rafmacalaba/data-use-mentions-extended huggingface dataset:
Policy Research Working Paper 9465

# **Abstract**

This paper analyzes how local leaders make targeting decisions in the context of a public workfare program in the Lao People’s Democratic Republic. The study finds that village heads are progressive in their targeting, prioritizing the poorer households in their villages. The study benchmarks this decentralized selection to the common alternative proxy means test method and finds that village heads are at least as progressive as a proxy means test method approach. To illuminate what poverty-related information village heads could plausibly be incorporating into their internal selection decisions, the study designs and administers a set of exercises for village heads to rank villagers on land ownership, access to nutrition, and experience with recent shocks—indicators that are likely to differ in their observability to village heads and could plausibly be associated with need for public support. The study finds that village heads’ perceptions, as revealed through the ranking exercise, differ substantially from actual levels reported in surveys of the villagers themselves. The study then uses a data-driven machine learning approach to identify the predictors of village head selection. It concludes that village heads rely on a combination of easily observable household characteristics, forming a holistic impression of household welfare, rather than specific indicators like actual land ownership, nutrition, or economic shocks.

This paper is a product of the Gender Innovation Lab and the Office of the Chief Economist, East Asia and the Pacific Region. 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 eperova@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
with other studies, we find that the more generous safety net induces negative wealth effects on the labor supply of men and women at older ages. Contrary to other studies that model reform changes at the individual level, our simulations show that household structure is an important determinant of pension policy reform responses. Even though many of the reform features were targeted at women, we find that men’s responses are sometimes greater than those of women, as men respond to the wealth effect of an increase in pension benefits accruing to their wives. In addition, household-level

> 4The longitudinal household survey data were collected by the Microdata Center under the supervision of David Bravo and the administrative data come from Chile’s _Superintendencia de Pensiones_ .

2
040||0.033|0.004||0.011|
|Country Dummies|no||no|yes||yes|
|N||45,839|||45,839||
|r2_a||0.002|||0.155||

Standard errors are clustered at the city level.

# 4. Pollution Effects on Firm Productivity

We now move our focus to the second question: is firm performance affected by air pollution? Following a similar strategy, we estimate the effect of PM 2.5 on employment growth and labor productivity growth. As mentioned earlier, because location data are missing for some of the firms, we restrict our sample to only those firms for which we have location and PM 2.5 concentration values. Additionally, data on PM 2.5 from van Donkelaar have better coverage than PM 2.5 obtained from NASA directly, so we opt to use the first one.

We explore different model specifications and present the results of the model that better fits the data. Globally, pollution seems to be associated with employment growth positively and

> 12 This exercise is only do-able for manufacturing firms, and we thus only use the manufacturing firms.

17
<!-- Start of picture text --> Lebanon: Spactral Density Function of Real Credit<br>0.00 0.10 0.20 0.30 0.40 0.50<br>Frequency<br>Evaluated at the natural frequencies<br>West Bank and Gaza: Spactral Density Function of Real Credit<br>0.00 0.10 0.20 0.30 0.40 0.50<br>Frequency<br>Evaluated at the natural frequencies<br>Syria: Spactral Density Function of Real Credit<br>0.00 0.10 0.20 0.30 0.40 0.50<br>Frequency<br>Evaluated at the natural frequencies<br>6<br>6.00<br>4<br>4.00<br>2<br>2.00<br>0<br>0.00<br>log Periodogram -2<br>-2.00<br>-4<br>-4.00<br>-6<br>-6.00<br>6<br>6.00<br>4<br>4.00<br>2<br>2.00<br>0<br>0.00<br>log Periodogram-2<br>-2.00<br>-4<br>-4.00<br>-6<br>-6.00<br>6<br>6.00<br>4<br>4.00<br>2<br>2.00<br>0<br>0.00<br>log Periodogram -2<br>-2.00<br>-4<br>-4.00<br>-6<br>-6.00<br><!-- End of
example, research has found that effective enfranchisement of poor voters has direct consequences for the delivery of health services and improved health outcomes, while poor voters’ disenfranchisement, through vote buying, has the opposite effects (Fujiwara, 2015 and Khemani, 2015). But these ideas about the role of politics and exploration of its policy implications has not happened through RCTs for the simple reason that the suggested interventions are more complicated than what is feasible in most RCTs. The interventions involve not only changes in contract design (level of wages, whether high powered or not) which other RCTs have undertaken (Dal Bo et al, 2013; Ashraf et al, 2014; Ashraf et al, 2015), but crucially, these contract changes need to be combined with political and bureaucratic reforms if the insights of economic theory are to be fully tested and exploited. Collaboration with policy-makers who are willing to experiment with policy is hard enough for most RCTs, and compounded in this case by the complexity and potential sensitivity of targeting bureaucratic management culture and political contestation.

In the absence of opportunity to directly undertake a policy experiment suggested by economic theory, and evaluate its impact to the standards of econometric rigor of other RCTs, the research in Bihar we report on in this paper gathered descriptive data, through rich surveys using innovative modules to measure the variables that economic theory suggests are important (such as, intrinsic motivation, and peer norms). This survey provides evidence of the mis-match between actual policy practice and the insights from economic theory and offers ideas to policy makers to adopt a different approach to strengthening health systems using the current crisis as an opportunity.

# **3 Description of the survey in Bihar, India**

The survey was undertaken in the state of Bihar in India between November 2018 and March 2019.<sup>7</sup> Data were collected across different layers of government jurisdictions within the state–districts, blocks and village governments, known as Gram Panchayats (GPs)–and across different types of
. World Inequality Lab.

- Alvaredo, Facundo, Bourguignon, Franc ̧ois, Ferreira, Francisco H. G., & Lustig, Nora. 2023 (Oct.). _Seventy-five Years of Measuring Income Inequality in Latin America_ . Tech. rept. Inter-American Development Bank.

- Assouad, Lydia, Chancel, Lucas, & Morgan, Marc. 2018. Extreme Inequality: Evidence from Brazil, India, the Middle East, and South Africa. _AEA Papers and Proceedings_ , **108** (May), 119–123.

- Atkinson, Anthony, Casarico, Alessandra, & Voitchovsky, Sarah. 2018. Top incomes and the gender divide. _The Journal of Economic Inequality_ , **16** (2), 225–256. Publisher: Springer.

- Auten, Gerald, & Splinter, David. 2023. Income Inequality in the United States: Using Tax Data to Measure Long-Term Trends. _Journal of Political Economy_ , Nov. Publisher: The University of Chicago Press.

21
across the countries in our sample, the median outpatient caseload per facility is 25.9 patients per day. As many facilities have multiple providers, if we assume that the patient load in the facility is evenly distributed across available providers, the mean daily caseload per _provider_ was 15.7 and the median was 10.9 across our full sample, ranging from 1.2 in Nigeria to 20.7 in Malawi. This mean is remarkably close to the 15.5 patients per day that emerged from our crude calculation above, and it indicates that the caseloads of PHC providers are consistent with one hour and forty minutes of daily consultations across the countries in our sample.

To understand why patients still report long queues even though providers have substantial excess capacity, we then examine the _variation_ in caseloads across facilities. Across the countries in our sample, the 20% busiest providers saw between 40%–67% of all outpatients, which implies that most patients (by definition) visited facilities with relatively busy providers. The median _patient_ in our sample visited a provider who saw 25.7 patients each day, ranging from 6.6 in Nigeria to 64.6 in Malawi. These are substantially higher caseloads, and simulations using stochastic queuing theory show that even mild “clumping” of patients at any time of the day – or day of the week – would lead to long queues and waits at these higher caseloads. We conclude that official statistics and facility survey data are correct in indicating concurring patterns of excess capacity for providers. Simultaneously, the variation across facilities in the survey data implies that the characteristic patient experience is instead one of crowds and queues.

With this new perspective in hand, we turn to a second issue of human resource management for these PHC systems. We consider, as a starting point, that the unequal caseloads we observe could reflect efficient allocation mechanisms if the busier providers were also those of higher quality. Our second aim in this article is then to investigate whether caseloads were strongly positively
UCL) - CRED, D. Guha-Sapir - www.emdat.be, Brussels, Belgium,” www.emdat.be 2017.

- Garza-Gil, M. Dolores, Albino Prada-Blanco, and M. Xos Vzquez-Rodrguez, “Estimating the short-term economic damages from the Prestige oil spill in the Galician fisheries and tourism,” _Ecological Economics_ , 2006, _58_ (4), 842 – 849.

- General Statistics Office, “Labor Force Survey 2016,” Technical Report, Government of Vietnam 2016.

- , “Statistical Yearbook of Vietnam, 2016,” Technical Report, General Statistics Office of Vietnam 2016.

- Gray, Clark and Valerie Mueller, “Drought and Population Mobility in Rural Ethiopia,” _World Development_ , 2012, _40_ (1), 134–145.

- Groger, Andr and Yanos Zylberberg, “Internal Labor Migration as a Shock Coping Strategy: Evidence from a Typhoon,” _American Economic Journal: Applied Economics_ , April 2016, _8_ (2), 123–153.

- Liu, Xin, Ruolin Meng, Qianguo Xing, Mingjing Lou, Hui Chao, and Lei Bing, “Assessing oil spill risk in the Chinese Bohai Sea: A case study for both ship and platform related oil spills,” _Ocean & Coastal Management_ , 2015, _108_ , 140 – 146. Estuaries and Coastal Areas in Times of Intense Change.

- Neidell, Matthew J., “Air pollution, health, and socio-economic status: the effect of outdoor air quality on childhood asthma,” _Journal of Health Economics_ , 2004, _23_ (6), 1209 – 1236.

- Noy, Ilan, “The macroeconomic consequences of disasters,” _Journal of Development Economics_ , March 2009, _88_ (2), 221–231.

- Page, Lionel, David A. Savage, and Benno Torgler, “Variation in risk seeking behaviour following large losses: A natural experiment,” _European Economic Review_ , 2014, _71_ (C), 121–131.

24
equilibrium were people is not satisfied with public education either when they use it and do not spend much on it (usually the poorer) or when they choose private schools but they are still paying for public education in the form of taxes (the middle and upper classes).

# **II.3 Health**

In the health sector, an ambitious set of reforms started in 2001 with the approval of the General Health Law (42-01) and the Establishment of the Dominican Republic Social Insurance System (87-01). These reforms are aimed at achieving universal health insurance, reducing the vulnerability of the poorer to financial shocks caused by out-of-pocket health expenditures. In order to achieve universal coverage, the law foresees three different modalities of social insurance: a fully subsidized regime, targeted at around 3.4 million of the poorest<sup>9</sup> , a contributory employer-employee regime and a partially subsidized regime. The Secretary of State for Public Health and Social Assistance has established a series of arrangements with regional health care providers in order to count with a decentralized network. Financing, risk management, service acquisition and service provision functions have been separated in this redesigned system (Montenegro, 2010).

> 9 This group was identified using SIUBEN beneficiary database. SIUBEN’s survey agreed with the World Bank (2006) poverty assessment in the size of the poorer (34% of the population by then). At the moment, it is estimated that the number of beneficiaries of the fully subsidized regime is just around 20% of the total population.

[14]
national statistical offices with differing degrees of expertise. Taken together, these facts suggest that we should expect that any empirical analysis using these measures will involve a relatively low signal-to-noise ratio.

Our focus here is on designing a prototype drought-contingent targeting system, rather than providing a systematic analysis of the causes of stunting.<sup>12</sup> However, it is worth noting that other studies have found that stunting is not responsive to single-sector interventions.<sup>13</sup> Multi-sectoral approaches that address food availability, health and sanitation _are_ associated with reductions in stunting rates (Skoufias et al. (2019)).

In this paper, we view the prevalence of stunting as a time-varying, but lagged, sig-

- 8We use a harmonized version of the DHS Surveys constructed by Boyle et al. (2019).

> 9In the case of stunting, this entails subtracting the WHO median height from the child’s height and then dividing by the WHO standard deviation — all with reference to a particular age.

- 10See Assaf et al. (2015) for an analysis of measurement challenges and data quality concerns.

- 11If ethnicity _does_ have a role to play in influencing anthropometrics, policies that target stunted children will have hidden biases that favor some ethnicities over others.

- 12Our results speak to concerns raised by Deaton and Cartwright (2018) regarding the causal attribution of outcomes associated with interventions that are randomly implemented at different locations. We show that weather shocks are frequent and impact stunting. Therefore, shocks that occur _after_ randomization may result in the misattribution of the impacts of interventions that aim to reduce child malnourishment.

- 13For example, using sub-national data from 59 countries, Headey and Palloni (2019) found no impact of water, sanitation and hygiene variables on stunting.

6
SOEs under their oversight (Huang et al. 2017). The main incentives of the local governments were to get rid of loss-making SOEs to unburden the governments. Under the central government’s mandate to completely restructure, most SOEs, invariably possessing valuable urban land, could be, and had been, sold. We can thus use, with details to be shown later, rulebased political incentives of local politicians as the instrumental variable for identifying the privatization effects.

Using a large data set that covers _all_ Chinese industrial SOEs from 1998 to 2009, we first document that the rule-based promotion incentives of local politicians (i.e., at the prefecturallevel city) affected their privatization decisions. As a result of the Chinese Communist Party’s bureaucratic rule that limited promoting local politicians within a specific age range, their promotion probability drops sharply and robustly when reaching age 58. Indeed, using a regression discontinuity framework, we find that local politicians become reluctant to privatize SOEs under their oversight when they get sufficiently “old” and the underlying political benefits disappear. To exclude the possibility that other unknown local economic factors might drive the result, we examine the privatization likelihood of SOEs under the oversight of the provincial or the central government in the same region, and we do not find it related to the local politician’s age.

We next study the impact of privatization on firm productivity. First, without dealing with time-varying selectivity, we use ordinary least squares, fixed-effects and the firm random growth specifications. We find that privatization in China is associated with productivity improvements within the range of effects found in the earlier literature on Eastern European and CIS countries that were formally affiliated with the Soviet Union, with the magnitude on the high end of the range. Since privatization is not a random event, we then address the timevarying selectivity of privatizations with the dummy variable of the local politician’s age exceeding 58. Results from the instrumental variable estimation show that privatizations lead to dramatic increases in firms’ productivity by more than 170
e.g. it’s OK to spread rumors to defend those you care about or it’s no big deal to pass someone else’s work as your own).

> 9All indices are created using Inverse Covariance Weighting (ICW) as described in Michael Anderson. "Multiple Inference and Gender Differences in the Effects of Early Intervention: A Reevaluation of the Abecedarian, Perry Preschool and Early Training Projects. Journal of the American Statistical Association. December 2008, Vol. 103, No. 484. This is similar to Principal Component Analysis (PCA), but overweights variables that provide "new information" (i.e. have lower covariance with other variables). All underlying data is coded such that higher value of indices are "more positive" outcomes.

17
<!-- Start of picture text --> 600<br>Large Economies<br>Singapore<br>High-Perfomers<br>Low-Performers<br>Vietnam Cuba Poland<br>500<br>Bulgaria<br>China United Arab Emirates<br>Mexico<br>Brazil<br>400<br>Qatar<br>India Kuwait<br>South Africa<br>300<br>Ghana<br>Nigeria<br>200<br>6 8 10 12<br>log GDP per capita<br>SUPPLEMENT FIGURE VII<br>HLO<br><!-- End of picture text --> Average Learning (2000-2017) versus 2015 GDP per capita _Notes:_ Average learning is calculated across subjects and schooling levels over the given time period. _Source:_ GDP per capita estimates are from World Bank national accounts data; learning outcomes are from our database.

# III. DATA DESCRIPTION SUPPLEMENT

# _A. International Standardized Achievement Tests (ISATs)_

In the mid-1990s, there was an emergence of standardized, psychometrically robust and relatively consistent ISATs. Below we describe the major ISATs we use in this database.

_TIMSS_ **.** The Trends in International Mathematics and Science Study (TIMSS) is conducted by the IEA. Five TIMSS rounds have been held to date in Math and Science subjects covering grades 4 and 8. The first, conducted in 1995, covered 45 national educational systems and three groups of students.<sup>11</sup> The second round covered 38 educational systems in 1999, examining pupils from secondary education (grade 8). The third round covered 50 educational systems in 2003, focusing

> 11 IEA assessments define populations relative to specific grades, while PISA assessments focus on the age of pupils. In IEA studies, three different groups of pupils were generally assessed: pupils from grade 4, grade 8 and from the last grade of secondary education. In 1995, two adjacent grades were tested
In equation (4), β=β2 and _xi_ ( γ ) = _xi d i_ ( γ ) , and _d i_ ( γ ) = { _qi_ ≤ γ} is a dummy variable. The first step is to identify the threshold value γ and the other coefficients. This is done by using the algorithm provided by Hansen (2000), which searches through the values of γ until the splitting value is found (this is the value of γ which minimizes the concentrated sum of squared errors based on an OLS regression).

Most of the _xi_ variables included in our threshold regression are typical variables used in gravity models—probably the most robust empirical relationship explaining the volume of bilateral trade flows. To identify the threshold value in the preferential margin we estimate to following equation: In equation (5), _Yi_ jk is the utilization rate of Cotonou preferences for product _k_ , in other words the percentage of country _i's_ imports of product k from country _j_ which requested preferential access. The data originates from Eurostat and contains import data at 8-digit level for the year 2001. _Dutydifference_ k is the difference between MFN and preferential tariffs for product k. This is the variable ( _qi_ ) for which we identify a threshold value.

As a proxy for the trading countries' _income_ and _size_ the GDP ( _GDPi_ is the level of income in country _i)_ and population ( _POPi_ is the population in country _i_ ) of both partner countries are included in the regression. GDP and population data are taken from the World Development Indicators database. _Dij_ is the distance between the partner countries and is a proxy for _trading costs_ . Previous empirical results showed that distance had an important negative impact on trade. The further away the trading partners are located from each other the higher the costs will be for transporting the products. Distance is expected to have a significant and negative impact on preferential trade. The distance data originates from the CEPII distance database and calculated following the great circle formula, which uses latitudes and longitudes
developing countries in agriculture account for only 3 percent of world rice consumption. For wheat, where these countries account for 27 percent of world consumption, the benefit is likely somewhat greater. However, it is clear from these trade shares that the key trade policy influence on the stability of world markets is what happens in developing countries.

Within the group of developing countries, there are also very substantial differences in the extent of price insulation. As shown in Figure 4, it appears that domestic price rises for wheat in the 2006-8 period were restrained much more in Asia than in other world regions. This suggests that—in contrast with the case considered in Figures 1 and 2—price insulating policies may not have been completely ineffective in stabilizing prices in all regions. Rather, their effect may have been to reduce the volatility of domestic prices in some regions, while increasing this volatility in others.

Are rice and wheat representative of other farm products in terms of insulating behavior by governments? There is no global database for all farm products for the most recent spike period, but there is for the upward spike of 1974-6 and the slump of 1984-8. Anderson and Nelgen (2010a) decompose the nominal rate of assistance (NRA) estimates, for the overall agricultural sector of all 75 countries in the Anderson and Valenzuela (2008) database, into the various border and domestic measures for developing and high-income countries. The annual estimates summarized for the upward spike period of 1972-76, and the downward spike period of 1984-8, are reported in Table 2.

In both of these periods, export restrictions were the dominant instrument for developing countries; they became more and then less important in the upward spike period of 1972-76, and conversely in the downward spike period of 1984-88. In highincome countries there were virtually no taxes or other restrictions on exports, but export subsidies followed the same path as import tariffs over those spike periods: U- shaped during the upward spike, inverted U-shaped in the downward spike. Together these estimates suggest the experiences