rafmacalaba/data-use-mentions-extended huggingface dataset:
Policy Research Working Paper 9625

# **Abstract**

This paper examines to what extent household surveys and censuses in low- and middle-income countries include disability questions and the types of questions under use. A pool of 734 data sets and 1,297 data set-years from 133 low- and middle-income countries from 2009 to 2018 were screened for disability questions, which were classified by type of questions: Washington Group short set of questions, other functional difficulty questions, activities of daily living, broad activity limitation, general disability, and other disability questions. Only 31 percent of the data sets under review had at least one disability-related question and 15 percent of the datasets of low- and middle-income countries have functional difficulty questions that meet international standards, whether the Washington Group short set or other functional difficulty questions. The most commonly found disability question is the general question “Do you have a disability?” which does not produce meaningful and internationally comparable data. The adoption of functional difficulty questions such as the Washington Group short set in national censuses and surveys and in international surveys is needed to monitor the implementation of the 2030 Agenda for Sustainable Development as well as the Convention on the Rights of Persons with Disabilities.

This paper is a product of the Development Data Group, Development Economics. 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 mitra@fordham.edu.

_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
reported in Table A17 and A18 in the Appendix. Despite losing more than one third of our observations, unexpected demand shocks still have a significantly positive effect on sales and exports, with coefficient magnitudes that are very similar for exports and even larger for sales. Furthermore, we find significantly positive effects on monthly and hourly wages that are larger than our baseline estimates. Overall, these results suggest that our results are not particularly driven by exceptional adjustments during the global financial crisis.

# **6 Conclusion**

In this paper, we examined the effects of unexpected demand shocks on worker compensation. We proposed a new methodology to identify the unexpected component of demand shocks at the firm-level, exploiting errors in the official forecasts in the GDP growth of export markets. In each destination, the unexpected component of demand shocks was measured as the difference between the GDP growth actually observed and recent forecasts published in the World Economic Outlook of the International Monetary Fund. We then aggregated these shocks at the firm-year level, weighting by the initial share of destinations in firms’ total sales. Since firms initially served different destinations to a varying degree, they were differentially exposed to these unexpected demand shocks across markets.

In the empirical analysis, we found that unexpected demand shocks have significant effects on sales, employment, investment and average wages. Using employer-employee panel data, we reported evidence that revenues from unexpected demand shocks are partly transmitted to workers in the form of higher average wages, but in a highly unequal way, with most of the wage increases occurring close to the top of the within-firm wage distribution. These wage increases, which include an increase in average base wages, occur despite some evidence that the skill composition of the workforce is negatively affected by unexpected demand shocks.

These results suggest that wages to some extent reflect rent sharing between firms and their workers, and our analysis indicates several different channels through which such rent sharing occurs. One channel is collective bargaining power, which is corroborated by our finding that positive base wage responses to demand
AUC represents the area under the receiver operating characteristic curve. Each study presents AUC estimates from multiple specifications; we present the range as well as the best out of sample AUC for each sample. These best estimates will tend to overstate performance on independent samples because they are selected based on performance on the test dataset. (Baesens et al., 2003) also reports results from publicly available Australian and German data sets, but the outcomes are not specified so they have been omitted. Source: authors’ analysis from telecom data.

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against less Participation.<sup>41</sup> They also confirm that the same is not true for Protection ( ) as can be seen from the positive and significant relationship of with . In contrast, when using PP1 data on OECD countries both Provision and Protection are in a positive and significant PP1 PP3 relationship with Participation, which rules out the potential existence of any bargain between governments and citizens through , , and in these countries.<sup>42</sup> This contributes to strengthening the idea that the link between Provision and Participation in the MENA region is PP1 PP2 PP3 somewhat specific, and thus deserves particular attention.

As to the controls, we see that the higher the rurality, the lower the Participation in both MENA and OECD. This seems plausible as more rural countries are often less developed than more urban countries. People living in rural countries are more often worried than those living in urban countries about ensuring the livelihood of their families due to stronger financial constraints. This is generally a result of fewer job opportunities in rural areas compared to urban ones. Fighting for democracy and participation in society's decision making is usually not their highest priority and public authorities do not have any incentives to improve Participation. Against this backdrop, increases in rural population may then result in lower participation.

Human development is found to be negatively related to Participation both in MENA and OECD. For the case of MENA, this suggests that health, education, and standard of living, the components of the human development index, have somehow improved overall but at the expense of citizens' Participation. As to the OECD, as discussed previously, on average, this region's level of Participation is far from being qualified as "poor" as it includes mostly developed countries that are committed to democracy. Because Participation is somewhat already a reality in their economies, as they develop, these countries tend to rest on their laurels and focus their financing and efforts on other topical societal issues such as global warming
|_Ridership Data:_|||
|---|---|---|
|PAYING PASSENGERS||4.490.176|
|INTEGRATED PASSENGERS||1.460.155|
|OTHERS||419.173|
|TOTAL PASSENGERS<br>(Monthly<br>Average for 1995)||6.369.504|
|_N_° OF TRIPS TAKEN|92.525||
|LEVEL OF SERVICE|Average at peak hour=5,4 P<br>Average between peak<br>Passengers/m2|assangers/m<br>2<br>hour<br>=<br>3,5|
|MAXIMUM HEADWAY|20 Minutes||
|FLEET|46 Trolleybus<br>120 diesel buses<br>23 articulated diesel buses||
|TARIFF|R$ 1,00 (US$1=R$1.06)||

**Passengers Transported Monthly Average in 1995**

<!-- Start of picture text --> OTHERS<br>INTEGRATED 7%<br>23%<br>PAYING<br>70%<br><!-- End of picture text --> 13
arise from the use of different extraction methods does not substantially affect estimates. When researchers use publicly available data with obfuscated GPS information, they should feel confident that matching those coordinates with remote sensing data will not introduce measurement error into the analysis.

Our second hypothesis concerned whether the choice of metrics to measure precipitation and temperature are critical to the analysis. Here the concern is that the process economists use to choose one metric, say mean temperature, over another, say growing degree days, is _ad hoc_ and lacks the specificity necessary to accurately measure the weather that matters. Certain metrics may mismeasure the relevant meteorological event. If, for example, what matters to human capital development is the number of days with temperatures above a certain threshold, as in Garg et al. (2020), then mean daily temperature mismeasures the relevant event. The results presented in section 4.2 lead us to reject Hypothesis 2. Based on our heuristics, some weather metrics clearly perform better than others. For precipitation, mean daily rainfall, total seasonal rainfall, the number of rainy days in a growing season, and the share of days in the growing season that saw rain are all strongly correlated with outcomes. For temperature, mean, median, and variance of daily temperature are all frequently correlated with outcomes. Among these seven metrics, mean and total rainfall are highly correlated and could be substituted for each other. Similarly, rainy days and percentage of rainy days are highly correlated, as is mean and median daily temperature. One could substitute these metrics for each other without appreciable differences in results.

Hypothesis 3 considered whether remote sensing products mismeasured the objective facts regarding the volume of precipitation and the temperature in a given location on a given day. The overwhelming evidence presented in section 4.3 is that some products do, in fact, mismeasure the weather, though there is general agreement among several products. Specifically, MERRA-2 appears to suffer from classical measurement error, producing noisy data that results in rainfall metrics frequently being uncorrelated with
and paid labor income for all adults increase by 5% (p-value 0.684) and 8% (p-value 0.389), respectively.

Increases in revenues from livestock come mostly from an increase in livestock sales of USD 32 PPP (USD 9 nominal, p-value 0.002) compared to the control group, followed by increases in the value of milk produced by USD 23 PPP (USD 6 nominal, p-value < 0.0005), and yogurt by USD 7 PPP (USD 2 nominal, p-value < 0.0005) (Table A6 in the <u>Online Appendix). Since</u> these figures reflect the revenues during the four weeks preceding the follow-up survey, our measures of income and revenues may miss long-term cycles and important smoothing dynamics of consumption. However, these results indicate that livestock sales are an important source of income. To what extent reproduction of the livestock vs. decrease in the value of the assets due to liquidation for consumption occurs is an important question to assess the sustainability of these impacts in the longer term.

# Psychological Well-Being

Table 6 shows the impact of the program on the psychological well-being of the primary woman and man. The treatment effects on both indices are statistically significant and large, both in absolute terms and compared to other programs. The index increases by 0.58 SD (FWER-corrected p-value < 0.0005) for the primary woman and 0.26 SD (FWER-corrected p- value 0.010) for the primary man. An important difference with other studies stems from the use of a more comprehensive set of tools to measure psychological well-being. We use an index including six measures: five subjective indicators and one objective measure. The subjective measures include self-reported life satisfaction (WVS), self-esteem, depression (CES-D), self-reported happiness (WVS), and stress (Cohen). The objective measure is salivary cortisol. Other studies of TUP programs typically measure well-being through a smaller set of indicators. Table 6 shows the breakdown of
to contribute to this growing corpus of work by formally developing and testing the implications of a model of the political economy of public health resource allocation. Specifically, we test: (1) whether the agendas of stakeholders do diverge significantly along efficiency and equity dimensions as the _generic political economy literature_ would anticipate; and (2) given the substantive assumptions of the governance literature, how increased health litigation is perceived to affect the welfare of different stakeholder groups. These empirical implications, of the model, are tested using data collected from key healthcare stakeholders in Uruguay. This research agenda is realized via the first section. The next section, Section II, provides a brief literature review- thereby, providing a rationale for modeling and critically evaluating, via empirical hypothesis testing, the political economy of public 2
# **Regional Export Demand with Market Power:** Ei =K,/[Pi(1+Q1)]

where E; is the quantity of Cameroonian exports demanded in the regional market, Pi is the price received by exporters from Cameroon, **t;** is the ad valorem tariff rate imposed on sector i exports from Cameroon in the region, **7ci** the elasticity of demand for sector i exports from Cameroon in CEMAC, and K; is a constan **t** hat varies by sector. Implementation of the CEMAC arrangements implies that the tariff rate applied against Cameroonian exports will be reduced (see below for the data details), thereby shifting demand for Cameroonian exports in CEMAC out and to the right.

# **Tariff Rates Chosen in the Model**

In table 3 we present the tariff rates that we employ in the benchmark equilibrium and the policy counterfactuals. The structure of the import tariff rates was obtained from legal tariff rates, but we adjusted the legal tariff rates to reflect the actual collected rates as follows.

For the benchmark equilibrium, we employed the estimates of Semen (1988) to obtain the structure of legal tariffs rates that Cameroon applied on intermediate and consumption goods imported from the rest of the world; Semen shows that both for both Cameroon and its partners in UDEAC these rates followed closely the common external tariff of UDEAC. For legal tariff rates on intermediates and consumption goods imported from the region, we employed results from both Bela (1992) and unpublished IMF estimates. These studies combined gave us the structure of tariffs, intermediate versus consumption goods and regional versus rest of world.

Due to a large number of exemptions, however, the actual coliected duties were considerably less than what is implied by the legal rates. Based on data we received from the Ministry of Finance

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urban area, having fewer than three children, and having greater educational attainment have a particularly strong and positive association with economic welfare within countries.

The main findings on the nature of poverty are generally robust to a variety of methods. The share that is rural seems to vary little regardless of the lineup method or sample used. Furthermore, calculations based on South Asian data suggest that the share of the poor in rural areas would remain high even if welfare aggregates were spatially deflated in all countries. On the other hand, the shares of the poor that are young and less educated, and working in agriculture are mildly sensitive to how the welfare aggregates for each country are lined up to 2013, with differences of one to two percentage points. Therefore, further research could usefully document in detail the exact procedure used to line up the estimates and explore whether lining up improves the accuracy of profiles. As with all household survey data, there are missing values because information is occasionally not reported or processed. Because patterns of missing values vary across different variables, restricting the analysis to a common subsample would distort the key findings.

This study is a first step towards exploiting the World Bank’s unique inventory of household survey data to better understand the poor’s living conditions, earning capacity, and economic constraints at a large scale. The database can also help fill in other important knowledge gaps on global poverty. These include a more detailed look at the relationship between labor market 31
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- because many expenditure categories are covered, the level of d:tail is unsatisfactory, often, importnt variables such as price, fuel availability and end-use equipment are not included;

- typically, no time series data are generated by these exercises because they are undertaken infrequently and/or do not use the same methodology, including questions, for each iteration; and

- because these surveys mostly concentrate on cash purchases, collected fuels (wood, twigs, agricultural and animal residues) are not reflected in final consumption figures.

Still, there is room for improvement whereby t i- hehold energy module can be incorporated in the family budget survey to generate useful information for pi ning and implemenitation purposes An example<sup>of such</sup> a module, which was added to the 1987-88 Family Budget Survcy in the Yemen Arab Republic, is<sup>presented in</sup> Annex 1.

# Micro-survy

These data collection ex'rcises are aimed at understanding the social and microeconomic aspects<sup>of</sup> household energy demand in a limited geographical area. Generally, they can involve a sample of up to<sup>several</sup> hundred households, may cover several villages and could rely on re-surveying. They are attractive because: (a) micro-surveys are usually inexpensive; (b) because of their small sample size, they can be undertaken and analyzed relatively rapidly, and (c) because of their smali size and limited geographical focus, they are easily managed. On the negative side,

- their specific focus is also a limitation as one can rarely extrapolate results from the sample to the national, or even regional, population;

- in practice, they often don't measure such important characteristics as efficiency of end-use devices, the natural resource stock and income or expenditure level; and

- they are one-shot affairs which don't allow for comparison of results over time, especially regarding seasonality of fuel use.

So, micro-surveys are generally not appropriate for
and Health Survey (India IIPS, 2022), indicating that only around a third of households in India possess at least one mosquito net, with an estimated 8% having an insecticide-treated mosquito net (ITN). In the three study states, population-level estimates suggest that only one in three women and six in ten men have accessed the internet at some point. These statistics emphasize that our study and evaluated intervention reflect the results from a specific subgroup of the population, and do not generalize to individuals and households without access to the internet.

As anticipated, both covariates and pre-treatment outcomes vary among different types of dwellings. Annex Tables D5 and D6 demonstrate that households residing in solid dwellings exhibit greater economic advantages, such as higher levels of education, lower unemployment rates, and belonging to higher castes. Additionally, they tend to reside in closer proximity to urban centers with medical facilities and are less prone to experiencing malaria in the last 5 years and 2 weeks compared to those living in non/semi-solid dwellings. Although bed net ownership rates are comparable between the two groups, residents in solid dwellings are less inclined to use bed nets consistently. This could be attributed to their perception of lower malaria contraction risks. These differences emphasize the importance of having both types of dwellers equally represented in our sample, which allows us to explore potential effect heterogeneity.

# **5.2 Survey-based Results**

## **5.2.1 Preventative behaviors and response actions during the campaign**

Table 2 reports the results on sleeping under mosquito nets during the campaign, one of the main messages of the ads that received more budget. Columns (1-4) pertain to the respondent’s behavior, while columns (5-8) capture the behavior of the entire household. When considering the complete sample (of respondents that had at least one bed net), we note modest yet favorable impacts of the campaign on increased bed net utilization in columns (1-2) and (5-6). Individually, there is an approximate
# **References**

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<mark>from 1790 to 1840. See Allen and Gale (2000), Holmstrom and Tirole (1997) and Song and Thakor (2010) for theoretical contributions on the complementarity and co-evolution of banks and markets.</mark> However, this is not to say that financial structure is not important. Instead, the studies seem to suggest that since countries differ in their underlying institutions and follow different paths of development, there is great variation in the financial structure and not one optimal institutional structure fits all types of firms and economies. Lin (2010) outlines a New Structural Economics approach wherein there is an endogenously determined optimal financial structure at each stage of an economy„s development. <mark>Demirguc-Kunt, Feyen, and Levine (2011) revisit the bank versus markets debate using data on 72 countries from 1980 to 2008 to explore whether deviations from an optimal financial structure is associated with development. They conclude that different financial structures may be better at promoting economic activity at different stages of a country‟s economic development. Allen et al. (2011) provide a comprehensive historical review of financial structures in the US, UK, Germany and Japan and how they contributed to their development process. The experiences of these four countries which all had different but sophisticated financial systems suggest that a variety of financial structure can lead to higher growth.</mark> Moreover, financial structure also affects different firms differently. Demirguc-Kunt and Maksimovic (2002) suggest that at lower levels of financial development, firms‟ ability to obtain financing is affected in different ways by the two systems. A larger securities market is associated with better access of firms to long-term financing while banking development is more associated with availability of short-term financing. Morck, Yavuz, and Yeung (2010) find that in countries where banking systems are controlled by wealthy tycoons or families, there is less efficient capital allocation, more non-performing loans, more frequent banking crises, and slower income and productivity growth rates. Thus financial structure may have important implications