rafmacalaba/data-use-mentions-extended huggingface dataset:
problems, again jeopardizing the fundamental goal of improving services in low-income areas. The important point is that any requirement that concessionaires provide only a single level and quality of service can create problems if demand for that level of service is not high enough.

To avoid these pitfalls of output standards, concession contracts and sector regulations often include exclusivity provisions designed to ensure that households accept a single level of service from a single service provider (reduce the scope of household choice). Exclusivity reduces market risk, but it presents its own dangers for poor households; these problems are discussed in more detail below.

_Input standards: materials, design, and procedures_ Input standards dictate how concessionaires must achieve the output standards. For example, a concessionaire may be required not only to meet water quality standards, but also to do so by using a specific chemical and/or a specific filtration process.

_Materials and design standards_ SAMAPA, like all other public utilities in Bolivia, was subject to Bolivian standards for materials and system design in the water and sanitation sector. In designing the La Paz concession, the government intended to offer the concessionaire slightly more flexibility than SAMAPA had in this area. The Aguas del Illimani contract states only that

> 28 There is ample evidence from willingness to pay studies in developing countries that some households in some communities choose not to use low-tech systems, and instead invest in private solutions (e.g. private wells or standpost) that provide a higher level of service.

10
form and city productivity in Latin America (Duque et al., 2017a). In that work, the three nighttime images were used to delineate urban extents in each year for most of the Latin American and Caribbean cities that had more than 50,000 people in 2010 using a threshold approach. Figure 1 shows the workflow of urban extent delineation in Duque et al. (2017a). Figure 2 shows three examples of the obtained urban extents from the 2010 NTL image composite. Figure 3 shows the location of the obtained urban extents in Latin America and the Caribbean region.

> 1 Image and Data processing by NOAA's National Geophysical Data Center. DMSP data collected by the US Air Force Weather Agency. https://ngdc.noaa.gov/eog/dmsp/download V4composites.html.
fleet; and the number of doctors per capita. We also document the importance of seatbelt usage, although this significantly reduces the size of our dataset.

The paper is organized as follows. Section 2 describes the pattern of pedestrian and occupant fatalities in the IRTAD countries over the study period. In section 3 we develop formal models of pedestrian and vehicle occupant fatalities, following Edlin (1999). We estimate two version of these models: one in which all variables are proxied by per capita income (section 4); and a second in which we use a richer set of variables to explain the behavior of pedestrian and occupant fatalities per VKT in industrialized countries between 1964 and 2002 (section 5). Section 6 concludes.

# **2. Traffic Fatality Patterns in Industrialized Countries**

This paper focuses on a subset of high-income countries, countries that, from the early 1970s to the present have experienced a decline in traffic fatalities per vehicle kilometer traveled (VKT). The countries, which (with the exception of Chile and Israel) are all members of the OECD’s IRTAD database, are listed in Table 1. Between 1970 and 1999, total traffic fatalities declined, on average, by nearly 35% in most of these countries, while total vehicle kilometers driven increased by over 250%.<sup>3</sup> Within each country, the decline was more dramatic for the most vulnerable road users: pedestrians and bicyclists.<sup>4</sup> As shown in Table 1, on average, the number of pedestrian and bicyclist fatalities fell by over 60% in our sample countries between 1970 and 1999. Occupant fatalities, on the other hand, declined, on average, by 21% during this period, and even

> 3 On average, the total number of vehicles increased by over 200% during this period.

> 4 Hereafter, “pedestrian” deaths refers to both pedestrian and bicyclist fatalities resulting from a motor vehicle accident.

5
— both measurement noise and the levels of reported skills for example via the level of explanation they provide or other unintended nudges, or if respondents report differently to enumerators of different genders (see Di Maio and Fiala, 2020; Laajaj and Macours, 2021; Rodriguez-Segura and Schueler, 2023). Importantly, these effects may also interact with the respondent’s gender.<sup>10</sup> Next, we expand the controls to include key characteristics of — interest that might be associated with individuals’ self-reported SES years of education, cognitive ability, social desirability, and beliefs on gendered abilities. Finally, to test whether these additional correlates play a differential role by gender and help in explaining purported gender gaps, we interact these variables with the gender dummy.

> 10Our baseline survey was administered by 52 enumerators, equally split by sex, organized into six teams of approximately nine members each. Each team was responsible for surveying respondents within their assigned city: four teams in Dar es Salaam, and one team each for Dodoma and Iringa. The geographically limited teams were formed, balancing administrative and logistical burdens as well as minimizing survey biases. First, we purposely chose six team leaders, one for each team, for administrative purposes. Second, the remaining 46 enumerators chose a city with which they were familiar for logistical considerations. Enumerators who chose Dodoma and Iringa were automatically members of the single team assigned to these cities. Enumerators who chose Dar es Salaam were randomly assigned to one of its four teams. These teams were then randomly assigned to communities within their assigned cities. Finally, within an assigned community, enumerators (members of a team) were randomly assigned to specific respondents without blocking by enumerator or respondent characteristics.

12
households than the benchmark. All other interaction terms are not significantly different from zero. As we have seen in this sub-section, while absolute poverty measures vary dramatically across the different modules, the partial correlations of poverty status with selected characteristics do not differ significantly and the relative rankings of households with those same characteristics are largely stable between modules.

# **5. Resource Implications**

The willingness to accept some degree of inaccuracy in consumption estimates from using a recall survey or a household diary compared with the personal diary is driven by the practical need to reduce the study costs and the burden to respondents of survey work. Our benchmark of frequently supervised individual diaries is often not a feasible option for field researchers, which leads to the question of recommendations for alternative approaches. Here we review the cost implications of different survey designs, focusing first on the cost in terms of time to administer a recall module and then on dollar expenditures for survey implementation in order to contrast recall with diary approaches.

Among the recall modules, the shorter lists in the subset and collapsed recall modules are assumed to significantly reduce the length of time to complete the module and this consideration in our experiences is often used as a justification to adopt a shorter consumption module. Figure 2 presents the average time to complete the recall modules. Respondents required an average of 50 minutes to complete the recall module that listed 58 foods for a 14-day reference period; for the 7- day full list module, the length of time to complete is just 1 minute shorter. The mean time savings is only 8 minutes (42 minutes total) when using the 11 broad food group headings (module 4) and 9 minutes (41 minutes total) when using the module 3 subset recall list with the 17 most important food items. While the interview time is shorter on average, the 8 or 9 minute savings in interview time of the shortened modules must be weighed against the overall lower mean consumption (especially for module 4) and truncated distribution relative to the longer list
plentiful in the agricultural tariff schedules of many high-income, high-protection countries), and the effects of agricultural tariff rate quotas. In addition, key trade policy changes to the start of 2005 have been added, namely, the commitments associated with accession to WTO by such economies as China and Taiwan (China), the implementation of the last of the Uruguay Round commitments (most notably the abolition of quotas on trade in textiles and clothing at the end of 2004), and the eastward enlargement of the European Union from 15 to 25 members in April 2004.

Hence what distinguishes the present study from the above 2004 studies and other books with similar titles is that (a) its _ex ante_ analysis focuses on the core aspects of the July Framework Agreement from the viewpoint of agriculture and developing countries, taking account also of what might happen to non-agricultural market access and the other negotiating areas, and (b) it does so in an integrated way by using the new GTAP Version 6 database (amended to account for key protection changes to early 2005) and the latest version of the World Bank’s global, economy-wide Linkage model, details of which are documented in van der Mensbrugghe (2004).<sup>4</sup>

# **What questions are addressed in this study?**

Among the core questions addressed in this study, following an intense program of integrated research during the latter half of 2004 by a complementary set of wellinformed scholars from four continents, are the following:

- What is at stake in this Doha round, in terms of efficiency gains foregone by the various regions of the world because of current tariffs and agricultural subsidies?

4 This analysis is vastly more sophisticated than the _ex ante_ analyses undertaken for the Uruguay Round. At that time there were very few economy -wide global models, so primary reliance was on partial equilibrium models of world food markets (see, e.g., World Bank 1986, Goldin and Knudsen 1990, Tyers and Anderson 1992); estimates
# **1. Introduction**

The quality of preschool education<sup>6</sup> plays an important role in early development. Research to date has shown that children who have high-quality early childhood education experiences have better cognitive and socio-emotional outcomes (Engle et al., 2011). Unfortunately, providing quality early childhood education services can be particularly challenging in poor, rural contexts – especially so in developing countries. As a result, few studies have been able to use an internationally comparable measure of quality to examine the link between quality and child development outcomes in remote, resource-constrained environments.

This study investigates the quality of early childhood education programs in 303 villages in Indonesia. We use data collected in 2013 as part of an impact evaluation of the Indonesia Early Childhood Education and Development (ECED) Project, which provides rich information on early childhood classrooms, teacher characteristics, and child development outcomes.

Indonesia offers a useful setting to explore early childhood education as the government has been highly committed to improving both access to and quality of preschools in the country (Hasan, Hyson and Chang, 2013). In 2009, the Ministry of Education and Culture established national standards for ECED quality, further emphasizing the importance of investing in highquality programs. By providing an overview of the quality of early childhood education services in poor, rural areas in Indonesia, this study will help inform policy makers whether the current national quality standards align well with desired child development outcomes.

This paper is organized as follows. Section 2 reviews the literature on early childhood education quality by discussing three components of quality: observed preschool quality (focusing on the ECERS-R, an internationally comparable measure), teacher characteristics (measured using their education and experience), and structural characteristics. Section 3 provides an overview of the early childhood education policy landscape in Indonesia and the research questions in this study. Then, section 4 introduces the data and methods of the study. In section 5, we outline the empirical strategy – including approaches to correcting for measurement
A closer look at the data for old age and disability pensions shows that male pensioners on average do reach a high net replacement rate. Male pensioners in 1994 on average had 39.3 insured years of service with an average of 1. I personal points per year. Relating the average pension paid to male pensioners in 1994 to the average wage results in a net replacement rate of 72 percent (gross:50 percent). For female pensioners, however, the net replacement rate was considerably lower at about 40 percent due to an average of only 25 insured years and 0.7 personal points per year.7 A pensioner receiving a full pension at or above age 65 may earn unlimited additional income. For cases of early retirement pensions are reduced according to the level of additional income earned.

Pension contributions are subject to income tax. Pension contributions are paid out of after-tax income; but some tax deductions are allowed for insurance contributions.According to German tax laws, only that portion of the pension is taxable which represents the notional capital gain on contributions.

There is no minimum pension in Germany; however, a method is applied to lift very low pensions by increasing the personal points to a maximum of 0.75 points per year, provided that the insured has contributed for 35 years.This increase has benefited predominantly female pensioners of the Workers' Insurance who made very low contributions during their working life. But the most important supplement for lowincome pensioners is social assistance. Approximately half of all social assistance is paid to pensioners, and about one third of all social assistance is spent for long term care. Social assistance is financed at the local level, thus the municipalities' budgets are increasingly burdened with the costs of aging. Therefore, in 1995, Germany introduced a new branch of social insurance for long term care.

Pensioners must contribute to the statutory health insurance unless they are covered by a comparable private health insurance contract. The rate is currently 6.7 percent of the pension. This contribution is matched
of standard controls including experience (and experience-squared), marital status, _i_ gender, industry, and occupation. Finally,  _jk_ is the error term at the individual level, which is correlated between individuals in the same cohort. We adjust standard errors by accounting for cluster effects within cohorts.<sup>8</sup> We use two main data sources: the 2006 Labor Force Survey (LFS) and the nationally representative migration survey undertaken in 2006 by CBS-AXA (2006). The CBSAXA survey collects detailed demographic and socio-economic information on every member of the household, including information on whether there are members of the households who are currently abroad, their labor market and remittance activities, etc. We construct education-experience emigration cohort using CBS-AXA data. The rest of the individual-level data are from the LFS. The analysis includes only the working-age, wage-employed individuals, following standard practice. We also use supplemental summary information from the Annual Survey of Enterprises to report relevant labor demand trends and discuss the implications of the main results. The descriptive statistics are in Appendix Table 1. Wages are top-coded and we address this in our robustness tests.

We define as emigrants those who are of working age who are currently abroad and who may or may not have existing ties to households in Moldova.<sup>9</sup> The inclusion of emigrants who are considered ex-members of households in Moldova is an improvement over the existing literature, which has tended to discuss Moldovan emigration only with respect to those with existing ties to Moldovan households. Nonetheless, our measure of emigration may still be subject to measurement error due to sampling error and because households whose members have all left Moldova will not be captured in the survey.

> 8 This was done using the _cluster_ option in Stata. We also ran our baseline model correcting for cluster effects due to the multi-stage stratified design of the LFS and found similar results.

> 9 Other studies (e.g., International Organization of Migration, 2007) restrict their analyses to those emigrants
half of the respondents were asked about their experiences with conflicts, deaths, and shocks before the questions on depression, while the other half were asked about their experiences with these adverse events _after_ the questions on depression.

Even though previous studies find a clear relationship between adverse events and depression, it is hard to identify whether depression is caused primarily by shocks or lower income. Lund et al. (2010) conduct a meta-analysis on the relationship between poverty and depression in low and middle income countries, and find a positive association between poverty and depression in many studies. <mark>Distinguishing whether poverty or adverse events affect mental health and economic activities has important policy implications. If the primary causal link is that low incomes leads to deteriorating mental health, then interventions such as cash transfers and access to credit are likely to be effective. O</mark> n the other hand, if depression is caused solely by experiencing shocks, interventions that focus on treating depression can be more effective. Although the linkages between poverty, adverse events and depression are difficult to disentagle, this study will examine these linkages and attempt to provide some insights on their relative magnitudes. Through the analysis, we can provide prelimiary guidance on the most effective policy interventions to combat the negative effects.

Furthermore, poverty, adverse events and depression have the potential to be endogenous. For example, people may have fallen into poverty as a result of adverse events or depression. In addition, people may be more strongly impacted by negative shocks because they were already poor or had mental health problems. Although the endogeneity between poverty, adverse events and depression cannot be fully controlled, this study attempts to address the problem by investigating the effects of lagged consumption expenditures from the previous wave of the survey (2012-13) and the experience of adverse events after lagged consumption was observed (between the second and third waves of the survey) on the current level of depression. As GHS-Panel is a panel survey, consumption expenditure information is available from three waves of the
Policy Research Working Paper 6426

# **Abstract**

Most migration surveys do not ask about the legal status of migrants due to concerns about the sensitivity of this question. List randomization is a technique that has been used in a number of other social science applications to elicit sensitive information. This paper trials this technique by adding it to surveys conducted in Ethiopia, Mexico, Morocco, and the Philippines. It shows how, in principal, this can be used both to give an estimate of the overall rate of illegal migration in the population being surveyed, as well as to determine illegal migration rates for subgroups such as more or less educated households. The results suggest that there is some useful information in this method: higher rates of illegal migration in countries where illegal migration is thought to be more prevalent and households who say they have a migrant are more likely to report having an illegal migrant. Nevertheless, some of the other findings also suggest some possible inconsistencies or noise in the conclusions obtained using this method. The authors suggest directions for future attempts to implement this approach in migration surveys.

This paper is a product of the Finance and Private Sector Development Team, Development Research Group. 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://econ.worldbank.org. The author may be contacted at dmckenzie@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 of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World
and city-level wealth level prediction.

**Asset wealth index (AWI).** We construct the asset wealth index using data from the national census questionnaire. We utilize full census data in Mozambique and Madagascar, and census extracts in Malawi and Burkina Faso, resulting in a total dataset comprising over 12 million households across four countries, with more than 700,000 households represented in each country’s dataset. In contrast, previous studies [29, 23] leveraging DHS data included approximately 500,000 households across 23 African countries, while LSMS data measured about 9,000 households across five countries. Table 1 provides a full description of the size of the datasets.

From the census questionnaire, we rank seven housing characteristics (housing type, wall material, roof material, floor material, water source, toilet type, and energy source) on a scale of 1 to 5. Additionally, we assess the presence of six assets (radio, television, landline, car, motorbike, and bicycle) using a binary classification (ownership/non-ownership). This data is then standardized and used to construct a principal components analysis (PCA) model, from which the first principal component was extracted as the asset wealth index [13, 25, 29]. Asset wealth index labels are then aggregated from the household to the

**Table 1**

National census data details.

|Country|#Images # Admin areas # Households Surveyed|
|---|---|
|Malawi (2008)|3,432<br>12,412<br>572,764|
|Malawi (2018)|3,432<br>18,700<br>796,925|
|Mozambique (2007)|37,325<br>45,244<br>4,797,372|
|Mozambique (2017)|37,325<br>67,218<br>6,119,847|
|Burkina Faso (2019)
force is then distributed across different labor types based on base

> 5 The SAM is available upon request.

> 6 The SUT, TOFE, TCEI and the household survey were sourced from INSEED. The latest available TCEI is for 2010.

> 7 In French the original title of the survey is Enquête sur la Consommation des Ménages et le Secteur Informel au Tchad (Ecosit

> 4). It is a survey with a sample size of 7,493 households representative at the national and regional levels and by urban/rural.

3