rafmacalaba/data-use-mentions-extended huggingface dataset:
criminal justice. The work by Hendley and Murrell (2003) is a rare exception to the lack of emphasis on the role of government in this context, though this paper's attention to this role is linked to the focus on the transition of Romania from socialism. Our data suggests that government officials do sometimes support the enforcement of agreements, even if that role is minor. In the _strong comprehensive governance_ class of supplier relations, government officials are prominent.

Second, given the amount of attention paid in the literature to non-paid private third parties, especially networks, one would expect them to be more important. Network approaches have been very popular in recent decades, following Granovetter's (1985) emphasis that transactions are embedded in a broader social structure, the historical-theoretical analysis of Greif (1989), and case studies on the importance of trading networks in varied settings (Bernstein 1992; Landa 1981). However, as we point out in Section II, the term 'network' is used in diverse ways in the literature, some of which would imply that a network is present even when the reference is only to a large grouping of similar agents who are not necessarily invoked in any type of enforcement process. In fact, our results suggest that, in aggregate, non-paid private third parties are arguably the least important of the six agents in enforcement activities (Tables 1, 2a, and 2b).

# **V. Variations in the Importance of Governance Structures**

In this section, we examine how the importance of governance structures varies with the environment of firms, focusing on the countries and regions in which they are located. This exercise and that in Section VI are exploratory, providing examples of how our LCA-generated data can be used to understand the links between governance structures and their determinants. Here, we simply explore patterns in the data and do not attempt to isolate ceteris paribus, causal effects of single variables. Nevertheless, this exercise adds evidence on the validity of the data we have
even if the model is correctly specified, the MSE of the ELL estimators can be substantial, especially if the prediction power of the model is weak.

# **3 Molina and Rao’s EB and Census EB estimators**

Molina and Rao (2010) consider the nested error model (1) as in the ELL procedure, but the location effects are originally defined for the areas of interest. A more recent paper by Guadarrama, Molina and Rao (2018) further extends the EB method of MR (2010) to complex sampling designs, but so far it has not been implemented in any software package as a library or command, unlike the traditional ELL (2002) with the subsequent updates by Van der Weide (2014). For simplicity, this section describes the original EB approach proposed by MR (2010).

The main difference with the ELL approach is that the EB method of MR (2010) conditions on the survey sample data and thus makes a more efficient use of the survey data, which contains the only available (and hence precious) information on actual welfare. Nevertheless, conditioning on the survey data requires areas and households across survey and census to be matched. Thus, if _Pc_ denotes the area’s population of size _Nc_ , then the survey sample, _sc_ , is a sample of size _nc ≤ Nc_ drawn from _Pc_ . The complement to the sampled population is referred to as _rc_ , which is just _Pc − sc_ . Thus, the census

> 10Note that the total survey sample size _n_ is typically large.

6
A potential explanation of these results is alcohol induced physical intimate partner violence (AIPIPV). Existing evidence from Psychology shows that Intimate Partner Violence (IPV) is a major predictor of post-traumatic stress disorder in abused women (Pico-Alfonso, 2005) and can drive negative interactions between mother and children (Taylor et al, 2009), directly affecting child development (Bedoya et al, 2020). Using YL data, Bedoya et al (2020) find that IPV is one of the main forms of violence against women in Peru. The authors also find that early-life exposure to AIPIPV is indeed associated with lower test scores in vocabulary.

A second explanation is budget constraints. Allocating household income to consume alcohol reduces the availability of resources in the household for other needs, including inputs that help to support child development. This creates a vicious cycle for mothers with mental health issues, since it can impose additional stressors.<sup>16</sup>

# **5. Discussion and conclusions**

In this paper, we explore the extent to which maternal depression affects child cognition. The identification strategy exploits variation in the exposure to a particular exogenous shock between pregnancy and when the child was 1 year old in Peruvian households. Exposure to the shock can affect maternal mental health and children’s vocabulary development. The paper’s main results indicate that exposure to a crop or livestock loss in 2002 increases maternal depression in that period. Moreover, a standard deviation decrease in maternal mental health in 2002 negatively affects the child’s vocabulary by up to 0.54 standard deviation when children are 5 years old, a result that fades out by time the children are 8 years old. That is, our results suggest the negative effects of maternal depression on child receptive vocabulary do not persist beyond children’s early school years. However, given that vocabulary size in kindergarten and earlier predicts reading comprehension throughout school and into early adulthood, facilitating the development of other cognitive skills (Powell and Diamond 2012), and potentially
- <mark>Nollenberger, Natalia, and Núria Rodríguez-Planas. "Full-time universal childcare in a context of low maternal employment: Quasi-experimental evidence from Spain."</mark> _<mark>Labour Economics</mark>_ <mark>36 (2015): 124-136.</mark>

- <mark>Padilla‐Romo, María, and Francisco Cabrera‐Hernández. "Easing the constraints of motherhood: the effects of all‐day schools on mothers' labor supply."</mark> _<mark>Economic Inquiry</mark>_ <mark>(2018).</mark>

- <mark>Pitt, Mark M., Mark R. Rosenzweig, and Donna M. Gibbons. "The determinants and consequences of the placement of government programs in Indonesia."</mark> _<mark>The World Bank Economic Review</mark>_ <mark>7, no. 3 (1993): 319-348.</mark>

- <mark>Schlosser, Analia. "Public preschool and the labor supply of Arab mothers: Evidence from a natural experiment."</mark> _<mark>Manuscript, The Hebrew University of Jerusalem</mark>_ <mark>(2011).</mark>

- <mark>Strauss, John, Firman Witoelar, and Bondan Sikoki. "The fifth wave of the Indonesia family life survey: overview and field report."</mark> _<mark>RAND: Santa Monica, CA, USA</mark>_ <mark>(2016).</mark>

- <mark>Strauss, John, Firman Witoelar, Bondan Sikoki, and Anna Marie Wattie. "The fourth wave of the Indonesian Family Life Survey (IFLS4): overview and field report."</mark> _<mark>RAND Corporation</mark>_ <mark>(2009).</mark>

- <mark>
et al theorize that ...rms exporting to high income destinations will hire a higher proportion of high skilled workers and will pay them higher wages than ...rms that either export to low or middle income countries or sell their products domestically. They test their theory with 1998-2000 panel data from Argentine manufacturing ...rms. Their ...ndings show that Argentine ...rms exporting to high-income countries are associated with higher skilled workers and higher average wages than ...rms that either do not export or export to middle income countries. However, they ...nd no signi...cant di¤erence in ...rms’use of skilled labor between those ...rms selling their product domestically and those exporting to low and middle income countries. The authors reason that these results are due to the similarities in the domestic and export markets among low and middle income countries. Their theory and results are in line with Verhoogen’s (2008) ...ndings on the quality upgrades of exporting ...rms and Bustos’ (2007, 2009) work on technology and skill upgrading behavior of exporting ...rms. The results further suggest that non-homotheticities in demand are important for income distribution (as suggested in theory, though not with the same mechanism, by Fajgelbaum, Grossman and Helpman (2009)).

To sum up, the emerging work on trade and inequality with ...rm-level data appears to be con...rming a central role for between-...rm e¤ects in governing the relationship between trade and inequality, and the available results seem to support the thrust of theoretical models in Section 2.2 that predict a rise in inequality with more openness.

# 3.3 New Empirical Work on Trade in Tasks.

Much new empirical work focuses on the fragmentation of the production process, or o¤shoring. Recall from Section 2.3.1 that one of the pioneering theory models in
) Manufacturing (right)<br>15 100<br>13<br>95<br>11<br>90<br>9<br>85<br>7<br>Share revenue generated from goods<br>Share revenue generated from services<br>5 80<br><!-- End of picture text --> Source: EIS data from Turkey; author’s calculations.

# **Box 3.1: Where does servicification take place?**

Servicification involves all kind of services activities such as R&D, design, and marketing, as well as construction and transportation services. Depending on where in the supply chain the manufacturing firm is located, it adds or sells different services to downstream users (or consumers). Studies using aggregated value‐added of exports data show that industries such as chemicals and motor vehicles use the most services value‐added while coke and petroleum use the least (Miroudot and Candestin, 2017).

Across countries, business services and distribution services are most prominent in terms of services activities by manufacturing industries. Across sectors, however, capital‐intensive industries seem to be

> 9 From the Ministry of Science, Industry and Technology (MoSIT) Enterpreneurial Information System (EIS) database.

14
Policy Research Working Paper 8885

# **Abstract**

- This paper uses the construction of India’s Golden Quadran gle central highway network, together with comprehensive loan data from the Reserve Bank of India, to investigate the interaction between infrastructure development and financial sector depth. The paper identifies a disproportionate increase in loan count and average loan size in districts along the Golden Quadrangle highway network, using stringent specifications with industry and district fixed effects. The results hold in straight-line instrumental

variable frameworks and are not present in placebo tests with another highway that was planned to be upgraded at the same time as Golden Quadrangle but subsequently delayed. Importantly, however, the results are concentrated in districts with stronger initial financial development, suggesting that although financing responds to large infrastructure investments and helps spur real economic outcomes, initial financial sector development might play an important role in determining where real activity will grow.

This paper is a product of the Macroeconomics, Trade and Investment Global Practice. 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://www.worldbank.org/prwp. The authors may be contacted at eghani@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._ Produced by the Research Support Team
perceptions of the individuals interviewed – such as in Ocello et al. (2015) – whose accuracy remains questionable. The inclusion of longer-run climatic measures and time series would also allow the implementation of more recent and sophisticated techniques tailored to bridge the external validity gap between weather and climate, such as long differences or the inclusion of several weather lags in the regression models.

Lastly, while standard nationally-representative household surveys such as the LSMS-ISA are clearly disadvantaged with respect to the possibility of investigating the migratory outcomes of localized suddenonset weather shocks, which require _ad hoc_ post-disaster surveys, the use of ‘mixed-mode’ data collections solutions, such as the alternation of standard face-to-face surveys with higher-frequency phone-survey interviews, would allow one to obtain not only more timely and frequent longitudinal information in general but also, in case a sudden shock occurs, the collection of basic migration data in the aftermath of the shock itself, and to do so in an easier and less expensive way compared to the complexity associated with the implementation of a swift _ad hoc_ survey in the area exposed to the disaster.

33
These results show that while the differences in performance metrics between different modeling scenarios are not very large, small differences can multiply over space leading to substantial differences in maize area estimation. Hence, there is value in achieving small performance gains anchored in better training data.

Finally, after evaluating maize classification performance in Malawi and Ethiopia, we generated 10-meter resolution rasters of area cultivated with maize for both countries over the period of 2016-2019. Table 10 provides an overview of these rasters. After creating the rasters of probability of maize cultivation, we generated binary maizeland masks for each country and season in two steps. We first used our country- and season-specific cropland rasters to remove all pixels that were not cultivated with any crops. Pixels with probability of (any) crop cultivation less than 40 percent were assumed to be non-cultivated. Subsequently, we used our country- and seasonspecific maizeland rasters to identify which of the cultivated pixels were cultivated with maize. In Malawi, pixels with probability of maize cultivation greater than or equal to 60 percent were assumed to be cultivated with maize. The comparable threshold was 50 percent in Ethiopia.

Table 10: Specifications of predicted maizeland rasters in Malawi and Ethiopia

|**Country**|**Maize classification**<br>**model specifications**|**Seasons trained on**|**Seasons predicted on**|
|---|---|---|---|
|Malawi|Plot mean geolocation<br>method,<br>0.05 ha area threshold,<br>Optical features only|2017/18 rainy season,<br>2018/19 rainy season|2015/16 rainy season<br>2016/17 rainy season<br>2017/18 rainy season<br>2018/19 rainy season|
|Ethiopia|Corner point geolocation<br>method,<br>No area threshold,<br>Optical features only|2018 meher season|2016 meher season
1980s and were adults being surveyed in the ESS from 2002 to 2018. In addition to climate and voting outcomes, the ESS data contains birth year and years of education for every individual, which are critical to mapping climate outcomes to cohorts of students affected by compulsory schooling laws, and who in turn experienced exogenous shocks to their educational attainment.

To examine the causal effect of education on climate outcomes, we leverage a new World Bank dataset on compulsory schooling laws (CSLs) in Europe. Europe has had dozens of education reforms throughout the twentieth century expanding the number of years of education legally mandated through compulsory schooling laws. Figure A1 in the Appendix includes a map of the number of compulsory schooling law reforms which can be mapped to the ESS data over this time period. For each CSL, we have information on the year it was passed, the year it came into effect, and the new minimum schooling requirement under the law. For most CSLs, we also have the school starting age, and assume this to be 6 years – the most common school starting age – for CSLs for which it is missing; this lets us calculate the birth year of the first affected cohort. We identify the CSL which applies to each respondent by finding the CSL that is applicable to their birth year cohort.

Together, these two unique datasets yield exogenous shocks to education which can be mapped directly onto climate outcomes including beliefs, behaviors, policy preferences, and voting.

# **III Empirical Strategy**

## **III.A Compulsory Schooling Laws as an Instrument**

Compulsory schooling laws are commonly used in the economics literature as an instrument for educational attainment. We briefly review the necessary conditions for their use in our context. First, compulsory schooling must affect educational attainment. While this may seem obvious, we show in Section III.B that this relationship holds for many reforms, but does not necessarily hold for all. Thus, following (Oreopoulos, 2006), we carefully identify reforms which bind
nighttime lights|0.15|
|Structural feature sets mean,scale 7|1.00***|Minimum of nighttime lights|0.48|
|||Maximum economist costs of drought|0.00|

24 Ayush et al (2020) also finds that the use of interpretable features instead of features derived from transfer learning increased predictive power by 31 percent in Uganda, which is consistent with the stronger performance seen in these models.

25 Engstrom et al (2017) averages a model-based estimate of poverty derived from the census over large numbers of census households in each village, which makes it similar in practice to a non-monetary measure of poverty.

21
in the bottom panel of Table 6 and show that our previous results stand and remain statistically and economically significant. Both _CIF_ and _COD_ decline significantly during the crisis year and, according to the Wald tests, are statistically smaller than their average during the preceding two years. Also consistent with our previous results, gross capital flows during the post-crisis period remain at depressed levels in comparison to the run up to crises. In sum, the results in Table 6 show that the behavior of foreign and domestic agents during the recent financial crisis is in line with their behavior during previous crisis episodes, with estimates confirming a generalized retrenchment of gross capital flows around these events. Hence, for the remainder of the paper, we proceed with the analysis of the data based on our entire sample period, from 1970 to 2009.

Thus far we have considered a single crisis indicator that pools together several types of financial crises for a particular country in a given year. We extend this analysis by considering the intensity of the turmoil episodes and distinguishing mild and severe crisis episodes.<sup>25</sup> In particular, as described in Section 2, we classify crisis events into: _one crisis_ episodes, in which a country experiences the beginning of one, and only one, type of crisis in a given year; and _more than one crisis_ episodes, in which a country faces the beginning of more than one type of crisis within a given year. We estimate the following equation, which adapts equation (4) to these two indicators: where _Yc_ , _t_ stands for our standardized measures of _CIF_ or _COD_ ; _One Crisis_ corresponds to the _one crisis_ indicator; _More One Crisis_ stands for the _more than one crisis_ indicator; and _Controls_ capture additional control variables such as country trends.

> 25 De Paoli, Hoggarth, and Saporta (2009) show that twin crises feature larger output losses than milder episodes.

21
Financial Times, Measuring what matters: the scramble to set standards for sustainable business, 14 May 2021 <u>Measuring what matters: the scramble to set standards for sustainable business | Financial Times (ft.com)</u>

Gibson, R., P. Krueger, N. Riand, and P. S. Schmidt, ESG Rating Disagreement and Stock Returns. SSRN Scholarly Paper ID 3433728, Social Science Research Network, Rochester, NY, 2019.

Haralampieva, V., Ramping Up Climate Action by Enhancing Companies' Governance Framework, - Law in Transition Journal, 2019 Articles | EBRD LiT 2019 (lit <u>ebrd.com)</u>

ILO, Small matters, Global evidence on the contribution to employment by the self-employed, micro-enterprises and SMEs, International Labour Organization, 2019 ILO, The power of Small: Unlocking the potential of SMEs, International Labour Organization, October 2019 OECD-JRC, Handbook on Constructing Composite Indicators, 2008, <u>https://www.oecd.org/els/soc/handbookonconstructingcompositeindicatorsmethodologyanduser guide.htm</u> Moody’s, ESG Score Predictor: Applying a Quantitative Approach for Expanding Company Coverage, July 2021

- <u>60ec66d0af57878032604495_ESG Score Predictor_090721.pdf (website files.com)</u>

SASB, SASB Conceptual Framework and Rules of Procedure <u>Academic ESG data review | PRI Web Page | PRI (unpri.org)</u>

World Economic Forum, Statement of Intent to Work Together Towards Comprehensive Corporate Reporting (Summary of alignment discussions among leading sustainability and integrated reporting organisations CDP, CDSB, GRI, IIRC and SASB), September 2020 Statement-of-Intent-to-Work- <u>Together-Towards-Comprehensive-Corporate-Reporting.pdf (netdna-ssl.com)</u> Oh, S., D. Noh, Are Corporations feeling the heat?, World Bank Sovereign ESG Data Framework, September 2021 <u>Sovereign ESG Data Framework | Sovereign Environment Social Governance Data | World Bank</u>

# **7
plow use to be negatively associated with current attitudes towards gender equality, and female participation in labor, politics, and entrepreneurial activities. Therefore, the work of Alesina, Giuliano and Nunn (2013) suggests that norms around gender roles may have been established even earlier in the pre-industrial period.

Restrictive or conservative gender norms may translate into behaviors that disadvantage female labor supply and earnings, and/or discourage male engagement in childcare and household chores. Norms are expected to influence behavior through expectations of what others in your reference group do or approve of (Gauri, Rahman and Sen, 2019). In addition, when measuring gender beliefs, there may be expectations that men and women should play different roles in society (gender role beliefs) and that men and women are essentially different (gender category beliefs). The questions included in the Survey on Gender Equality at Home mainly capture measures of gender role beliefs rather than measures of beliefs in gender essentialism. Both genders may face norms costs imposed by those community members who disapprove of certain behaviors that contradict the expectations of the roles of men and women in their society (Bernhardt et al., 2018). Women or men who defy stereotypical norms potentially do so at a personal cost. For example, Bertrand, Kamenica and Pan (2015) show in the US that it is relatively unlikely that a woman will earn more than her husband, and when she does, marital satisfaction is lower and divorce is more likely. Friedson-Ridenour and Pierotti (2019) find that some women in Ghana explicitly limit their business growth in order to reinforce their husband’s role as a primary provider. In addition, for many men, engaging in care and housework is inconsistent with male gender roles and indicates weakness; and when men feel threatened in their role as providers, they may be even less inclined to engage in behavior associated with female gender roles (Munoz-Boudet et al., 2013).<sup>6</sup> A first contribution of the paper is to