rafmacalaba/data-use-mentions-extended huggingface dataset:
Among these different measures of village health service delivery, while two are more direct measures of municipal actions (placement of health workers and projects), the third plays the role of an important summary measure of service delivery performance—percentage of children characterized as being severely below normal weight. This measure can be particularly helpful in discerning the equilibrium policy consequences of clientelism. Other work has shown that even primary health services can be subject to clientelist targeting (Chen and Cammett, 2012; Nichter, 2011). That is, it is difficult to find a measure of broadly delivered services that are not subject to the _quid pro quo_ of clientelism. The data on child health outcomes that are available in the Philippines are particularly helpful in this regard, serving as a measure of government performance in delivering broad welfare to its most vulnerable citizens.

In different specifications, the vector Wijkcontains relevant characteristics of the barangay in which the household resides: poverty, population, location (distance from centro), and quality of roads. The survey team recorded direct-observation data on the quality of barangay roads. The percentage of household respondents reporting participation in bayanihan activities is used as a barangay-level measure of social capital. All of these variables were used in the previous section to examine correlation with vote buying; none were robustly correlated with vote buying.

The vector Zjk across different specifications contains municipal political variables that might be correlated with health services in their own right, or be mediating the correlation with vote buying: whether key informants indicate that the mayor’s family is a major landowner or employer of labor; whether a political clan has been entrenched in power; other available measures of electoral competition such as number of candidates and the margin of victory. The vector Zjkalso includes indicators of municipal fiscal capacity—the share of own revenues (or alternately, the share of transfers from above), and the total per capita revenues.

The following specification is estimated to assess the correlation of vote buying measured at the municipal-level (percentage of household respondents in a
Finally, Table 2 shows individuals' effective use of parental leave up to nine months after the intervention. Parental leave take-up is higher among women for all treatment arms compared to men. There are strong differences by experiment, and the percentage of both men and women that made use of the parental leave program is much higher in Experiment 2. That can be explained by the fact that this sub-sample is composed of individuals that are already parents. Moreover, the demand for parental leave is slightly higher in the treated group in Experiment 1 for both men and women, and in Experiment 2 among men.

Table 2. Medium-term effective use of parental leave by treatment arm and sex

|**Experiment**|**Intervention**||**Men**|**Wo**|**men**|
|---|---|---|---|---|---|
|1|Control|0|0,0%|4|1%|
||Information|1|0,4%|8|2,4%|
||Information|1|1,1%|177|57,1%|
|2|Testimony|3|2,8%|186|58,9%|
||Planning|7|6,7%|175|56,1%|

Notes: The table shows individuals' effective use of parental leave between 1st September 2021 and 7th June 2022 for each treatment arm and sex. The estimation sample consists of 1,221 individuals in experiment 1 (554 men and 667 women), and 1,242 in experiment 2 (304 men and 938 women). Data includes all surveyed individuals. Source: Postintervention survey.

# _3.6. Empirical strategy_

To investigate the effects of providing information through a text message campaign, we estimate the following equation separately for men and women: where yig is the outcome
The control group is not completely without publicly provided health insurance. While those not in NHIS must pay fees at public healthcare facilities, those fees only have to cover supplies, maintenance, medicines, and diagnostic costs. Capital expenditures and, importantly, staff salaries are covered by the general government budget regardless of a user’s NHIS affiliation. While not called health insurance, this support to public healthcare facilities does function like insurance: General revenue is collected from all taxpayers to provide benefits to those who draw unfortunate health outcomes. Our comparison estimates the financial insurance value of NHIS relative to this “reduced insurance” state, not to no insurance at all.

The data we need from treatment and control groups are more detailed than those used in a typical evaluation in that we need to compare full distributions of OOP healthcare expenditures, not just their means. We create these distributions from the observed distribution of OOP healthcare expenditures for treatment and control groups, assuming that the cross-person distribution reflects each individual’s _ex ante_ distribution of possible expenditures.

Given these OOP healthcare-expenditure distributions for those with and without NHIS membership, we then calculate the risk premium associated with each distribution for each person in the sample using a stylized constant relative risk aversion (CRRA) utility function. The difference in those risk premiums is our estimate of the financial insurance value of NHIS membership.

The data come from the Ghana Living Standards Survey (GLSS) 2016/17, fielded between October 2016 and September 2017. GLSS 2016/17 is the latest available round of the national household sample survey administered by Ghana’s statistical agency (GSS 2019). The survey collected information on household expenditures, including expenditures for healthcare for each person in the household. Our data, then, are individual level for each person in the survey, with 58,844 people considered in all.

The remainder of the paper is organized as follows. Section 2 provides background information on government healthcare financing and spending in Ghana and for NHIS. Sections 3 and 4 describe how
investment. Rampant corruption mostly goes along with weak incentives for firms to compete and hence to lower productivity growth. We can think of numerous other examples, but the point remains; the question of relative impact of reforms in one dimension against another is still very much left unanswered.

A large part of the problem is the inability of empirical macro-research to converge on methods and techniques that can attribute causal effects of interventions on outcomes. Traditionally, OLS regression methods have been used on country cross-section data to study the links between macro policy/governance interventions and outcome variables. These methods have been criticized for the lack of accuracy emanating from problems of omitted variable bias and endogeneity, model uncertainty and heterogeneity. Researchers have attempted to solve some of these problems by using instrumental variables approach, for example Acemoglu et al. (2001). These studies are important steps towards estimating causal inference in cross-country studies and yet problems remain. Strong external instruments are hard to find, and even if they exist, the effect obtained from such regressions are limited to the variation that is affected by the instrument. These problems make the instrumental variables approach limited in its ability to evaluate macro interventions. This has led some researchers to use dynamic panel data methods, which account for endogeneity issues and yet other problems remain, such as the instability of results from cross-country regressions when variables, time periods and countries in the data change.

Our goal in this paper is not to attempt to resolve the two aforementioned questions in their entirety. Such an endeavor requires a much larger and longer research agenda. We merely attempt to identify specific cases of reforms in the disparate dimensions, ranging from macroeconomic and debt dynamics to governance reforms in the last decade, and attempt to assess their impact on development indicators such as economic growth. We do this by using recently developed methods of inference, which help us attribute with larger certainty the impact on outcome variables to the interventions themselves. By selecting case studies where changes in one dimension were not accompanied by changes in other dimensions
include an asset index based on principal component analysis as suggested by Filmer and Pritchett (2001). While these indices do well in describing the relative wealth ranking within a country, asset quintiles are hard to compare across countries with highly heterogeneous income and asset levels. We thus chose to directly control for a set of durable assets available in all surveys.<sup>12</sup> To avoid potential

> 12 Other potentially important control variables to limit omitted variable bias are indicators related to health preferences, such as the vaccination status of the child and whether the child was breastfed. The problem with vaccination and breastfeeding in cross-sectional studies is reverse causality: children who die at a very young age will never be vaccinated or breastfed. We could use the vaccination and breastfeeding status of living siblings to approximate or instrument the vaccination and breastfeeding status of dead children. The validity of such an approach is however, debatable, and the improvements achievable in the face of the resulting sample restrictions (identification can only be reached in households with at least two children) are uncertain.

12
<br>Information|d|||||
|4 cylinder<br>cars<br>|5,683.8<br>|1,265.4<br>4.49<br> <br>|16,099.5<br>|3,584.2<br>|4.49<br>|
|6& 8 cylinder<br>cars|3,602.7<br>--------------------------|718.5<br>5.01<br>----------------------------|221,676.9|44,212.1|5.01|
|Passengercars|9,286.5|1,983.9<br>4.68|223,776.4|47,796.3|4.97|

Source: see text.

## **TABLE** A.6

# Gross Value of Output and PPPs for Passenger Cars, Mexico (1975)/USA (1977)

|Me|xico(197|5)|USA|(1977)||
|---|---|---|---|---|---|
|million<br>1975<br>pesos|million<br>1977<br>US**$**|PPP<br>Ps./US$|million<br> 1975<br>pesos|million<br>1977<br>US S|<br>PPP<br>Ps./US$|
|Match using Census Data<br>only (without model<br>differentiation)<br>Passenger<br>
**Table** 7: **Number of phones due and installed by December 31, 1999**

|**Year**|**Phones due**|**Phones installed**|**Percentage installed**|
|---|---|---|---|
|**1997**|**265**|**265**|**100**|
|**1998**|**1,551**|**1,436**|**92,6**|
|**1999**|2,574|**2,350**|**91.3**|
|**2000**|**1,078**|**211**|**19,6**|
|**2001**|**448**|||
|**Total**|**5,916**|**4,262**|**72,0**|

Source: Memoria 1999, Fondo de Desarrollo para las Telecomunicaciones, Memoria 1999, Subtel.

A second problem has been the quality of the service - particularly its reliability. The successful bidder takes on the commitment to maintain the public phone for ten years, which is not a minor issue since some of the phones are in remote areas, and maintenance and billing costs are quite high. There are indications that service quality, especially among phones located in isolated areas, is not always the best: hence the need to monitor service quality, especially its continuity, in order to guarantee fulfillment of the standards established in the regulations. One way of doing this would be through user surveys. Local authorities are closer to the subsidy beneficiaries and so in the best position to carry out such surveys; municipalities should therefore be active in monitoring public phones
as the lower interest rates induced by the state-subsidized housing loan system, also contributed to the pickup in lending. As a result of the latter, in the early 2000s new loan disbursements were dominated by state-subsidized forint loans. Retail foreign currency lending also appeared in Hungarian financial intermediation, although financial enterprises<sup>5</sup> were the sole providers of this product at the time. Indeed, typically the financial enterprises of foreign-owned banks offered foreign-currency-denominated loans to households, mainly to finance vehicle purchases. Thanks to parent bank relations, the owner bank was able to provide them with the required foreign currency funds (Banai et al., 2010a).

**Box 1: The identification methodology of equilibrium credit-to-GDP levels based on Kiss et al.**

The identification of the equilibrium credit-to-GDP levels is based on a two-step out-of-sample method. In the first step, eurozone data was employed for panel estimation using the pooled mean group (PMG) estimator. In the second step, the estimated long-run parameters (structural relationship) were used for the calculation of the equilibrium level of Hungary‘s credit-to-GDP.

The underlying assumptions for the estimation are that the long-term relationship is the same in every examined country, but the short-term dynamics and the constant can differ across countries. Specifically, it means that in the estimation of the equilibrium credit-to-GDP, the estimated parameters of the explanatory variables are assumed to be the same; however, the dynamics around the equilibrium, hence the constant in the equation, are allowed to differ. The explanatory variables for the estimation of equilibrium credit-to-GDP were the short-term real interest rate, the GDP and inflation.

Finally, for Hungary we used the common long-term parameters on the Hungarian data. Choosing the countryspecific constant was less straightforward. Therefore, we decided to plot out-of-sample equilibrium credit estimates using all country-specific effects.

It was only in 2004 that foreign currency lending rose noticeably in banks‘ mortgage lending. In response to news about a drastic tightening of the subsidy scheme on forint-denominated mortgage loans, 2003 saw a
, with 50 provinces and 346 cities, called ”comunas”. Meanwhile, the sectoral information is provided following ISIC rev.4 standards.

## **5.1 Pollution data**

Data for particulate matter (PM2.5) concentrations was sourced from van Donkelaar et al. (2016). This data contains annual global surface concentrations (micrograms per cubic meter) of mineral dust and sea-salt filtered fine particulate matter of 2.5 micrometers or smaller in diameter. This annual data set is gridded at 0.01 degrees, which allows us to connect pollution concentration levels for each city.

Chilean pollution data from the Ministry of Environment<sup>2</sup> is compared to the gridded data. For the majority of the cities the correlation between official and satellite data over time is high. Figure 3 presents the correlation for selected cities.

> 1We could easily use Euclidean distance, but this is a straight line distance measure, where as the Haversine distance measure accounts for great-circle distances, typically applicable for the earth’s geometry.

> 2 `httpss://sinca.mma.gob.cl/`

7
Do such breaks in the time series characteristics of these variables reflect fundamental changes in the government budget process? Was this change necessitated by the unsustainable nature of fiscal policy prior to the "data break?" Or is the change in the time series properties of the data merely reflecting changes in short-run dynamics rather than longrun relationships among fiscal variables? When there are data breaks, we should presumably focus on the more recent government budget process instead of the government budget process over the whole period if we want to assess the sustainability of current fiscal policy. The entire data sample would be used in assessing the sustainability of fiscal policy, past and present, allowing for shifts in policies over time (perhaps caused by the desire to insure sustainability).

Ahmed and Roger's (1995) analysis of sustainability of fiscal and current accounts in the United States and the United Kingdom includes annual data from 1792 and 1692, respectively. The U.S. sample, therefore, includes major wars such as the civil war, World War I and World War II. The U.K. sample includes the wars of Spanish Succession, Austrian Succession, the Seven Years' War, American Independence, wars with France, the Crimean and Boer wars, and World Wars I and II. The authors carry out a thorough analysis of the cointegration relationship implying sustainability taking into account the above-mentioned break points. While the U.K. results are somewhat inconclusive, they conclude that: "despite the recent U.S. twin deficits problem, the currently expected future course of fiscal policy might plausibly be regarded as sustainable. However, it is clear that to formally conclude this with any substantial degree of confidence--given the nature of the tests involved and the need for a long span of data that we have argued for--must await the availability of much more data" (p. 18). In the LDC context, of course, the econometrician Oliver Twist would certainly be chastised for calling out "More,
Africa, using national survey data from 1993.<sup>4</sup> The question is whether the gender of a transfer recipient matters for child outcomes. While pension recipients are unlikely to be parents of little children, about one-third of pension recipients live with children, typically their grandchildren. Duflo (2000) finds in households where there is a woman receiving an old-age pension compared to households where no one receives a pension, girls have better anthropometric status (weight for height and height for age).<sup>5</sup> More specifically, girls in households with a women receiving the pension have 1.19 standard deviations larger weight for height. Interestingly, the effect is only significant in households where the pension recipient is the mother of child's mother, whereas there is no effect for paternal grandmothers. There is also no significant effect of a man receiving a pension.

Atkin (2009) uses Mexican data to study the effect of mothers' employment in manufacturing on children's height for age. To identify causal effects, geographic variation in the opening of new factories at the time a woman enters the labor market is used. The study finds that child health outcomes improve for mothers who end up working in manufacturing due to a new factory opening: their children are between 1.18 and 1.75 standard deviations taller than children whose mothers did not have their first job in manufacturing. One shortcoming of this study is that male and female income shares within the household are not observed, so that it is not possible to separate between a general household-level income effect and an effect that is specific to female income.

# **2.3  Randomized Cash Transfer Programs**

Several studies have analyzed on the effects of the PROGRESA program in Mexico (Attanasio and Lechene 2002, Rubalcava, Teruel, and Thomas 2009, and Bobonis 2009). PROGRESA is a conditional cash-transfer program that makes transfers to mothers as long as their children meet certain criteria such as keeping up on
# **2. Background**

# **2.1. HIES rounds sampling design prior to the HIES 2016/17**

The HIES rounds have been central for monitoring poverty and welfare indicators in Bangladesh. Prior to the HIES 2016/17, the HIES rounds were designed to produce annual poverty estimates at the division level for urban and rural areas and Statistical Metropolitan Areas (SMAs) (see Munoz 1998 and 2004). The sample size of the HIES gradually increased over time and, as of the latest round completed in 2010, the sample size was 12,240 households. To avoid the effects of seasonality, the sample was proposed to be randomly split across quarters – a full round of the HIES data collection takes 12 months – but there was never an explicit attempt by BBS to produce quarterly poverty estimates before the HIES 2016/17.

All of the previous HIES rounds follow a stratified clustered sampling design – each of urban, rural, and SMA areas in a division forms a stratum. Primary Sampling Units (PSU) are constructed based on Census of Population and Housing Enumeration Areas and represent a cluster. PSUs are selected with probability proportional to size (PPS) and 20 households from each PSU are selected using systematic sampling.

It is worth noting that PSUs for all of the previous rounds of the HIES were selected from the Integrated Multiple-Purpose Sample (IMPS). The IMPS is a master sample updated after each Census of Population and Housing, and which has been used in Bangladesh as the sampling frame for the selection of Primary Sampling Units (PSUs) in all previous rounds of the HIES and other surveys such as the Labor Force Surveys and Demographic and Health Surveys.

The HIES 2016/17 deviates from the sampling design used in the previous rounds of the HIES in several ways. First, the objectives of the HIES 2016/17 have changed significantly from the one used to design the sample in previous rounds. Second, the HIES 2016/17 did not use the IMPS for
# **Appendix D: VenRePS Follow-up and Final Database Cleaning**

We hired Innovations for Poverty Action (IPA) to administer the survey over the telephone between October 2021 and March 2022. This operation represented the follow-up of individuals surveyed one year earlier. We managed to recontact 2,308 out of 3,455 migrant households—a high figure considering the challenges of following very mobile individuals who are often reluctant to give information for fear of deportation.

The tasks carried out in the and data collection of the round were design survey’s first crucial to implementing the follow-up phase. From the baseline, we needed detailed information that would allow us to track individuals in future rounds. Therefore, we asked for more than one telephone number and current residence. An essential part of the design was the pursuit of a “snowball” sampling strategy, which consists of identifying individuals who refer other potential participants. This allowed us to broaden the sample of potential respondents and helped us recontact respondents as needed.

The first round of survey collection ended in March 2021. We next conducted a WhatsApp survey, which enabled us to update participants’ telephone information prior to the start of the second round. We implemented two additional strategies. First, we telephoned individuals we could not reach on WhatsApp. Second, we incentivized participants to respond by conducting raffles and offering a document certifying that they were in Colombia prior to January 31, 2021. The last was a requirement to apply for the official Estatuto Temporal de Permanencia (ETPV), a status that allows migrants to work and access social programs for a ten-year renewable period. Between June 2021 and September 2021, we designed the questionnaire for the second round using three criteria. First, we prioritized the head of household and partner as the primary individuals to follow within the nuclear household. Second, we included questions to identify individuals who joined the household and those who were no longer part of it. Finally, we devised a strategy to characterize split households.

33
, University of California at San Diego.

- Hildebrandt, N. and McKenzie, D., (2005). The effects of migration on child health in Mexico. _Economia: Journal of the Latin American and Caribbean Economic Association_ 6, 257289.

- Kanaiaupuni, S. and Donato, K., (1999). Migradollars and mortality: The effects of migration on infant survival in Mexico. _Demography_ 36 (3),  339-353.

- Karlan, D. and Zinman, J., (2010). Expanding credit access: Using randomized supply decisions to estimate the impacts _.  Review of Financial Studies_ 23 (1), 433-464.

- Khandker, S., (2005). Microfinance and poverty: Evidence using panel data from Bangladesh. _World Bank Economic Review_ 19(2), 263-286.

- King, R. and Levine, R., (1993). Finance and growth: Schumpeter might be right. _Quarterly Journal of Economics_ 108, 717-737.

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