rafmacalaba/data-use-mentions-extended huggingface dataset:
opportunities between polygynous and monogamous households living in the same village — (Dessy et al. 2021).

# **5. Conclusion**

Climate change is the defining challenge of our time, and its impacts are far-reaching and complex. As we design policies to address this challenge, it is essential that we understand the ways in which climate change affects different groups in society. There is growing evidence that climate change has a gendered impact, with women and girls disproportionately affected by extreme weather events and other climate-related phenomena. Understanding these impacts is essential if we are to design policies that are effective, equitable, and sustainable.

The largest differences in the gendered impacts of climate change come from the social responses to weather shocks. In many parts of the world, girls and women are more likely to be discriminated against from an early age, leading to reduced opportunities for education and employment. Women are more likely to withdraw from agricultural work and struggle to find alternative sources of income after weather shocks. Boys may also be taken out of school to work, while men may be forced to migrate in search of new employment opportunities. These social responses to weather shocks could ultimately result in widening the gender gaps.

To design policies that effectively address the gendered impacts of climate change, we need a better understanding of the social mechanisms through which men and women are affected. This requires investment in research that looks at the intersection of climate change, gender, and social inequality. It also requires policies that are designed with a gender perspective, taking into account the unique challenges faced by men and women in different contexts. For this, there is a critical need for improved collection and analysis of gender-disaggregated data. As the COVID-19 pandemic has shown, pervasive gaps in sex-disaggregated data caused knowledge of the gender impacts of the pandemic to be incomplete (World Bank 2021). The lack of gender-disaggregated data makes it difficult to fully understand and address the ways in which men and women are affected differently by climate change. By improving
## **Concentration indices**

This section looks at the evolution of diversification using two different methods of measurement. The first is the proportion of the value of exports of the major export products, a widely used simple and intuitive indicator. The second one is the Herfindahl-Hirschman (HH) index, a well-known indicator used extensively in the literature.<sup>13</sup> The indicators are calculated using nominal trade information and the 12 The analysis starts from 1993, the year as from which the Superintendency of Tax Administration has systematized and integrated information with data on the level of subheadings.

13 The Herfindahl Index is defined as ; where _n_ is the number of observations and _x_ the fraction of exports in relation to total non-traditional exports of the j-th SIC; in this case, the range of the index fluctuates from (maximum diversification) to 1 (maximum concentration). Nonetheless, if the idea is to compare 12
has been a symbiotic relationship between the Bank‘s research department and the research community outside the Bank.

Measuring the impact of these activities on development is notoriously difficult. The Independent Evaluation Group (IEG) of the World Bank attempted an evaluation of country level studies – Economic and Sector Work (ESW) – and TA.<sup>69</sup> One key technique was to use opinion surveys of Bank counterparts in client countries. The report found: ―The majority of ESW and TA met their objectives at least to an average extent during fiscal 2000–06. Between 65 and 80 percent of users of ESW and TA in client countries and between 74 and 87 percent of users within the Bank gave ratings of average and above when asked to what extent these products met their stated objectives. But there were substantial differences in ratings across countries and tasks, some of the reasons for which are as follows. First, the technical quality of ESW and TA influenced their effectiveness. Second, close collaboration with clients, from task initiation through the formulation of recommendations, was important for ESW and TA to be effective, whether clients actually produced part of the task or not. Third, sustained follow-up after the completion of the tasks, rather than just dissemination, was important for effectiveness. Fourth, whether clients requested the tasks or not did not matter for their effectiveness, although tasks not requested by clients needed to be tailored to client needs and interests to be effective. Fifth, there is some evidence that ESW and TA were less effective in countries where

> 67 For a history of World Bank research see Dethier (2009).

> 68 See Ravallion and Wagstaff (2010).  More details are provided below.

> 69 Internal Evaluations Group (World Bank), 2008.

43
31

# <u>Figure 5: Impoverishment due to out-of-pocket health expenditures</u>

Percentage of Households Impoverished by Out−of−Pocket Health Expenditures, PL=$1.90−a−day Percentage of Households Impoverished by Out−of−Pocket Health Expenditures, PL=$3.20−a−day <!-- Start of picture text --> 2.5–4.5 2.5–6.7<br>2.0–2.5 2.0–2.5<br>1.5–2.0 1.5–2.0<br>1.0–1.5 1.0–1.5<br>0.5–1.0 0.5–1.0<br>0.0–0.5 0.0–0.5<br>no data no data<br><!-- End of picture text --> Percentage of Households Impoverished by Out−of−Pocket Health Expenditures, PL=$5.50−a−day Percentage of Households Impoverished by Out−of−Pocket Health Expenditures, PL=$10.00−a−day <!-- Start of picture text --> 2.5–6.1 2.5–5.2<br>2.0–2.5 2.0–2.5<br>1.5–2.0 1.5–2.0<br>1.0–1.5 1.0–1.5<br>0.5–1.0 0.5–1.0<br>0.0–0.5 0.0–0.5<br>no data no data<br><!-- End of picture text --> <!-- Start of picture text --> IBRD
tracked between baseline and endline at household level; as a robustness check, we also report cohort level results for Grade 3 and 4 students tested at the school level.

# **3.3 Mediating variables**

Very few studies have tested any structural model to identify the specific channel through which institutions supporting community engagement impact education outcomes. Nonetheless, we report some additional statistics on mediating variables which can be measured robustly from the detailed household and school level surveys to describe possible ways the interventions might have impacted outcomes.

To assess monitoring of school resources by the community, we analyze data on the frequency with which household heads report having visited schools in academic years 2015/16 and 2016/17.<sup>34</sup> We also present descriptive statistics from the endline household survey on the key priorities which household heads discuss with head teachers when they visit school.

To measure the engagement of communities with SMCs, we employ data from household surveys at baseline and endline testing the awareness of household heads of (i) the existence of the SMC, (ii) its membership, (iii) the frequency of its meetings, (iv) the amount of school grants it controls, and (v) the requirement to prepare a SIP.

To measure improvement in alignment of SMC activity with communities’ priorities, we analyze the main items of expenditure in SIPs developed during the capacity building exercise provided to

> 34 A greater number of visits to the school or to see the Head Teacher suggests a greater interest in education, as well as more engagement in the way resources are utilized at the school level. We note that the number of visits to school may not fully capture the quality or relevance to school issues of interaction between teachers, head teachers and parents at the school level.

31
(e.g. Mexico and Panama) PCRs collect, for each credit, date of origination, contractual maturity and amortizing profile, and register the occurrence of early amortizations. With this information the effective maturity for different credit lines can be estimated. Also, it is quite simple to track and analyze the behavior of borrowers’ balances prior to the event of default, and hence estimate the exposure at default of credit lines at different banks.

Bank deviation from the IRB underlying assumptions should also be of concern for bank supervisors, and some of them can be addressed with PCR data. The IRB approach relies on the assumption that banks portfolios are perfectly granular and have therefore diversified away all the idiosyncratic risk. Therefore, it is important that supervisors inspect that loan portfolios are sufficiently fine grained (for example, computing a Herfindahl index). Consideration should be given to adopting corrective measures, for example with granularity add-ons that adjust capital requirements for undiversified idiosyncratic risk (Gordy, 2002). However, Tarashev and Zhu (2008) show that a violation to perfect granularity has a more limited impact on IRB measures of risk than a deficient calibration of the IRB model, resulting for example from wrong asset correlations.

The possibility to perform these exercises on an off-site fashion without using bank internal data facilitates the supervisory assessment of their internal rating systems.

- **Auxiliary rating systems** . Whether to level the playing field in the banking sector or to facilitate banks gradual adoption of more advanced risk management tools, supervisors can use PCR data to build risk rating systems themselves. These can be provided to those banks that are unable or unwilling to develop their own systems (for example because they lack sufficient historical data, resources or experience). They can also be used by the supervisors to benchmark banks’ internal rating systems; for example, flagging those borrowers who are rated abnormally well.

# _The macroprudential revolution in Basel III_

The traditional approach to banking sector regulation and supervision has been predominantly microeconomic, mainly concerned with stand-alone
procedures undergone by citizens while accessing public services and goods, they cannot represent the variety of experiences faced by different individuals. This was mainly observed while attempting to collect data for areas such as paying taxes, access to health, access to education, and access to utilities. In these areas, the most relevant information regarding interactions lies in the practical experience of respondents rather than on what is written in laws or regulations. Therefore, surveys aimed at collecting data from a representative sample of households would be the optimal approach to retrieve data about citizen-government interactions based on the respondents’ own experiences.

Moving forward, the team should refine and redesign the questionnaires according to the type of data collection – contributor-based or household survey – with relevant questions that target specific audiences. Household surveys must have questions that are crafted in a more straightforward and intuitive manner. Contributor-based questionnaires should be more technical and require respondents to indicate the corresponding legal basis for their answers.

A second lesson learned was that the initial scope of the project was too complex and nuanced to be dealt with using limited human and financial resources. Each area of study requires technical skills, extensive research, and in-depth sector-specific analysis in order to convey the project’s ultimate goal, which is to measure bureaucratic complexity in citizen-government interactions. Moving forward, _Living Life_ would benefit from refinement of its methodology by selecting only two or three areas of study for in-depth data collection and 29 | P a g e
<!-- Start of picture text --> 40<br>Rest of the World 6<br>USA<br>Middle East (Saudi Arabia and UAE)<br>30 Europe (Germany and UK) 4<br>China (Mainland and Hong Kong) and Singapore<br>2<br>20<br>0<br>10 -2<br>-4<br>0<br>-6<br>-10<br>-20 Middle East (Saudi Arabia and UAE)<br>USA<br>2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017<br>2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017<br><!-- End of picture text --> Note: Data is from UN Comtrade database. Years are calendar years. Export growth in nominal USD.

Significant improvement in the competitiveness of Indian firms would be the key to reinstate the increasing trend in its share in global exports. The factors that may help India improve its competitiveness include an infrastructural boost to bring it at par with other manufacturing hubs of the world; reforms in land, labor, financial markets, and in the educational system, to assure the continued competitive supply of key production inputs, such as labor, land, finance, and skills. Building on recent improvements in its Doing Business ranking, India can benefit from further strengthening of the competitive business environment. Besides, issues related to competitive exchange rate, enhancing bilateral and regional trade integration, evading the temptation to cave in the rhetoric on trade protectionism, and embedding more deeply in the global value chains all assume great significance and require an objective discussion and assessment.

46
and Central Europe and the Former Soviet Union in 2002, 2005, and late 2008 or early 2009.<sup>13</sup> The second is the Financial Crisis Surveys (FCS), which were conducted in six countries in the middle of 2009.

The surveys provide complementary information. BEEPS provide information on perceived financial constraints over time for most countries in the region. Although the last round of surveys was conducted relatively early in the crisis, we can use BEEPS data to track responses to questions about financial constraints over time for a wide set of countries. As discussed below, because managers‘ perceptions are likely to be forward looking, the responses received at the onset of the crisis should reflect managers‘ initial views about the likely severity of the crisis. In contrast, although the FCS was only conducted in six countries, it provides concrete information on the effect of the crisis as it was unfolding.

# **A. Business Environment and Enterprise Performance Surveys**

BEEPS covers a broad range of issues about the business environment, including access to and the use of financial services. Because one goal was to provide information on a panel of firms over time, considerable effort was made to collect accurate, detailed, and comparable information across survey waves. Despite these intentions, new questions were added to later rounds and some questions were modified in terms of wording or response options.<sup>14</sup> Our study of financial constraints requires an indicator that is comparable over the three rounds. The best candidate is a broad measure of managers‘ views about access to financing: ―Is access to finance, which includes availability and cost, interest rates, fees and collateral requirements, No Obstacle, a Minor obstacle, a Moderate Obstacle, a Major Obstacle, or a Very Severe Obstacle to the current operations of this establishment?‖ This question provides a comprehensive measure of managers‘ views about financial constraints.

> 13 The first round of the BEEPS was conducted in 1999 but the coverage
# **Literature**

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Azzarri, C., Carletto, G., Covarrubias, K., A.P., Petracco, de La O. C., Scott, K. and Zezza. A. (2010). “Measure for Measure: Systematic Patterns of Deviation between Measures of Income and Consumption in Developing Countries - Evidence from a New Dataset”. Paper presented at the Fifth International Conference on Agricultural Statistics (Icas-V), 13 - 15 October 2010, Kampala, Uganda.

Azevedo, J.P., and Atamanov, A. (2014). Pathways to the Middle Class in Turkey: How Have Reducing Poverty and Boosting Shared Prosperity Helped? Policy Research Working Paper; No. 6834. World Bank, Washington, DC.

Beegle, K., De Weerdt, J., Friedman, J. and Gibson, J. (2012). “Methods of Household Consumption Measurement through Surveys: Experimental Results from Tanzania.” _Journal of Development Economics_ 98(1): 3–18.

Burbidge, John B., Magee, L. and Robb, L. (1988). “Alternative Transformations to Handle Extreme Values of the Dependent Variable.” _Journal of the American Statistical Association_ 83 (401): 123–27. doi:10.2307/2288929 Chen, S. and Ravallion, M. (2010). The developing world is poorer than we thought, but no less successful in the fight against poverty. Policy research working paper 4703. World Bank, Washington DC.

Coudouel, A., Hentschel, J. and Wodon, Q. (2002). Poverty Measurement and Analysis, in the PRSP Sourcebook, World Bank, Washington D.C.

Datt, G. (1998),
the Russian economic agenda between mid-1995 and the meltdown, views stabilization as a strictly macroeconomic phenomenon, with enterprise reform interpreted largely as privatization. However, the accumulated experience with transition since 1990 makes two points about hard budget constraints for enterprises: 6 (i) they are an indispensable microeconomic complement to macroeconomic stabilization, as documented here; (ii) they are necessary for the enterprise restructuring that supports the initial revival of growth, and for the credibility of reforms. 7 Later, the manner in which Russia pursued stabilization (not by cutting fiscal deficits) is discussed, while the rest of this section dwells on hard budget constraints.

> 5 For Gazprom, ferrous metallurgy and petrochemicals have become main targets, while UES concentrates on penetrating non-ferrous metallurgy.

> 6 This term was coined by Professor Janos Kornai. For the seminal article, see Komai (1986). 7The earliest published evidence on the efficacy of hard budgets and competition for transition economies is contained in Pinto, Belka and Krajewski (1993). This result has been confirmed most recently by a 3000-firm survey conducted by EBRD and reported in Carlin, et al. (1999), and discussed in Chapter 7 of the EBRD Transition Report, 1999.
countries. They also find that these misperceptions lead to a negative bias in preferences for redistribution, which does not disappear with the provision of objective information. Hangartner et al. (2019) find that refugee immigration to Greece increased natives’ hostility toward refugees and support for restrictive immigration policies.

There is a small literature on the effects of the Venezuelan exodus on popular opinion in Latin America. For Chile, Ajzenman et al. (2021) find negative effects on natives’ security perceptions, despite null effects on the objective crime rate.<sup>4</sup> They identify media to be an important determinant in this context due to disproportionate coverage of immigrantperpetrated homicides that trigger crime misperceptions. For Colombia, Chatruc and Rozo (2021) find that economic concerns, despite a lack of objective evidence on negative labor market effects, are another important driver of anti-immigrant sentiment. Additionally, Rozo and Vargas (2021) identify strategic electoral misinformation in Colombia as an additional channel. Exploiting rich opinion polls, we contribute to this literature by estimating the causal impact of migration on both attitudes and perceptions of natives and immigrants in the same context.

There are also a number of studies conducted within the DFID-WB-UNHCR initiative _"Preventing social conflict and promoting social cohesion in forced displacement contexts"_ that relate to our analysis. Relying on data from the Gallup World Poll, Aksoy and Ginn (2021) analyze the effect of refugee inflows on natives’ attitudes towards refugees in a global sample of low- and middle income countries. Interestingly, they do not find evidence of a negative effect on attitudes. They also investigate potential heterogeneity in those effects across camp and non-camp refugee settings as well as across progressive and restrictive right-to-work environments and find little evidence for any differential effects.

For the case of Colombia, Allen et al. (2021) conduct a survey experiment investigating the preferred policy preferences of native Colombians in response Venezuelan mass immigration. On the one hand, their results suggest that natives favor the use of numerical immigration limits and
, and short-wave infrared 2. For city-level wealth prediction, we collect PlanetScope (3m/pixel) and SkySat (0.5m/pixel) multispectral satellite imagery to cover each administrative area in Lilongwe and Blantyre. Based on the average size of administrative areas, we empirically define the size of each grid as 0.3 × 0.3km<sup>2</sup> , which results in each PlanetScope image with 100 × 100 pixels and each SkySat image with 600 × 600 pixels. Despite using 2018 household-level census data, we utilized available PlanetScope and SkySat imagery acquired in April 2023. These images contain red, green, blue, and near-infrared bands.

**Geospatial features.** In addition, we supplement satellite imagery with publicly available processed geospatial features, which we refer to as _geo-features_ . These geo-features capture population, developmental, and environmental statistics. These features are population structure [18], population density [28], annual rainfall [1], minimum and maximum temperature [1], nighttime lights [3, 11], terra net primary product [10], aqua net primary production [24], cellphone tower count [22], impervious surface change year [15], land cover type [5], GHSL [26], building counts [27], building areas [27], soil pH [16], and soil organic carbon [16]. A visual representation of one datapoint is provided in Figure 5; note that final asset wealth labels are combined into a single scalar value.

## **Training wealth measurement models**

The comparisons include a tree-based model, namely extreme gradient boosting (XGBoost) [7] and two advanced deep learning models (convolutional neural networks and transformers based on an encoder-linear architecture [29]. Based on empirical and Page 8 of 11
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