rafmacalaba/datause-encoder-data huggingface dataset:
An example is provided by Cromley, Cromley and Ye (2004) where user queries yield results only if the cell contains at least six records (and the minimum population in the smallest mapping unit is about 1,000).

Point data on household locations can be converted to a continuous surface to represent the spatial distribution of either characteristics or outcomes without identifying respondents. For example, geographers have a variety of spatial interpolation methods, such as spatial variants of the kernel density estimators increasingly used by economists (Bithell, 1990). Alternatively, point location coordinates can be replaced with distances to various features of interest in any public release dataset. However these methods are not very flexible and are likely to limit future research use of the data. Surfaces do not provide the micro data needed for studies that seek to measure causal impacts. The features of interest that distances are reported for are likely to vary from one study to another and as distances to more features are included the possibility of using triangulation to identify household locations increases. Moreover, distances are often needed for more than just features of interest. For example, knowing the position of households relative to other households helps study learning from neighbors (Conley and Udry, 2005) and helps improve the modeling of spatial autocorrelation (Gibson and Olivia, 2007).

Aggregating groups of observations into larger reporting units is a widely used method for maintaining confidentiality of both survey and census records. With GPS coordinates, the locations of individual households could be aggregated into larger areal units like Census Blocks or Census Tracts so that all that is reported is either an administrative code for the larger area or a polygon showing the boundaries of the area where the household is located. These techniques can also be applied to the visual display of data by using dot points on a map that are sufficiently large to prevent disclosure risk. For example, VanWey et al. (2005) show how the size of the required buffer around the locations of sampled schools in a U.S. survey would need to vary from only six kilometers in a city to over 50 kilometers in the countryside in order to hold disclosure risk to only five percent when mapping the sample points. Although aggregation can reduce disclosure risk it comes at the cost of seriously degrading the analyses that can be conducted since so much detailed spatial information is lost. For example, Fefferman, O’Neil and Naumova (2005) providing an example where areal aggregation yields little benefit of additional privacy and large costs in terms of impaired ability of statistical tools to analyze patterns of disease incidence.

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understanding why mortality has declined among better-off children but not among poor children. To investigate this, we divide the births in our sample into two groups: the poorest quartile of children (the "poor"), and the richest three quartiles (the "nonpoor"). The smaller decline in mortality among poor children may be due to any or all of four reasons: (i) the poor experienced less advantageous changes in the x's; (ii) changes in the x's mattered less for the poor since they face a worse set of coefficients linking survival determinants to survival outcomes; (iii) the poor experienced less advantageous changes in the Fs; and (iv) changes in the fl's mattered less to the poor since they have worse determinants to start with. Thus in a similar vein to Makepeace and others (1999), we can write a decomposition for the _differential_ change in mortality across poverty groups: where the LHS indicates how much more -lnA has risen for the nonpoor as compared to the poor, and Terms _DI - D4_ correspond to (i) - (iv) above. There is no reason, of course, why _DI, D2,_ D3 and D4 should all be positive-it may well be some changes have worked to make for a smaller reduction in mortality among the nonpoor (i.e., one or more of the terms in eqn. (6) might be negative).

Components (i) and (iv) are straightforward to rationalize-one would expect that the poor and nonpoor will have different mean values of the x's in any one year, and that these means may change differently across the two consumption groups. Jalan and Ravallion (2001) develop a theoretical model which rationalizes differential Pl's across the poor and nonpoor. In their model, child health depends on parental inputs and other inputs (such as piped drinking water). If parental inputs and, say, piped water are complements, parents will increase their own inputs when piped water increases, and it is likely that child health will increase. Jalan and Ravallion also show that if parents inputs and water are complements, the impact of water on health is likely to rise with income, 14
# **References.**

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Boeri, T. (1997) "Learning from Transition Economies: Assessing Labor Market policies across Central and eastern Europe". Journal of Comparative Economics 25, pp. 366-384.

Boeri, T (1997) "Labor-Market reforms in Transition Economies". Oxford Review of Economic Policy, vol. 13, No. 2, pp. 126-140.

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Cebrian, **I.** _et alia_ (1996) "The Influence of Unemployment Benefits on Unemployment Duration: Evidence from Spain". Labour, 10 (2), pp. 239-267.

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Ham, J.C., Svejnar, J. and Terrell K. (1998) "Unemployment and the Social Safety Net during Transition to a Market Economy: Evidence from the Czech and Slovak Republics". American Economic Review, December, pp. 1117-1142.

Lubyova, M. (2000) "Overview of the Evolution of the Slovak Labor Market" in _Economic Policy in Slovakia, 1990-1999._ A. Marcincin and M. Beblorvy, editors.

Lubyova, M. and van Ours, J.C. (1999) "Effects of active Labor Market Programs on the Transition Rate from Unemployment into Regular Jobs in the Slovak republic".

Lubyova, M. and van Ours, J.C. (1999) "Work Incentives and Other Effects of the Transition to Social Assistance: Evidence from the Slovak Republic". Empirical Economics, 23, pp. 121-153.

Lubyova, M. and van Ours, J.C. (1997) "Unemployment Dynamics and the Restructuring of the Slovak Unemployment Benefit System". European Economic Review 41, pp. 925-934.

Meyer, B.D. (1990) "Unemployment Insurance and Unemployment Spells". Econometrica, vol. 58, No. 4, July, pp. 757-782.

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# **Impact of Salinity on Infant and Neonatal Mortality in Bangladesh**

George Joseph<sup>1</sup> , Qiao Wang<sup>1</sup> , Gnanaraj Chellaraj<sup>1</sup> , Mohammed Shamsudduha<sup>2</sup> , Abu Mohammed Naser<sup>3</sup>

## **JEL Classification: I15, Q25, Q53**

## **Key words: Bangladesh, Water, Health, Salinity, Mortality**

> 1 World Bank, Washington DC, USA

> 2 Institute for Risk and Disaster Reduction, University College London, UK

> 3 <mark>Emory Global Diabetes Research Center, Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA</mark>
To see this, consider the numerical example illustrated in Figure 7. The unshaded area in the top panel depicts the set of ( _τ, θ_ ) types that are hired by an intermediate management public school, while the unshaded area in the bottom panel depicts the set of ( _τ, θ_ ) types that are hired by a low management public school. It is clear that the intermediate management public school hires both more and better types.

In contrast to the people management case, there is a channel operating via household incentives. A further part of the reason that test scores are higher in schools with good operations management practices is because households (students plus parents) exert more effort due to additional _intrinsic_ motivation arising via the shift term _γ_ .

# **3.4.2 Predictions for intermediate school outcomes and evidence from PISA**

Again, we set out predictions relating to intermediate school outcomes (see Remark 2 in Appendix A), and then explore empirically whether they hold in our PISA data.<sup>24</sup>

**Teacher shortages.** The probability of hiring the teacher in an intermediate management public school is higher than the probability of hiring the teacher in a low management public school (via teacher selection). In the numerical example shown in Figure 7, the unshaded area is larger in the top panel relative to the bottom panel.

We take this prediction to the data using the 4 questions in the PISA school principal questionnaire that ask the principal whether they feel that the school’s capacity is hindered by a lack of qualified teachers (see Appendix C). Column (1) of Table 4 shows a negative and statistically significant correlation between the operations management index and the teacher shortage index. A one standard deviation increase in operation score is associated with a 0 _._ 076 standard deviation _decrease_ in the teacher shortage index, significant at the 10 percent level.

**Teacher motivation.** The expected intrinsic motivation of a teacher hired to an intermediate management public school is higher than the expected intrinsic motivation of a teacher hired to a

> 24We present the main results with our preferred specification, but include additional variations of the main explanatory variable in Tables B.2 in Appendix B. The results are robust to alternative specifications.

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# **INTRODUCTION**

Over the course of history, governments have applied import protection through many different policy instruments. One extreme features an instrument that is widespread, simple, and relatively transparent: most customs authorities currently apply a nondiscriminatory, ad valorem import tariff. Heading toward the other extreme are dozens if not hundreds of eclectic examples of instruments that are more complex, less transparent, and which frequently entail additional political-economic distortions. Consider the experience of only one industry in only one country – U.S. steel – even since the 1960s. While being protected by applied, nondiscriminatory, ad valorem import tariffs, U.S. steel has also featured quotas, minimum price arrangements, voluntary export restraints, antidumping, countervailing duties, suspension agreements, preferential tariffs to NAFTA and other partners, import licenses and monitoring, safeguards, expanded trade adjustment assistance, and local content requirements.

That import protection arises through such a number of different instruments raises fundamental questions for political-economic research. Are there apparent trends in the use and non-use of particular import protection instruments? Furthermore, what are the political-economic and institutional determinants of, interrelationships between, and implications for, government use of these different instruments?

The next section begins by examining historical trends for a number of import protection instruments. Perhaps the most pervasive trend across the international trading system since 1947 has been the reduction in applied tariffs and opening of economies to international commerce. Nevertheless, it is worth recalling _The New York Times_ analogy that Robert E. Baldwin made famous at the conclusion of the Kennedy Round through its inclusion in his comprehensive economic analyses of nontariff protection, "[t]he lowering of tariffs has, in effect, been like draining a swamp. The lower water level has revealed all the snags and stumps of non-tariff barriers that still have to be cleared away" (1970, 2).

While individual nations may have drained their swamps by lowering applied tariffs, the more complete story of import protection admits to substantial heterogeneity. Sometimes these low applied tariffs have not been accompanied by the legal commitments that ‘bind’ them under the World Trade 2
**Folha de Pagamentos do Bolsa Familia (BF payment records)** The payroll dataset of BF contains information on the monthly payments received by every family. It does not allow for distinguishing between the different benefits but gives the total sum of transfers received. In addition, datasets on the exit reasons and people in the benefit graduation/transition rules ( _Regra de Permanencia_ ) are available from 2016 onwards.

**Rela ̧c ̃ao Anual de Informa ̧c ̃oes Sociais (RAIS)** RAIS is an administrative dataset that contains information on formal dependent employment in Brazil. Every company needs to fill in the information on its employees’ occupation, monthly compensation, contract type, date of entering the company, date of exiting the company, and dismissal reason. In addition, information on the firm, including the economic sector, the location, and the size of the establishment (defined by the number of employees), is available.

# **2.3 Sample Construction and Key Variables**

We construct a panel to longitudinally track all individuals aged 18 to 59 who were newly registered in CadUnico and either belonged to a BF recipient family as of December 2012 or joined an already recipient BF family at some point during the observation period. BF participation is determined based on payment records, which are registered at the household head level. To identify all family recipients, we expand the payment information using the family identification number, ensuring coverage of all household members. Individual records in CadUnico are then matched to RAIS using the anonymized _Programa Integra ̧c ̃ao Social_ (PIS) number. The initial set of individuals is followed monthly until 2019. We then further collapse the data to a semester basis – enabling us to track individuals over 14 semesters and examine their transitions into and out of the formal labor market – and at the family level – to examine family-level movements in and out of the BF program. Figure A.1 in the Annex provides an overview of the data merging process.

**Exiting Bolsa Familia** Exiting BF is defined by using the program payment records ( _folha de pagamento_ ). We define exiting BF as not being in the program for at least four consecutive months. This threshold has been chosen since beneficiaries who do not comply with program rules might get a grace period of three months in which the benefit is suspended, though people are not expelled from the program immediately. Additionally, we consider beneficiary families that enter the permanence rule as if they have left. The reasoning is that we want to identify the impact of employment changes at the municipality level on exit probabilities. The permanence

9
**Figure 2. EMBI Spreads for Brazil, Chile, and Turkey, 1996-2003**

<!-- Start of picture text --> Basis points<br>2400<br>2100<br>Brazil<br>1800<br>1500 Turkey<br>1200<br>900<br>600<br>300 Developed-country high-risk Chile<br>0<br>Jun-96 Jun-97 Jun-98 Jun-99 Jun-00 Jun-01 Jun-02 Jun-03<br><!-- End of picture text --> _Note:_ Spreads on developed-country high risk is an average for the global junk bond market _Sources:_ Bloomberg, JP Morgan Chase, and GDF, World Bank

**Figure 3.  EMBI Spreads for Selected East Asian Countries, 1997-2003**

<!-- Start of picture text --> Basis points<br>1050<br>Developed-country high-risk<br>i k<br>900<br>750<br>600<br>450<br>Philippines<br>300<br>Malaysia<br>150<br>Thailand<br>Korea<br>0<br>Dec-97 Aug-98 Apr-99 Dec-99 Aug-00 Apr-01 Dec-01 Aug-02 Apr-03 Dec-03<br><!-- End of picture text --> _Note:_ Spreads on developed-country high risk is an average for the global junk bond market _Sources:_ Bloomberg, JP Morgan Chase, and GDF, World Bank 28
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reflected by the recent increasing real wages of unskilled workers (with incomplete or no education)—is encouraging (Verner 2004).

## **2.2 Agriculture, Land and Rural Living**

Although nearly half of Mexico's total land area is officially classified as agricultural, only 12 percent of the total area is cultivated. This is one of many factors driving migration and off-farm employment in rural Mexico. In the early 1990s, 80 percent of Mexico's cultivated land required regular irrigation. Because of the high cost of irrigation, the government has emphasized expanding production on existing farmland rather than expanding the area under irrigation. Although corn is grown on almost half of Mexico's cropland, the country became a net importer of grain during the 1970s.

Agricultural practices in Mexico range from traditional techniques, such as the slash-and-burn cultivation of indigenous plants for family subsistence, to the use of advanced technology and marketing expertise in large-scale, capital-intensive export agriculture. Government extension programs have fostered the wider use of machinery, fertilizers, and soil conservation techniques. These diverse agricultural practices call for a diverse rural labor market.

# **3. Poverty**

Since 1996, Mexico has made creditable headway in reducing national poverty. During 1996-2002, the state’s extreme poverty, measured by P0, fell 17 percentage points (Figure 3.1 and Table 3.1).<sup>4</sup> There is little room for complacency, however, because extreme poverty was still only slightly lower in 2002 when 20 percent of the Mexicans were poorer than it was in 1992 (22 percent). This translates to around 20 million Mexicans who still live in extreme poverty, which means that they do not have sufficient income to buy a minimum basket of food.

Rural population is more affected than urban population by poverty. Extreme poverty affected 42 percent of the rural population in areas with less than 2,500 inhabitants in 2002, approximately the same as one decade earlier (Figure 3.1 and Table 3.1). While only 25 percent of Mexico’s population lives in rural areas, more than 65 percent of the Mexican poor are live in rural areas. The incidence of extreme rural poverty has declined since 1996, but at a slower pace than the decline in urban poverty.

> 4 Throughout this paper poverty refers to extreme poverty and poor to extremely poor. The secretariat of social development ( _Secretaria de Desarrollo Social-_ SEDESOL) uses three poverty lines: a “foodbased” poverty line (income required to acquire enough food to cover nutritional needs); a “human needs” poverty line which includes also the income required to acquire basic education, health, housing, dress, footwear, and transportation; and an “assets-based” poverty line, which also includes other needs. The latter corresponds to the usual broad definition of “poverty”, which we call “moderate poverty’, while the former corresponds to the usual definition of  “extreme poverty” (World Bank 2004 for more information on poverty lines).

8
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