enactment of rules (institutions)**|**Existing data**<br>**sources/indices**|
|_Formal_<br>•Number of international instruments<br>and conventions on civil and political<br>rights ratified (6)<br>•Index of Civil Liberties (1)<br>(independent judiciary; civil and<br>criminal rule of law)<br>•Press Freedom Index (1) (legislation<br>protecting press freedom)<br>•Civil Society Index (3) (civil and<br>criminal rule of law)<br>•Number of laws/acts providing<br>protection from political oppression<br>•Number of laws/acts providing<br>protection from social oppression<br>•Number of laws/acts providing<br>_protection_from domestic violence<br>•Number of anti-corruption laws/acts<br>(2, 4)<br>•Number of statutory rights conferred<br>by a national framework of criminal,<br>commercial, and international law|_Formal_<br>•Number of reported incidents of government<br>interference in police force per year<br>•Corruption Perception Index (5)<br>(transparency/accountability/freedom from<br>corruption to ensure accessible justice with respect to<br>public officials and professional groups (including<br>investment in capacity building and in HR education/<br>training)<br>•Number of corruption cases tried per year<br>•Number of constitutional courts and national legal<br>mechanisms protecting national constitutional rights<br>(e.g. to fair trial, protection from torture and<br>detention without trial, divorce rights) (8)<br>•Number of affordable and accessible public redress<br>procedures (e.g. independent HR commissions,<br>ombudsmen and complaints tribunals)<br>•Number of cases tried in the national formal legal<br>system enforcing statutory rights per year<br>•Number of cases tried in local formal legal systems<br>(through local government enacting by-laws)<br>enforcing statutory rights per year<br>•Annual public expenditure in rights awareness<br>campaigns<br>•Number of extra-judicial killings per year (8)<br>•Number of extra-judicial disappearances per year (7,<br>8)<br>_Informal (Cultural)_<br>•Number of human rights violations occurring as a<br>result of the enforcement of customary rights<br>through structures of customary authority per year<br>(8)<br>•Number of crimes rooted in living, customary, or<br>religious law (e.g. honor killing, domestic violence,<br>and sexual abuse) reported per year (8)<br>•Number of women using local informal|(1) Freedom House<br>(2) Political Risk Services:<br>International Country Risk<br>Guide–Political Risk Rating<br>(3) CIVICUS<br>(4) World Bank Governance<br>Datasets<br>(5) Transparency International<br>(6) Office of the UN High<br>Commissioner for Human<br>Rights<br>(7) UN Working Group on<br>Enforced or Involuntary<br>Disappearances<br>(8) US State Department–<br>Country Reports on Human<br>Rights Practices<br>Where no data source is<br>identified, data must be<br>collected using the national<br>survey or in-depth research<br>techniques.|

65
inequality is a threat to political and economic stability. When people see some living in luxury while others are impoverished, it creates social unrest that typically culminates in the overthrow of government, disruption of the local economy and collapse of foreign investor confidence.

Negative associations between the ethnic diversity of societies and growth have been reported by authors such as Easterly and Levine (1995) and Mauro (1995). Collier and Gunning (1997) demonstrate that ethnic fractionalization negatively affects policy and reduces productivity more directly. They also show that the correlations are stronger with the delivery of public services such as schools and telephones, and weaker for macroeconomic policy. The wide use of the ethno-linguistic fragmentation indicator has created a mindset in which equates ethnic diversity with economic and political disaster, particularly in Africa. In an important study, Collier and Hoeffler (1998) establish that the relationship between civil war and ethnic fractionalization is not linear. The most unstable societies are those in which the index is around 45-50, societies with two fairly equal ethnic groups. On the other hand, highly fractionalized societies, such as are found in many countries in Africa (average score of 67.6), are as stable as the most homogenous societies.

In Latin America, by contrast, if one groups all the non-Spanish indigenous people together and all the Spanish speakers together, many Latin American countries then consist of two large groups with little interaction across groups, a situation rife with latent conflict. A recently completed poverty study in Peru found that the overall poverty levels had declined in Peru. However, the non-Spanish speaking population had not been integrated politically, socially or economically. In fact it had fallen further behind in income terms even after controlling for education, location, access to services, land and or house ownership (Hentschel et al, 1998).

To complement findings from cross-country data, and to understand the importance of cross-cutting ties in reducing exclusion even in multi-racial, multiethnic industrialized countries, it is useful to examine within-country data. Sustainable economic development requires reciprocal on-going relationships and networks beyond narrow geographic, ethnic or political communities in order to ensure access to additional resources (Portes and Sensebrenner, 1993).

Verba et al (1996) in _Voice and Equality: Civic Voluntarism and American Politics_ address the issue of inequality and the decline in civic engagement in the last three decades in the United States. They demonstrate that politicians listen primarily to those with college education and those who make contributions to political campaigns, which leads to selective hearing of interests of those who are educated, wealthy and organized. Their findings are based on a 25
**Page** 9

**Livestock Insurance in Mongolia**

due to a major campaign to educate herders,<sup>it islikelythatthemajor participants</sup> would be those who are most risky. This<sup>couldcreateseriouslossesforthe pool,</sup> especially given the covariate risk problem.<sup>Whilesome believethatcompulsory</sup> insurance will fix this problem, they are<sup>very likely mistaken.</sup> Further, it is ill advised to require the best herd managers<sup>tousetheirpreciouscash for insurance</sup> that likely will not work for their operation.<sup>This only reducestheiropportunityto</sup> invest in more effective risk mitigation strategies.

Both the weather index and mortality index<sup>insurancescorebetter onseveral</sup> criteria. Weather insurance is unlikely to<sup>protectagainst thegreatnumberof unique</sup> weather conditions that can create a problem<sup>with livestockmortality.This led to the</sup> recommendation to pursue insurance mortality<sup>rates directly.</sup> This idea is also limited on at least three important fronts:<sup>1) anindividual herderwhoisagood</sup> manager can have a loss and not get paid;<sup>2) thequality of themortality data might</sup> change once insurance is being sold based<sup>onthese numbers;and3)it willstillbe</sup> difficult to manage the covariant risk that<sup>arepresentinMongolia.Each ofthese</sup> points will be discussed further below.<sup>Additionally,someverycareful attention</sup> must be paid to numerous details to have successful<sup>mortality index insurance.</sup>

# Description of the mortality measure

The work by Enkh-Amgalan used data from<sup>36sum for the period1969-1999</sup> on mortality rates and birth rates<sup>4</sup> . These data are fairly reliable and afford<sup>the</sup> opportunity to performn a rather complete analysis<sup>ofthe riskand thepossibilitiesfor</sup> insuring based on mortality rates within<sup>eachsum.Thedatawereupdatedforthe</sup> years 1991-2000.

While statistics are developed for adult animals<sup>and offspringwithintheyear,we</sup> chose to use the adult mortality statistics to develop<sup>the insurance index.The censusof</sup> animals is performed every year. The mortality<sup>rateistheratioof totallossesof adult</sup> animals divided by the number of animals reported<sup>in the end of the previousyear census.</sup> _adultlosses total animals_

# Offspring losses are excluded on the following<sup>grounds:</sup>

1. Compared to other age groups offspring<sup>arehighlyvulnerable and lossratesare</sup> usually high. The offspring loss rate is<sup>calculatedasa ratioofoffspringlostto the</sup> total number of born. When losses associated<sup>withimmaturedeliveryareincluded,</sup> the losses increase further. Therefore,<sup>inclusionofoffspringlosseswould</sup> significantly increase the premium rates<sup>makingit less likely that herderscould afford</sup> the insurance.

- 4 1975 and 1979 are missing from the data.
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35
Table 5: Impact of books only on test score

||(1)|(2)|(3)|(4)|(5)|(6)|
|---|---|---|---|---|---|---|
||Peabody|Math|Listening|Reading|Writing|Total Score|
|ATE|-0.105|0.525**|0.186|0.982***|0.124|1.712*|
||(0.78)|(0.02)|(0.20)|(0.00)|(0.72)|( 0.08)|
|_N_|2111|2111|2111|2111|2111|2111|

b coecients; p in parentheses _∗ ∗∗ ∗∗∗ p <_ 0 _._ 05 , _p <_ 0 _._ 01 , _p <_ 0 _._ 001 Note: The matching variables are characteristics of the student, household, teacher and school. For the full list of covariates see Table A.2 in the annex Figure 4: Density of total test score for books only intervention <!-- Start of picture text --> Panel A:- Baseline Survey Panel B:- Follow-up Survey<br>0 10 20 30 40 50 0 20 40 60<br>Total test score Total test score<br>Treatment Treatment<br>Control Control<br>.05 .04<br>.04 .03<br>.03<br>.02<br>Density Density<br>.02<br>.01<br>.01<br>0 0<br><!-- End of picture text --> Note: Total test score is the sum of math, reading, writing, listening and Peabody test scores

# 4.3 Heterogeneity in treatment eects

This subsection investigates any heterogeneity in treatment eects using three subsamples of students, based on their gender, access to extra lessons, and parental education. On the bases of each of the above characteristics, the sample was divided into two subgroups: students who have taken at least one extra lesson per week versus those who did not; students whose either (or both) parent have completed secondary education against those whose parents have not completed high school; and boys or girls. It is reasonable to expect that students who have taken extra lessons or have educated parents could benet dierently from these interventions.

22
provide reconstruction and relief and potentially increasing the economic consequences of the disaster. The route followed by different governments concerning the combination of expenditures, revenues and borrowing will likely depend on the access to lending, its cost, and on the demand for government services. For instance, countries that can borrow at low cost and face the burden of reconstruction and relief may prefer that route to increasing revenues through taxation or restraining expenditures. And countries where private insurance markets share a large fraction of the reconstruction costs (e.g. by financing the reconstruction of private and public capital) may focus on emergency relief, face smaller funding requirements, and expanding expenditures moderately.

This paper estimates the impact of natural disasters on fiscal sustainability by characterizing how government expenditures and revenues typically respond to different types of disasters, and how these responses relate to a government’s ability to borrow and to the availability of private financial sources for private and public reconstruction. Following Raddatz (2009), we do this by estimating the parameters of a Panel Vector Autoregression (PVAR) model that includes real output, government expenditures, government revenues, measures of the occurrence of geological, climatic, and other disasters, as well as other external shocks and standard macroeconomic variables like inflation and interest rates.<sup>1</sup> The three categories of natural disasters we consider follow Skidmore and Toya (2002) and are defined as follows: geological disasters including earthquakes, landslides, volcano eruptions, and tidal waves; climatic disasters including floods, droughts, extreme temperatures, and windstorms; and other disasters including famines, epidemics, insect plagues, wild fires, miscellaneous accidents, industrial accidents, and transport accidents.

Using the parameters of the model we can predict the dynamic response of each of the variables of interest to the occurrence of any type of disaster the same year the disaster occurs and in the years following the disaster. We estimate the model using annual data for high and middle-income countries during the period 1975-2008. While low-income countries are also of interest, data availability and the importance of aid flows for government financing makes them

> 1 These types of models use the cross-country dimension of the data to increase the power of the estimation of time series models, and have been routinely used when short time series data is available, as it is the case in this paper.

2
outcomes for multiple sub-groups, therefore showing the extent to which each social division contributes to exclusion. Their findings highlight that gender-based disparities are larger than class-based differences, where poor men and non-poor men are equally likely to get treatment, but women are always worse off (and worst off in poor households). Based on this finding, the authors conclude that poverty status alone may not be a good predictor of who receives treatment, given that there is gender discrimination within households.

Using the same data, Sen and Iyer (2012) further explore if gender and class can be leveraged to secure health entitlements by groups disadvantaged by one of their identities but not by another one. They focus on the health outcomes of poor men (who face gender advantage, but class disadvantage) in comparison to non-poor women (who face gender disadvantage, but class advantage). They find striking similarities in health outcomes for these two groups, but also point out that the processes through which gender and class are leveraged are different. Again, these findings call for nuanced health interventions that take within-group heterogeneity (and the processes attached to these differences) into greater consideration.<sup>13</sup> Finally, there are quantitative studies in the broader economic literature that disaggregate wellbeing outcomes by gender in combination with other identities, but are not framed as intersectionality studies. For example, Ñopo, Atal, and Winder (2010) find sizable gender- and ethnicity-based wage gaps between indigenous and nonindigenous populations across Latin American countries, which they relate to differences in educational attainment between men and women and between indigenous and non-indigenous persons, as well as to the scarcity of minorities in the highest-paid positions. Other studies document gender-based disparities within and across minority groups descriptively, without analyzing their interactions in a multivariate setting. Grown and Tas (2011), for example, disaggregate a series of employment statistics for the U.S. to show that the impacts of the 2007-10 economic recession concentrated at the intersection of gender, race/ethnicity, age and family structure. In addition to finding a higher unemployment rate among African American and Hispanic women compared to all other groups, their analysis showed that job loss and insecure forms of employment were highest among young

> 13 The intersectionality literature on access to healthcare is expanding in both developing and developed countries. See Hankivsky (2012) for some empirical evidence and an intersectionality-based policy analysis framework.

7