rafmacalaba/data-use-mentions-extended huggingface dataset:
A straightforward regression framework is used to analyze the relative performance of the seven survey designs in relation to the benchmark module 8. For the specification with respect to consumption incidence, we have the following: where _M_ is a vector of indicators for module type. The individual diary, _m = 8_ , is the excluded category, and the constant ���� therefore represents the mean benchmark incidence. Regressions include survey cluster fixed effects and are estimated with ordinary least squares.<sup>11</sup> Earlier work has demonstrated that household characteristics interact with survey design in nontrivial ways to produce error and, so, may also interact in differential ways with respect to consumption incidence and value. An understanding of the presence of these interaction affects can also inform consumption survey design. An extended regression framework thus includes a household characteristic _X_ – for example the number of adult or child household members, household location, the educational attainment of the household head, or asset wealth – and interacts this characteristic with the survey module indicator, _M_ : In this specification, the coefficient of interest is ����, which relates how module effects on incidence reporting are mediated by the household characteristics.

The same two regression specifications given above are used to explore the survey design effects on the value of consumption (conditional on a positive value) by replacing the dependent variable with the consumption value and dropping all observations that report zero consumption for that specific food item.

The next section first explores consumption incidence and then consumption value. We then extend this analysis by relating module-specific reporting error for a particular food good to select characteristics of that good. It is possible for a survey design that minimizes error with respect to certain types of food goods to be less effective with other food types. Consequently, the analysis compares the design error as estimated above with respect to item-specific features such as consumption incidence (i.e. common or rare items), consumption value, the share of consumption from home production, the frequency of market
--|---|---|
|Jalanidhi-I|90|3,710|2001 to 2009|
|KWA-BM|44|395|2004 & 2005|
|Other CommunityManaged|66|750|1999 to 2010|
|**Total**|**200**|**4,855**||

## 4.2 _Data_

Data collection for the selected sample was undertaken using household surveys of beneficiaries, technical and financial audits of water schemes, and institutional assessment of BGs for the Jalanidhi and other community managed schemes. The following is a brief description of the data collection tools used in the study.

_Technical and Financial Audit:_ The technical audit was focused on assessing the current state of water supply infrastructure such as working of the pumps, condition of the reservoir, functioning of the water treatment plan, frequency of breakdowns, frequency of water quality testing, total daily supply of water with respect to the design criteria, water source reliability, quality, and household service level. The 9
||**Pooled**|**ELMPS**<br>**2012 in est.**|**ELMPS**<br>**2018 in est.**|**Economic**<br>**Census**|**Establishm**<br>**ent Census**|
|---|---|---|---|---|---|
||(0.239)|(0.805)|(1.360)|(0.321)|(0.026)|
|7|1.907***|2.162|2.875|1.976***|1.725***|
||(0.162)|(0.870)|(1.590)|(0.341)|(0.020)|
|8-17|2.426***|2.401**|1.931|2.780***|2.449***|
||(0.196)|(0.734)|(0.712)|(0.314)|(0.028)|
|18-27|3.190***|4.597***|1.299|4.899***|3.223***|
||(0.326)|(1.601)|(0.514)|(0.490)|(0.044)|
|28+|4.302***|4.414***|2.869*|5.045***|4.795***|
||(0.495)|(1.677)|(1.222)|(0
by<br>provinces|1,621<br>412|||
|STS<br>of which:|3,557|?|1,571,100|
|Teacher<br>training|1,028||558,200|
|SVS|8,070|?|2,295,700|
|Total Voc. and T|ech. Training|||4,606,800|
|Total Upper Sec.|Goa. Education||7,411,300|

*Source: Ministry of Labor and Personnel.

Other data from Statistical Yearbook of China, 1985.

- 13 -
Figure 3.1: _High government interference in the economy is compatible with high employment rate_ <!-- Start of picture text --> 70 rom<br>cze svn<br>60<br>ltulva<br>hun svk<br>pol geo<br>bgr mda<br>50<br>hrv<br>tur<br>40<br>2 4 6 8<br>Government interference index<br>Employment rate<br><!-- End of picture text --> Figure 3.2: _The reason is that public employment does not respond to the investment climate. Instead, if service employment is plotted against government interference, a clear negative relation is found._ <!-- Start of picture text --> 5 est<br>lva<br>cze kaz<br>hun bgr<br>svkltu<br>ukr<br>0 pol<br>hrv rom<br>geo<br>svn<br>mda<br>-5<br>2 4 6 8<br>Government interference index<br>sv emp. controlled for gdppc<br><!-- End of picture text --> 32
--> Although there is no perfect indicator of the overall quality of policy and institutions in developing countries, the World Bank’s annual Country Policy and Institutional Assessment (CPIA) provides a broadly consistent framework for assessing country performance on 16 items grouped in four clusters: economic management, structural policies, policies for social inclusion and equity, and public sector management and institutions. The score is from 1 (low) to 6 (high) for each policy that covers a wide range of issues.<sup>11</sup> The index focuses on policies and institutional arrangements--the key elements that are within the country’s control--rather than on actual outcomes (for example, growth rates) that are influenced by elements outside the country’s control. Over time, good policies and institutions are expected to lead to favorable growth and poverty reduction outcomes, notwithstanding possible yearly fluctuations caused by external factors.<sup>12</sup> Using the 1996 CPIA, the earliest index with comparable scale and criteria available,<sup>13</sup> suggests that countries starting with good policy and institutions tend to do better in the MDGs.

> 11 Issues include macroeconomic and fiscal policy, debt policy, trade, human development policy in education and health, gender equality, social protection, budgetary and financial management, and corruption in the public sector. 12 See World Bank (2009).

> 13 An earlier version of the CPIA goes back to 1970s but uses a different scale and criteria. For example, the assessment of governance issues was not included in the earlier CPIA.

13
Survey and Uganda’s 2011-12 National Panel Survey. It is not possible to determine whether a woman is pregnant at the time of measurement in the Tanzania survey.

**Table 2: Summary statistics for nutritional indicators using DHS**

||Underweight women|Stunted children|Wasted children|
|---|---|---|---|
|Benin|0.064|0.407|0.144|
|Burkina Faso|0.154|0.298|0.139|
|Burundi|0.160|0.516|0.051|
|Cameroon|0.068|0.279|0.050|
|Congo, Rep.|0.144|0.187|0.051|
|Côte d'Ivoire<br>Congo, Dem.|0.078|0.238|0.071|
|Rep.|0.144|0.366|0.072|
|Ethiopia|0.266|0.388|0.086|
|Gabon|0.074|0.131|0.032|
|Gambia|0.167|0.200|0.110|
|Ghana|0.061|0.134|0.053|
|Guinea|0.122|0.269|0.099|
|Kenya|0.122|0.293|0.058|
|Lesotho|0.058|0.302|0.030|
|Liberia|0.073|0.257|0.058|
|Malawi|0.087|0.413|0.038|
|Mali|0.114|0.337|0.119|
|Mozambique|0.086|0.371|0.049|
|Namibia|0.140|0.176|0.081|
|Niger|0.154|0.355|
unemployed. Indeed, self-employment in the EAP is quite extensive, ranging from 36 percent in the Philippines to 75 percent in PNG as a share of the labor force.<sup>24</sup> In middle-income countries such as those in the EAP, poorer workers are generally more likely to be selfemployed, while wealthier workers are more likely to work in salaried jobs (Fields 2019). Self-employment is relatively high in the agriculture sector and certain service sectors such as retail trade, which also had lower work stoppages (Figure 9, Panel A). Thus, looking solely at employment changes may understate the impact of the pandemic on inequality if poorer workers are less likely to report being out of work due to the nature of their employment.

Additionally, work stoppages only consider the extensive margin of employment impacts. Data from the World Bank’s Business Pulse Surveys suggest that firms have been more likely to reduce work hours, reduce wages, and/or grant paid or unpaid leave: Two-thirds of businesses in the sample made adjustments to their payroll, but only about one in five actually fired workers (Freund and Pesme, 2021). As a result, those who do not face job losses may still face reduced working hours and wages.<sup>25</sup> Income changes can thus provide a more accurate picture of the impact of the pandemic on inequality. Indeed, in all of the countries analyzed, the share of households that experienced labor income losses was larger than the share of respondents that experienced work stoppages. Moreover, in most countries, households were significantly more likely to experience reductions in business income than in wages (Figure 9, Panel B).

Figure 9. While the self-employed may be less likely to stop working, income losses from selfemployment were significantly larger than those from wage labor A. Self-employment and work stoppages B. Wage vs. Non-farm business income losses Note: Data from six countries are included: Indonesia, Lao PDR, Mongolia, Myanmar, the Philippines
# **D.1 Handbook**

The content of the handbook was developed through primary qualitative and quantitative assessment of best practices among local business peers. First, prior to the start of quantitative fieldwork, we conducted detailed qualitative interviews with a sample of 102 shop owners chosen from two comparable urban markets outside our study area. The goal of these semi-structured interviews was to understand the most common and successful local business practices from the perspective of business owners, and to familiarize ourselves with the various implementation processes, norms, and constraints to adoption. To this end, we asked a number of open ended questions in the format of a conversation, and responses were recorded and later transcribed.

The analysis of these interviews allowed us to identify the following five categories of locally relevant business practices: record-keeping, financial planning, stocking-up, marketing, and joint decision-making. In the next stage, these categories directly fed into the quantitative baseline survey, from which we were able to associate the contribution of within-category individual practices to profits, sales, and number of customers. Specifically, for each category we estimated linear regressions of profits, sales, and number of customers on individual practices and a set of firm-level controls. The findings from these quantitative assessments were then matched with the qualitative fieldwork to arrive at the final set of locally relevant best practices to be included in the handbook.

With this information and the help of a local NGO, we developed a handbook of best practices used by peers. The handbook consists of five chapters: keeping business records, calculating profits, making stock-up decisions, attracting customers, and cooperation in business decisions, in this order. Although there is no chapter exclusively on financial planning, practices such as reviewing financial performance, analyzing where there are areas for improvement, and comparing sales with targets are natural consequences of implementing the best practices suggested in the handbook. Appendix Table A10 lists all the practices measured in this formative stage of the study, and Appendix Table A11 presents a summary of the information on beliefs
SE<br>(Cutoff = 1|Spatial GMM<br>Est.<br>(Cutoff = 2)|Spatial GMM<br>SE<br>(Cutoff = 2)|
|---|---|---|---|---|
|Intercept|-.04565513|.17729723|-.0494362|.21368676|
|ln Teacher qualification in 1991|-.00177951|.00383909|-.00199813|.00412284|
|Years of Schooling in 1991|.06576312|.00830697|.06912613|.00973923|
|Total Rainfall|.00008265|.0000173|.00007853|.0000177|
|Government Accountability|.00246969|.02073262|.00032706|.01966279|
|Delta ln Employment|-.73485869|.14010873|-.74297255|.15258759|
|ln Transport Cost SP in 1995|-.05022805|.01231244|-.04537549|.01413209|
|ln Transport Cost Capital in 1995|-.04676843|.01599272|-.04803535|.01860846|
|Delta ln Transferences|.16973922|.07140593|.16184129|.08098298|
|Delta ln Market Potential|.64660937|.19555643|.60036469|.22895648|
|crit. fn. test of overid. restrictions|35.984318|35.984318|22.100483|22.100483|
-34 -

In order to generate the necessary parameters in the Mexican consumer's maximization problem we have assumed there to be a single domestic consumer, and have derived consumption weights from the aggregation of the original input-output matrix.<sup>26</sup> We did not directly estimate an elasticity of demand for leisure, but experimented with various values. The foreign consumer is represented by an export equation which determines the total U.S. dollar amount that he will spend on Mexican exports. This total is then divided into consumption on Mexican output of agriculture, manufacturing and petroleum with shares of 0.075, 0.531, and 0.394, respectively.27 The aggregate export equation was estimated by OLS using annual data for non-oil exports over the period 1950-1985 with the following results.

log E - -0.88 - 0.12 log RP + 0.12 log RP.1 - 0.22 log RP-2 + 1.75 log U (0.69) (-0.04) (0.31) (-0.64) (2.13)

- - 0.77 log U-1 - 0.88 log U-2 + 0.95 log E-1 (5.1) -(0.65) (-1.18) (14.05)

- R<sup>2</sup> - 0.99 H - Statistic - 1.48

- 26/ Consumption weights for domestic goods are derived from Matriz de Insumo-Producto Ahio (1978) (1983), Table 1, while the weights for imports came from the same source, Table 5.

- 27/ These shares are derived from Sistema de Cuentas Consolidades de la Nacion (1985), Table 69, where we have used 1982 shares in exports.
We also report the strength of shareholder and creditor rights from La Porta et al. (1998). The shareholder index is an average of five 0-1 indicators: the country allows shareholders to mail their proxy vote; shareholders are not required to deposit their shares prior to the General Shareholders' Meeting; cumulative voting is allowed; an oppressed minorities mechanism is in place; the minimum percentage of share capital that entitles a shareholder to call an Extraordinary Shareholders' Meeting is less than or equal to 10%. The creditor index is an average of four 0-1 indicators: whether the incumbent management remains in control of the company during reorganization or bankruptcy; whether the creditor is barred by "automatic stay" from taking collection action against the debtor's assets during the bankruptcy proceedings; and whether secured creditors have the first priority of claims to the debtor's assets. We expand on these data by including these rights for the four transition economies in our sample. We do not have creditor rights data for Venezuela.

Shareholder rights strongly relate to legal origin and vary from a low of 0 for Belgium to a high of _5_ for common law countries such as Canada, Hong Kong, India, and the United States. Creditor rights vary between 0 for several French and Germanic civil law countries (for example, China, France and the Philippines) to a high of 4 for some common law countries (for example, the United Kingdom, Pakistan and Singapore).

For the classification of countries by the relative importance of banks versus capital markets in their financial system, we use Demirguc-Kunt and Levine (1999). Using a number of indicators on the aggregate size, activity (turnover) and efficiency of a country's respective stock market and banking system, they classify countries as bank- or market-based. We expand on their classification for China and the transition economies 14
geospatial data sets within analyses of travel time to services or catchment modeling, key constraints of health care accessibility can be quantified (Cattaneo, Nelson, & McMenomy, 2021; Weiss et al., 2018, 2020).

A research agenda focused on assessing health care disparities could proceed by adapting the URCA or FEA approaches to health care. With 90 percent of the world population living either in urban areas or within one hour of an urban center, better understanding of the distinct challenges in access to quality health care faced by populations in urban and peri-urban areas as well as rural areas is required. For instance, in many situations, it may make more sense to think of the URCA or FEA as the relevant catchment area and the health care facilities contained within it as the health care system, rather than considering the catchment area of a single health care facility. Researchers may choose between the two global data sets depending on the focus of their analysis, with FEA data more geared to urban planning and URCAs having a better coverage of rural areas and towns with fewer than 50,000 people. The exhaustive geographic coverage of the URCA approach would allow researchers to associate health care gradients with administrative-level data or survey data suitable for assessing the contextual factors described above. This approach is similar, in principle, to the many applications of the RUCC in the United States in the area of health care (Cyr, Etchin, Guthrie, & Benneyan, 2019). The novelty of the URCA data set for RUCC-like applications is that data are available for any country in the world, and at a level of granularity that can be matched to any administrative level, as we illustrated with the example on poverty levels in Nigeria in Section 3.3. This would then make it possible to provide policy makers with holistic results that lead to more informed resource allocation decisions. It would also enable benchmarking across countries.

A further area of research stems from the scarcity of data characterizing specific health care services provided at known facility locations.
a part of the _Doing Business_ project, offers an expansive array of economic data in 183 countries, covering the period from 2003 to the present. The data cover various aspects of business regulations, including those relevant to financial sector development issues, such as contract enforcement and obtaining credit.

**<u>IMF’s access to finance database</u>** . The database aims to measure systematically access to and use of financial services systematically.  Following Beck, Demirgüç-Kunt, and Martinez Peria (2007), the database measures the reach of financial services by bank branch network, availability of automated teller machines, and by four key financial instruments: deposits, loans, debt securities issued, and insurance. The website contains annual data from about 140 respondents for the six-year period, including data for all G-20 countries.

**<u>The Global Financial Inclusion Index (Global Findex)</u>** is a new database of demand-side data on financial inclusion, documenting financial usage across gender, age, education, geographic regions and national income levels. The core set of indicators and subindicators of financial inclusion based on the Global Findex database include _Use of bank accounts_ (% of adults with an account at a formal financial institution, purpose of accounts, frequency of transactions; % of adults with an active account at a formal financial institution, mode of access), _Savings_ (% of adults who saved in the past 12 months using a formal financial institution, % of adults who saved in the past 12 months using an informal savings club or a person outside the family, % of adults who otherwise saved in the past 12 months), _Borrowing_ (% of adults who borrowed in the past 12 months from a formal financial institution, % of adults who borrowed in the past 12 months from informal sources, % of adults with an outstanding loan to purchase a home or an apartment), _Payments_ (% of adults who used a formal account to receive wages or government
Okiro, 2020; Gauvin _et al._ , 2021). However, to the best of our knowledge, this study is one of the few, particularly in the Sub-Saharan African context, that have used available spatially disaggregated data on clinical risk factors to map underlying risk of severe COVID-19 in a population. Understanding spatial variation in risk using spatial modeling has proved useful for a number of diseases including malaria (Weiss _et al._ , 2019), schistosomiasis (Sturrock _et al._ , 2013) , and HIV ((Dwyer-Lindgren _et al._ , 2019). In turn, clinical risk for severe COVID-19 is likely to differ across a country, so using a spatial approach has potential to be strategically useful for targeting a health policy response. Its application to severe COVID-19 risk factors is therefore applied here.
<!-- Start of picture text --> 0 .1 .2 .3 .4 .5<br>% of migrants in each occupation in 2005<br>.3<br>.2<br>.1<br>0<br>% of recently arrived migrants in each occupation (2018)<br><!-- End of picture text --> Source: Own elaboration based on the EU-LFS 2005 and EU-LFS 2018.

Note: Share of migrant workers in each occupation for each NUTS2 division of residence. For 2018, migrants are restricted to those recently arrived in the country (less than ten years) so there is no overlap with the migrants in the country in 2005.

38
of Credit Supply on Trade: Evidence from Matched Credit–Export Data,” Review of Economic Studies 82, 333-359.

- Rajan, R.G., and L. Zingales, 1998, “Financial Dependence and Growth,” American Economic Review 88(3), 559-86.

Rauch, J.E., 1999, “Networks versus Markets in International Trade,” Journal of International Economics 48, 7-35.

- Reinhart, C., and K. Rogoff, 2009, This Time Is Different: Eight Centuries of Financial Folly. Princeton University Press.

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- Varela, L., 2018, “Reallocation, Competition, and Productivity: Evidence from a Financial Liberalization Episode,” Review of Economic Studies 85, 1279-1313.

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of consumption data publicly available for India. The survey reports consumption expenditure values with a 30-day recall period<sup>11</sup> and consists of a sample of over 100,000 households spread across all Indian states. Survey estimates are representative at the district level. The poverty headcount rate at the $1.90 poverty line is 22.49 percent and the Gini coefficient is 35.71 using consumption per capita based on uniform recall period. We also use select moments derived from the leaked cumulative distribution function that is estimated from the 2017 NSS consumption expenditure survey round for robustness checks.

_Other official surveys_ : Despite there being no contemporaneous NSS and CPHS expenditure surveys, there are three official non-expenditure surveys that allow us to 9Vyas (2020) offers a detailed account of the execution challenges by the survey team until the first wave of 2015, especially related to inclusion of excess CEBs in the urban sample.

> 10CMIE makes an attempt to revisit households that are locked on the same day or sometimes the next day in villages. In urban areas, repeated re-visits are conducted spread over several days. If households are consistently locked or unoccupied over three waves, they are dropped from the panel.

> 11We continue the existing practice of measuring poverty and inequality from older NSS rounds based on the uniform recall period (URP)

6