rafmacalaba/datause-encoder-data huggingface dataset:
55. Epidemiological data on the health effects of child labor in Brazil are sorely needed. Although the above concerns are largely theoretical, they provide a guide for further investigation into the impact of child labor on children's health in Brazil. In addition, researchers need should examine gender and sex differentiated impacts, resulting not only from physiological and developmental differences, but also from social differences between girls and boys (i.e., discrimiination in the workplace and home, gender stereotypes, and social expectations and norns).

## IV. **INTERVENTIONS ADDRESSING THE** WORST FORMS **OF CHILD LABOR IN BRAZIL**

56. This section is divided into two parts: the first focuses on the Brazilian Government's efforts to reduce child labor, and the second discusses the general approaches for targeting children on the street, and examples of each in Brazil. The Brazilian Government has concentrated much of its efforts on providing conditional cash grants with the objective of increasing education and discouraging child labor. As far as children working in the streets, Government programs have focused on urban areas.

# The **Child Labor Eradication** (PETI) **Program**

57. The Child Labor Eradication (PETI) Program was initiated in 1996 in _rural areas_ of Brazil, and by 1999 had managed to reach 166 municipalities in eight states and 131,000 working children. The program aims to increase educational attainment and reduce poverty as well as eradicating the "worst forms" of child labor. It provides stipends of approximately R$25 per month to poor families who have children ages 7-14; resources are given to the mother of the beneficiaries. To be eligible, all school age children in the family must attend school participate in after-school activities, and agree not to work. After-school activities _(JornadaAmpliada)_ are a way of ensuring that children do not mix school and work. The advantage of the PETI program over other types of minimum income guarantee programs is that it is more targeted. This program is also anchored in the school system, and is supported by rural worker unions, which assist in the selection of children and the monitoring of the program.

22
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# Table 4: **Average Wage Differentials () by Gender, Experience and Education**

||||Educatio|n (years)||
|---|---|---|---|---|---|
|Gender|Experience (years)|0 to 3|3+ to 7|7+ to 12|12+|
|Male|0 to 10|0.21|0.18|0.05|-0.04|
||10+ to 20|0.12|0.13|-0.03|-0.08|
||Above 20|0.20|0.15|-0.01|-0.08|
|Female|0 to 10|..|0.27|0.15|0.11|
||10+ to 20|0.26|0.20|0.11|0.09|
||Above 20|0.33|0.26|0.14|0.09|

Source: Estimated from above results in Table 3. Notes: .. indicates small cell count.

The examination of the wage differential by the probability of being an indigenous person is listed in Table 5. Those living in _municipios_ with more than a ten percent indigenous population experience greater wage advantages in the union sector than do those with similar education and experience in less indigenous _municipios._ For example, for those with 10 to 20 years experience, and 7 to 12 years of schooling, the union-nonunion wage differential is nearly 31 times higher for those in more indigenous areas than in less indigenous areas.

19
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**_Source:_** World Health Organization: Estimates of numbers of deaths by sex, cause and WHO mortality sub-region for 2002

<u>www.who.int/healthinfo/bodgbd2002revised/en/index.html</u> 10
# Figure 9. Effect of policies on potential output growth

## A. Global potential growth in reform scenarios

<!-- Start of picture text --> Percent Social benefit reforms<br>4 Labor market reforms<br>Education and health improvements<br>Investment surge<br>3 Baseline<br>2<br>1<br>0<br>2011-21 2022-30 Reform impact<br>C. EMDE potential growth in reform<br>scenarios<br>Percent Social benefit reforms<br>8 Labor market reforms<br>Education and health improvements<br>6 Investment surge<br>Baseline<br>4<br>2<br>0<br>EAP ECA LAC<br>Source: World Bank estimates.<br>2011-21 2022-30 Reform impact 2011-21 2022-30 Reform impact 2011-21 2022-30 Reform impact<br><!-- End of picture text --> Source: World Bank estimates.

B. EMDE potential growth in reform scenarios <!-- Start of picture text --> Percent Social benefit reforms<br>6 Labor market reforms<br>Education and health improvements<br>Investment surge<br>5 Baseline<br>4<br>3<br>2<br>2011-21 2022-30 Reform impact<br><!-- End of picture text -->

## D. EMDE potential growth in reform scenarios

<!-- Start of picture text --> Percent Social benefit reforms<br>Labor market reforms<br>8<br>Education and health improvements<br>Investment surge<br>6<br>Baseline<br>4<br>2<br>0<br>MNA SAR SSA<br>2011-21 2022-30 Reform impact 2011-21 2022-30 Reform impact 2011-21 2022-30 Reform impact<br><!-- End of picture text --> Note: EAP = East Asia and Pacific, ECA = Europe and Central Asia, LAC = Latin America and the Caribbean, MNA = Middle East and North Africa, SAR = South Asia, and SSA = Sub-Saharan Africa. A.-D. GDP-weighted arithmetic averages. Scenarios assume a repeat, in each country, of each country’s best ten-year improvement.
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Dix-Carneiro and Kovak Trade Reform and Regional Dynamics dinal analysis is similar in spirit, but differs in a number of ways. Most importantly, we study a discrete policy shock rather than a continuously evolving phenomenon like Chinese export growth. This allows us to study the subsequent dynamics following liberalization without the confounding influence that occurs with a continually evolving shock. We focus on regional rather than industry shocks and study formal sector migration and population responses to regional shocks. Finally, we examine various margins of adjustment, including shifts into informal employment, nonemployment, and transitions between tradable and nontradable sector employment, all of which are salient features of the Brazilian context.

As an additional contribution, we examine administrative employer-employee data alongside more commonly available household survey data from the Brazilian Decennial Census of Population. When possible, we corroborate the findings across the two datasets, and find quite consistent results. Given the growing popularity of matched employer-employee data, it is encouraging that results from more traditional cross-sectional data sources are similar.

To summarize, our paper makes contributions to five strands of the international, labor and development economics literatures. First, this is the first paper empirically describing the transitional labor market dynamics that arise in response to a major trade liberalization episode. Second, we complement a growing literature on the local labor market effects of trade by studying the dynamics of these effects and putting existing static results into context. Third, our findings challenge the conventional wisdom in the labor economics literature that the impact of local shocks will be gradually dissipated through equalizing migration. We provide a theoretical interpretation for these findings and present additional empirical evidence in support of that interpretation. Fourth, we are the first to document the medium- to long-run effects of a major trade policy reform by following workers over time and across sectors and regions. Fifth, we find novel results regarding the effect of trade policy changes on informality in Brazil and reconcile our findings with those of the existing literature.

Our paper proceeds as follows. Section 2 describes the history and institutional context of Brazil’s early 1990s trade liberalization. Section 3 describes the data sources, including the matched employer-employee panel and cross-sectional data that we utilize, and describes our definition of local labor markets. Section 4 introduces a model of local labor markets with slow factor adjustment and presents our empirical approach, including a theoretically motivated regional measure of trade liberalization. Section 5 presents the empirical findings for our regional analysis, and Section 6 presents the empirical results in the individual analysis. Section 7 examines outcomes relating to the informal sector, and Section 8 concludes.

5
decreases steadily with salinity and shows a dramatic decline when salinity is more than 25ppt. Guran grows better with increasing salinity. Increase in salinity with climate change is likely to induce an overall shift from Sundari to lower value species (Gewa and Guran) in Sunderbans (Water Science and Technology Library 2004).

# _Expected Effects by District_

An overlay of isohalines on administrative areas of the coastal districts indicates that Barguna, Barisal, Bagerhat, Bhola, Khulna, Jhalokati, Patuakhali, and Pirojpur Districts will be affected severely by the increase in river salinity with climate change by 2050. Areas affected by expected change in river salinity, by district, for the best and the worst case future scenarios are summarized in Table 5.

The estimates indicate that even in the best case future scenario, freshwater (0–1ppt) zones will be lost entirely in Barguna, Jhalokoti, Khulna, and Patuakhali Districts. In the best case scenario, freshwater zones are expected to be reduced in Barisal, Pirojpur, and Bagerhat Districts by 85, 81, and 71 percent, respectively. In the worst case scenario, 100 percent of fresh river water in Pirojpur, 93 percent in Bagerhat, and 91 percent in Barisal will be at risk.

In addition, a serious shortage of water for dry season agriculture (water with salinity <2ppt) is envisioned with climate change. River water will no longer be utilizable for agriculture in Barguna, Bhola, Jhalokati, Khulna, and Patuakhali Districts in the worst case future scenario.

27
# **References**

- **Agarwal, Sumit, Vyatcheslav Mikhed, and Barry Scholnick** , “Does Inequality Cause Financial Distress? Evidence from Lottery Winners and Neighboring Bankruptcies,” _Working Paper_ , 2016.

- **, Wenlan Qian, and Xin Zou** , “Thy Neighbor’s Misfortune: Peer Effects on Consumption,” _Working Paper_ , 2017.

- **Akerlof, George A. and Rachel E. Kranton** , “Economics and Identity,” _Quarterly Journal of Economics_ , 2000, _115_ , 715 – 753.

- **Andreoni, James and B Douglas Bernheim** , “Social image and the 50–50 norm: A theoretical and experimental analysis of audience effects,” _Econometrica_ , 2009, _77_ (5), 1607–1636.

- **Austen-Smith, David and Roland Fryer** , “An Economic Analysis of ”Acting White”,” _Quarterly Journal of Economics_ , 2005, _120_ (2), 551–583.

- **Bagwell, Laurie Simon and B Douglas Bernheim** , “Veblen Effects in a Theory of Conspicuous Consumption,” _American Economic Review_ , 1996, _86_ (3), 359–373.

- **Banerjee, Abhijit V.** , “Envy,” in “Essays in Honour of Dipak Banerjee,” Oxford University Press, 1990, pp. 91–111.

- **and Esther Duflo** , “What Is Middle Class about the Middle Classes around the World?,”

- _Journal of Economic Perspectives_ , June 2008, _22_ (2), 3–28.

- **B ́enabou, Roland and Jean Tirole** , “Incentives and prosocial behavior,” _American Economic Review_ , 2006, _96_ (5), 1652–1678.

- **Bloch, Francis, Indrani Gupta, and Vijayendra Rao** , “Wedding Celebrations as Conspicuous Consumption: Signaling Social Status in Rural India,” _Journal of Human Resources_ , 2004, _39_ , 675–695.

- **Bursztyn, Leonardo and Robert Jensen** , “How Does Peer Pressure Affect Educational Investments?,” _The Quarterly Journal of Economics_ , 2015, _130_ (3), 1329–1367.

- **Charles, Kerwin Kofi, Erik Hurst, and Nikolai Roussanov** , “Conspicuous Consumption and Race,” _Quarterly Journal of Economics_ , 2009, _124_ , 425–467.

- **Cohen, Geoffrey L, Julio Garcia, Valerie Purdie-Vaughns, Nancy Apfel, and Patricia Brzustoski** , “Recursive processes in self-affirmation: Intervening to close the minority achievement gap,” _science_ , 2009, _324_ (5925), 400–403.

- **DellaVigna, Stefano, John A List, and Ulrike Malmendier** , “Testing for Altruism and Social Pressure in Charitable Giving,” _Quarterly Journal of Economics_ , 2012, _127_ (1), 1.

- **, , , and Gautam Rao** , “Voting to tell others,” _The Review of Economic Studies_ , 2017, _84_ (1), 143–181.

28
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COST RECOVERY, EQUITY, AND EFFICIENCY IN WATER TARIFFS IN AFRICA billing and meter reading) from the fixed part of the tariff, while the water-use part covers partial O&M costs. The fixed-cost element of the two-part tariff allows the recovery of investment costs without distorting price signals. Two-part tariffs are designed to simultaneously meet economic efficiency and cost-recovery goals (Whittington, Boland, and Foster, 2002).

About 14 utilities have designed a two-part tariff, including 13 that enforce a “fixed charge + IBT”; only NWSC in Uganda imposes a “fixed charge + linear tariff” structure. (The names of the surveyed utilities are spelled out in the list of acronyms and abbreviations on page v.) In addition to these utilities, seven utilities have a “minimum consumption + IBT” structure. Among the remaining 24 utilities, there is an interesting variety. Nineteen impose an IBT structure. Three enforce a linear structure, which means that households pay the same price per unit of consumption. These are FCT WB in Nigeria, and the NWC in South Darfur and the Upper Nile in Sudan. Two other utilities have a different tariff structure. The CRWB in Malawi charges a flat fee or fixed charge for the first 32 units of consumption, and the KIWASCO in Kenya has a U-shaped structure in which tariffs decline after the first block and rise again after the third (figure 1B and annex B).

The block structure can add to the complexity of tariffs. It can range from one block (linear) to seven, with the average being just above three blocks. Only four utilities have a single-block (or linear) tariff. At the other extreme, Drakenstein in South Africa has seven. Electrogaz in Rwanda, and Johannesburg and Tygerburg in South Africa, have a six-block water tariff structure. The MIC average is just above four blocks, while the LIC average is just under three. The most common is a three-tiered block structure; 16 utilities fall into this category. This is followed by a four-block structure; 10 water utilities in Africa exercise this tariff structure (figure 1A).

**Figure 1A. Number of blocks**

**Figure 1B. Type of tariff structure**

<!-- Start of picture text --> 20 19<br>18<br>16<br>16 15 13<br>14<br>12 10 10 7<br>10<br>5 3<br>8 6 1 1 1<br>6 5 0<br>4 3 3 Minimum consumption + IBT<br>2 1 Fixed charge+IBTIBT<br>0 Fixed charge + Linear<br>Fixed charge<br>Linear<br>U-shaped<br>Number of Utilities<br>Number of Utilities<br><!-- End of picture text --> _Source:_ AICD WSS Survey Database, 2007.

Fixed charges can take two forms: a minimum consumption charge, and a monthly fixed fee. The monthly fixed fee is evident in about 13 of the sampled water utilities in Africa. This fee is usually based on pipe size (which varies). The lower end of the range, corresponding to the usual residential pipe size of 15–20 millimeters (mm), is considered. In countries such as Benin, Cape Verde, Chad, the Democratic Republic of Congo (DRC), Ethiopia, Ghana, Nigeria, Kenya, Sudan, Rwanda, and Senegal, none of the 3
1. Individual indicators taken separately do not have a very strong explanatory power (max 15%). That is, no single endowment can explain the export matrix well.

2. The FSE and RFI are as expected (section 4) strongly correlated (Fig 7 and Table 5). 3. Results 1 and 2 imply that RFI/PRODY explains a small share of the information in the export matrix. The explanatory power of such univariate indicators is more limited than previously thought.

4. Including several variables improves the information explained by the model but not too strongly: five variables cannot explain 50% of the information. Furthermore, the multivariate elasticities are expectedly quite dependent on the other variables included in the model.

|**Table 1. Information explained by individual selected “competitiveness” variables**|
|---|

|Variable|Source|Countries|<br>Information<br>in model|
|---|---|---|---|
|GDPper capita(current US$) _log_|WDI|121|<br>0.149|
|GDP,PPP(current international$) _log_|WDI|119|0.0557|
|Liner shippingconnectivityindex 2010|UNCTAD|<br>103|<br>0.145|
|Time required to start a business(days)|WDI|125|<br>0.062|
|Natural Capital, $ per worker_log_|WDI|100|<br>0.136|
|Physical Capital Stockper Worker_log_|UNCTAD|<br>111|<br>0.145|
|Governance: Political Stabilityand Absence of Violence 2011|<br>WDI|128|<br>0.113|
|Governance: Government Effectiveness 2011|WDI|128|<br>0.118|
|Governance: Regulatory quality2011|WDI|128|<br>0.123|
|Governance Rule of Law 2011|WDI|128|<br>0.136|
|Governance: Control of Corruption 2011|WDI|128|<br>0.130|
|Governance: Voice and Accountability2011|WDI|128|<br>0.167|
|lpi score 2010|WDI|119|0.119|
|tons equivalentper unit ofgdp _log_|WDI|110|<br>0.076|

# **Table 2. Multivariate FSE estimates (two variables)**

First variable is log GNI per capita.

|Second Variable|countries|<br>Information<br>content|
|---|---|---|
|Liner shippingconnectivityindex|96|<br>0.274|
|Natural Capital, $ per worker|95|<br>0.289|
|Physical Capital Stockper Worker|106|<br>0.203|
|Governance: Political Stabilityand Absence of Violence 2011|121|<br>0.163|
|Governance: Government Effectiveness 2011|121|<br>0.186|
|Governance: Regulatory quality2011|121|<br>0.175|
|Governance: Control of Corruption 2011|121|<br>0.180|

17
childbirth compared with those who had not heard about the voucher (69 percent and 57 percent respectively), suggesting that the program not only created awareness about the vouchers but other reproductive health indicators as well. However, no significant difference was seen in knowledge of maternal health conditions between the health SPs from HealthyBaby voucher facilities who were interviewed in 2010–11 and those from nonvoucher sites (table 3).

Table 3 Percentage of Providers Interviewed in 2010–11 by Knowledge of Selected Maternal Health Conditions

|Maternal condition|HealthyBaby<br>voucher<br>facilities<br>(_N_= 63)<br>(%)|Comparison<br>facilities<br>(_N_= 49)<br>(%)|_P_value|
|---|---|---|---|
|Birth<br>preparedness<br>and<br>complications<br>readiness<sup>a</sup>|78|84|0.418|
|Danger signs in pregnancy|89|86|0.694|
|Danger signs during labor, delivery, and<br>afterward|86|89|0.659|
|Number of ANC visits women should make<br>during pregnancy|75|80|0.198|
|Gestational age at which a woman should make<br>first ANC visit|52|53|0.668|

_Source:_ Population Council, Health Facility Survey 2010–11.

_Note:_ ANC= antenatal care; _N_ = number of SPs interviewed.

a This statement was read to the respondents so they could indicate their level of knowledge regarding it.

# **<<B>>** Health Service Utilization

The net increase in private facility deliveries among women who had used the HealthyBaby voucher was greater than the reduction in public facility deliveries or home births (table 4). The proportion of private facility births among women who had ever used the HealthyBaby voucher in 22
22 Table 3 Comparion of Trade Liberalization Ease With Base Case, Beef and Pork. 1974-85

|VARIABLE|UNITS|BASE<br>CASE|TRADE<br>LIBERALIZATO|PERCENT<br>N CHANGE|
|---|---|---|---|---|
|Beef Productlon|1000 MT|1193.8|1189.3|-0.4|
|Beet Export|1000 MT|64.0|64.0|0|
|Beet Producer<br>Price|Pesos/KG|50.2|54.2|8.0|
|Per Capita Beef<br>Consumption|KG|16.4|16.3|-0.6|
|Cattle Stocks|millon head|29.487|31.180|5.7|
|Pork Productlon|1000 MT|1169|1172|0.3|
|Pork Producer<br>Price|Pesos/KG|62.1|57.1|-8.1|
|Per Capita Pork<br>Consumption|KG|16.9|16.9|0|
|Pig Stocks|millon head|16.425|16.453|0.2|

S Data are average values of variables shown over 1974-85 perlod. MT denotes metric tonts(). Price variables are In 1980 prices.