rafmacalaba/datause-encoder-data huggingface dataset:
from point A to point F.<sup>20</sup> Peru and Indonesia lie somewhere in the middle—the effects of their economic crises on school enrollment were generally small, and in the expected directions.

Costa Rica and Nicaragua are somewhat harder to explain. In Costa Rica, there was a reduction in school enrollment in spite of the fact that per capita income levels at the time of the crises were reasonably high (similar to Peru), although enrollment appears to have recovered quickly. Nicaragua saw an increase in school enrollment during the period of the coffee crisis in spite of the fact that it is a poor country, more closely comparable in its GDP levels to Cote d’Ivoire than to the other countries in the table. This may be explained, however, by the fact that the magnitude of the negative shock in Nicaragua was smaller than in Costa Rica or Peru, leading to a smaller negative income effect.

# _II. Child health and nutrition_

We next turn to the effects of aggregate economic shocks on child health and nutrition. As with the evidence on schooling, there are a reasonable number of studies from developing countries to draw on. A handful of these refer to Latin America, including Paxson and Schady (2005) on Peru, Cutler et al. (2002) on Mexico, Maluccio (2005) on Nicaragua, and Miller and Urdinola (2007) on Colombia. Other country-specific studies that consider the impact of aggregate economic shocks on health outcomes include Stillman and Thomas (2004) on Russia; Frankenberg et al. (1999) Rukumnuaykit (2003) and Strauss et al. (2004) on Indonesia; and Bhalotra (2008) on India. We also discuss findings from a recent study that uses Demographic and Health Surveys (DHS) to analyze the effect of positive and negative aggregate income shocks on infant mortality for 59 developing countries (Baird, Friedman, and Schady, 2007). Finally, we review the evidence of the effects of droughts on child nutritional status in Africa, including Hoddinott and Kinsey (2001), and Alderman, Hoddinott and Kinsey (2006) on Zimbabwe; Yamano, Alderman, and Christiaensen (2005) on Ethiopia; Alderman, Hoogeveen, and Rossi (2008) on Tanzania; and Jensen (2000) on Cote d’Ivoire.

> 20 The cycle of production in agricultural areas may have reinforced the negative income effect in Malawi and Cote d’Ivoire. Rainfall shocks often coincide with the harvest season, and result in reductions in household income and consumption. This is the income effect of the shock on child schooling. By the time of the planting season, however, the demand for child labor once again increases, so there is no (pro-schooling) substitution effect. Indeed, if the shock to income is severe enough, the demand for child labor during the planting season may be higher as a result of the drought, as families try to eke out more output from the farm (even if the marginal product of additional child labor is low). We thank Harold Alderman for this point.

17
environmental benefits is at least equal to, and possibly greater than its costs to the person. Using data on a large number of selections by many respondents among many plans with an array of characteristics, including varying costs of the plans, we statistically estimated mean WTP for avoided loss of forest area and reduced risk of species extinctions.

We developed the survey with the help of focus groups and individual interviews. All of the essential issues in stated-preference survey development were extensively tested in five focus groups and through a pilot survey using the same sampling frame as the one we used for the main survey (see below), following the generally accepted guidelines for survey development and stated preference valuation (Arrow, Solow et al. 1993; Dillman 2000; Bateman and Transport 2002; Hensher, Rose et al. 2015). We supplemented the pilot survey by individual briefings with a few pilot study participants, with discussions of survey details conducted with them within hours after the subjects had completed their test surveys.

# _2.2 Survey outline and valuation questions_

The survey first informed participants that its objective is to learn about the preferences of the U.S./Canadian population for the protection of the Amazon rainforest. The survey then used text in combination with the maps shown in Figures 1-3, as well as an additional map of global rainforests, to describe the Amazon rainforest and its current and projected future status. Thereafter, the survey explained, using estimates adapted from Soares-Filho et al. (Soares-Filho, Moutinho et al. 2010), future threats to forests and animal and plant species in the Amazon. The survey included pictures of selected threatened species, with hyperlinks to the names of 5
- 96 -

# Weaver, Sally M 1984

The role of aboriginals in the management of Coburg and Kakadu National Parks, Northern Territory, Australia, progress report North Aust. Res. Unit Unpubl. 22p

# Western, David 1976

A new approach to Amboseli Parks 1 (2) 1-4

# Western, David 1984

Conservation-based rural development 94-110 (in) Thibodeau and Field 1984

# World Bank 1982

Tribal Peoples and Economic Development Human Ecologic Considerations Bibliography, lllp

# World Wildlife Fund 1986

La Planada Education Project, Columbia Project Doscr. WWF-US, Unpubl.

# World Wildlife Fund 1981

Awa Ethnic Forest Reserve management plan WWF Yearbook 13p

# World Wildlife Fund 1988

Program in Wildlands and Human Needs: mid-course report WWF-US 103p

# World Wildlife Fund 1988a

Darien National Park protection and development: Panama Project Summary, WWF-US Unpubl. 2p

# World Wildlife Fund 1988b

Implementing pre-mgmt plans, Awa Reserve, Columbia Project Descr. WWF-US Unpubl.
depth -- for M2/GDP the reduction is roughly 10%; for QM/GDP, 8%. However, the tstatistics for these coefficients are significant at only at the .10-. 16 levels. 10 Table **3: Explicit Deposit Insurance and** Level of Financial Depth, 1992

|Explanatory<br>Variable|Dep**Var:**M2/GDP<br>De|p**Var:**Quasi-Money/|GDP|
|---|---|---|---|
||(1)<br>(2)|(3)|(4)|
|Constant|0.275<br>0.283|0.156|0.158|
||(7.06)<br>(7.02)|(4.52)|(4.40)|
|Per CapitaInc|0.043<br>0.043|0.034|0.034|
||(6.51)<br>(6.48)|(5.91)|(5.84)|
|Explicit Dep Ins|-0.097<br>-0.104|-0.080|-0.082|
||(1.53)<br>(1.62)|(1.42)|(1.43)|
|Avg Inflation (90-|-.004||-.001|
|92)|(0.83)||(0.27)|
|Adj. R-Squared|.49<br>.47|.44|.44|
|Observations|51<br>51|51|51|

Notes: t-statistics in parentheses. Per Capita Income measured in thousands of 1985 $US. Inflation measured as average annual percentage change in consumer price index.

Regression analysis of short-term financial deepening provides a somewhat stronger indication that explicit deposit insurance is negatively associated with financial development. Controlling again for inflation and income (both changes and levels), the dummy variable for explicit deposit insurance is negatively and significantly associated with changes in M2/GDP and QM/GDP (Table 4). The estimated coefficients indicate that, holding other factors constant, countries with explicit deposit insurance experienced 2-3% less growth in M2/GDP and QM/GDP in the three years after the program's inception than did the typical country that retained implicit insurance. The overall fit of the change in financial depth regressions is good -- income level enters positively and

> 10 Though weak, the result is somewhat reminiscent of the Denirguc-Kunt and Detragiache (1997) finding that explicit insurance is positivelv correlated with systemic banking crisis.

9
WPS3943

# **Is Cost Recovery a Feasible Objective for Water and Electricity? The Latin American Experience**

**Vivien Foster and Tito Yepes The World Bank**

# **Abstract**

One of the most commonly cited obstacles to cost recovery tariffs is the problem of affordability of basic utility services by residential households, and low income families in particular. However, a careful analysis of income distribution in the region suggests that only about 20% of Latin American households would have to pay more than 5% of their income for water or electricity services if tariffs were set at cost recovery levels. However, in the region’s lower income countries (Bolivia, Honduras, Nicaragua, Paraguay), reaching cost recovery tariffs would represent a significant affordability problem for around half of the population. Even in cases where tariffs might have to double to reach cost recovery levels, the overall impact on poverty levels in Latin America would be negligible. These results can be compared to those for India and Africa where around 70% of households could be expected to face difficulties in paying full cost recovery tariffs. In these regions, tariffs would likely have to increase by a factor of ten to reach cost recovery levels, and this could be expected to have a significant impact on poverty.

## **JEL Classification: I3, N7, H54, L95, Q25, Q4**

## **Keywords: Latin America, water, electricity, affordability, basic needs**

# World Bank Policy Research Working Paper 3943, June 2006

_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 view of the World Bank, its Executive Directors, or the countries they represent. Policy Research Working Papers are available online at http://econ.worldbank.org._ We are grateful to Marianne Fay, Antonio Estache and Jonathan Halpern for their suggestions and advice. We are particularly indebted to ADERASA and OLADE for sharing their tariff data.
the Eastern and Central Tibetan Plateau During 1961–2003. Journal of Geophysical Research 111:D19109, doi:10.1029/2005JD006915.

Lucas-Picher, P., J.H. Christensen, F. Saeed, P. Kumar, S. Asharaf, B. Ahrens, A. Wiltshire, D. Jacob, and S. Hagemann, 2011. Can regional climate models represent the Indian monsoon? Journal of Hydrometeorology 12: 849-868.

- Majra, J.P., and A. Gur, 2009. Climate Change and Health: Why Should India Be Concerned? Indian Journal of Occupational and Environmental Medicine 13: 11-16.

- Masutomi, Y., K. Takahashi, H. Harasawa, and Y. Matsuoka, 2009. Impact Assessment of Climate Change on Rice Production in Asia in Comprehensive Consideration of Process/parameter Uncertainty in General Circulation Models. Agriculture, Ecosystems & Environment 131: 281-291.

- Matsuo, K., and K. Heki, 2010. Time-variable ice loss in Asian high mountains from satellite gravimetry. Earth and Planetary Science Letters 290: 30-36.

- McMichael A.J., D. Campbell-Lendrum, S. Kovats, S. Edwards, P. Wilkinson, T. Wilson, R. Nicholls, S. Hales, F. Tanser, D. Le Sueur, M. Schlesinger, and N. Andronova,  2004. Global climate change. In M Ezzati, AD Lopez, A Rodgers, CJL Murray (Eds.) Comparative Quantification of Health Risks: Global and Regional Burden of Disease Due to Selected Major Risk Factors. Geneva: World Health Organization. pp. 1543-1649.

- McMichael, A.J., R.E. Woodruff, and S. Hales, 2006. Climate Change and Human Health: Present and Future Risks. The Lancet 367: 859-869.

- Mearns, L.O., W.J. Gutowski, R. Jones, L.-Y. Leung, S. McGinnis, A.M.B. Nunes, and Y. Qian, 2009. A regional climate change assessment program for North America. EOS 90(36): 311-312.

- Mehta, M., D.P. Dobhal, and M.P.S. Bisht, 2011. Change of Tipra glacier in the Garhwal Himalaya, India, between 1962 and 2008. Progress in Physical Geography. doi:10.1177/0309133311411760.

- Mendelsohn, R., A. Dinar, and A. Sanghi, 2001. The effect of development on the climate sensitivity of agriculture, Environment and Development Economics 6: 85-101.

- Ministry of Population and Environment (MoPE), 2004. Nepal Initial National Communication to the Conference of the Parties of the United Nations Framework Convention on Climate Change. July, 2004. Kathmandu, Nepal.

39
- 33 -

# Table 6 (continued)

||Model|1|Model|2|
|---|---|---|---|---|
|Variable|Coefficient|t|coefficient|t|
|Fiscal deficit<br>Specification<br>2|||||
|Constant|-0.7047|-2.92|-0.5629|-2.02|
|DBALAN|-0.5961|-2.06|-0.4863|-1.65|
|MSBALAN|-0.3311|-1.61|-0.5133|-2.33|
|MGDPZ|||-0.0729|-2.39|
|MSGDP|||0.3293|1.32|
|Africa|0.1622|0.65|0.2104|0.78|
|EMENA|0.2807|0.99|0.3768|1.30|
|LAC|0.1656|0.60|0.0939|0.32|
|Log likelihood||-126.35||-121.03|
|Price distortion|||||
|Specification<br>1|||||
|Constant|11.1010|1.09|7.2543|0.70|
|DOLLAR4|-0.1205|-1.19|-0.0810|-0.78|
|MSDOLLAR|-12.0760|-1.20|-8.2964|-0.80|
|MGDPZ|||-0.0685|-2.31|
|MSGDP|||0.2205|0.92|
|Africa|0.0203|0.07|0.0800|0.25|
|EMENA|0.3522|1.28|0.4013|1.43|
|LAC|0.1528|0.56|0.6023|0.21|
|Log likelihood||-128.05||-123.49|
|Price distortion|||||
|Specification<br>2|||||
|Constant|-1.0233|-5.00|-0.7556|-3.02|
|AHDOLLAR|0.0194|2.07|0.0187|2.03|
|MSAHDOL|0.0074|0.03|-0.5200|-1.76|
|MGDPZ|||-0.0791|-2.63|
|MSGDP|||0.5194|1.82|
|Africa|0.1987|0.70|0.5484|1.63|
|EMENA|0.2645|0.93|0.3725|1.28|
|LAC|0.1642|0.60|0.1002|0.34|
|Log likelihood||126.53||**-119.74**|

Note: Number of observations = 259. Asia is the left-out regional dummy.
BOTSWANA’S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE

**Figure 8. Freight carried by rail has a comparatively low unit cost in Botswana**

Unit tariff per traffic unit—average in period 2000–05 <!-- Start of picture text --> 16<br>14<br>12<br>10<br>8<br>6<br>4<br>2<br>0<br>Passenger Freight<br>Botswana Tazara<br>Gabon (Setrag) Kenya (KRC) Zambia (RSZ) Tanzania (TRC) Ghana (GRC) Madagascar ... Benin (OBN) Malawi (CEAR) DRC (SNCC) Ethiopia (CDE) DRC (CFMK) Uganda (URC)<br>Congo Brazzaville ...<br>Mozambique (CFM) Mozambique (CCFB) Senegal (Transrail) Cameroon (Camrail) Mozambique (CDN) Cote dÍvoire (Sitarail)<br><!-- End of picture text --> Source: Bullock (2009).

# Air transport

## **Achievements**

Botswana saw steady growth in its overall air passenger numbers, even during the economic crisis. Compared to neighboring Zimbabwe and Zambia, it has a relatively high per capita capacity. The aircraft fleet of Air Botswana, the main airline of the country, is one of the newest on the continent, featuring small commuter-sized turboprop aircraft (table 5). Air Botswana’s use of such efficient planes reflects the clever strategic approach to air transport services adopted by Botswana. The country is taking full advantage of its proximity to one of the most important air transport hubs in Africa: Johannesburg. Botswana does well to provide short local and regional links to South Africa, which in turn serves as the international gateway to the country.

Botswana has also spent a lot in recent years to upgrade the Gaborone and regional airports.

15
**Panel B.** In-kind benefits

<!-- Start of picture text --> 100%<br>90%<br>80%<br>70%<br>60%<br>50%<br>40%<br>30%<br>20%<br>10%<br>0%<br>Contributions Health Education Child Care Preschool and Secondary Tertiary<br>to Health Primary<br>Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5<br><!-- End of picture text --> Source: Authors’ estimates based on ECH (2017), INE and Fiscal Accounts and CEQ Methodology Notes: Quintiles are defined by per capita Pre-fiscal Income It is also relevant to consider groupings other than income to analyze public programs. This allows for a complementary scope on public policies, especially when it comes to identifying the focused support provided to the most vulnerable sectors of the population in a relatively egalitarian country. In this case, we consider both geographic regions and types of households. Since the groups comprise varying shares of the Uruguayan population, it is important to normalize the results. To keep things simple, we calculate the difference between the share (paid or received) of the observed policy and the population share of the group, divided by the population share. Thus, this population-adjusted incidence will be positive whenever a group pays (or receives) more than what a uniform distribution would imply.

When considering geographic regions, it is clear that direct taxes are being paid by the wealthier zones (Montevideo) and direct transfers are being focused at the poorer. In seen in Figure 4, Panel A, direct taxes paid in Montevideo are 65 percent higher than what they would be if they were equally distributed among the population. As for transfers, AFAM-PE and non-contributive pensions in Artigas, Rivera and Cerro Largo are 70 and 85 percent higher than their share respectively, while food and other direct transfers are more focused in the capital. Montevideo concentrates a high share of tertiary education expenditure and low shares of the other levels, while the opposite is true for the rest of the country. These results of lower economic dynamism (direct taxes), higher vulnerabilities (direct transfers and childcare education due to a slightly younger population) and lagging tertiary education and allow for a complementary view on the lag observed in the northmost region in Freire et al. (2020), for example.

Considering types of households, the weight of AFAM-PE in those with children is around three times larger than its proportion of the population, which is in line with the program’s design. Within those groups, households with only adult females are the most benefited. Direct taxes, on the other hand, are paid by households without children in a larger proportion. Finally, low and 16
# **<u>PWI</u>**

**Table 4- Domains of Personal Wellbeing Index regressed with Overall satisfaction with Life**

||Life as<br>Awhole|1|2|3|4|5|6|B|β|t|
|---|---|---|---|---|---|---|---|---|---|---|
|Constant||||||||1.726||5.93**|
|1.Standard|.672|||||||.103|.131|3.61**|
|2.Health|.331|.357||||||.047|.066|2.03*|
|3.Achive|.419|.462|.318|||||.128|.160|4.56**|
|4.Relations|.342|.345|.242|.387||||.118|.135|3.88**|
|5.Safe|.261|.274|.248|.268|.413|||.174|.190|5.69**|
|6.Community|.232|.294|.188|.158|.251|.250||.039|.053|1.63|
|7. Future<br>Security|.362|.427|.294|.357|.327|.330|.343|.065|.090|2.57*|

Adjusted R<sup>2</sup> = .298 Anova F= 49.75**

- significance at 0.01

- significance at  0.00

**Table 5- Domains of NWI for Bogotá regressed with** **<u>overall satisfaction with Life</u>**

||Life as<br>a whole|1|2|3|4|5|6|B|β|T|
|---|---|---|---|---|---|---|---|---|---|---|
|Constant||||||||4.98||25.20**|
|1.Economic<br>Situation|.232|||||||0.212|.214|4.84**|
|2.Environment|.168|.585||||||-0.034|-.046|-.314|
|3.Social|.179|.457|.595|||||-0.038|-.049|-1.11|
|4.Government|.03|.250|.321|.410||||.036|.063|1.699*|
|5.Business|.137|.399|.369|.427|.330|||.022|.034|0.86|
|6. National<br>Security|.168|.394|.444|.448|.371|.434||0.24|.037|.346|

Adjusted R<sup>2</sup> = .102 Anova F= 16.63** 67
_Intertemporal Adjustment and Fiscal Policy in a Fixed Exchange Rate Regime_ magnitude. This implies that an increase of one percentage point in the tax rate leads to an increase (about 1.4 percentage point) in exports over the medium and the long run.

The responses following a transitory shock in the foreign real interest rate (returning to its initial level after one period) are instructive. During the dynamic transitional period, capital accumulation decreases, and the real exchange rate depreciates, causing a rise in exports. These effects are not symmetric with those observed in the case of a tax increase—capital moves adversely in both cases.

# Figure 3.1 Dynamic response of Argentina’s GDP, real exchange rate, capital stock, and exports to simulated shocks

**Bold line: actual values Dash line :simulated values in sample  and out of  sample**

# **<mark>Argentina 1991:4 2001:3: Dynamic Simulations</mark>**

<!-- Start of picture text --> 72000 1.2<br>1.1<br>64000<br>1.0<br>56000<br>0.9<br>48000 0.8<br>1992 1995 1998 2001 2004 2007 1992 1995 1998 2001 2004 2007<br>GDP REER<br>700000 10800<br>9000<br>650000<br>7200<br>600000<br>5400<br>550000<br>3600<br>500000 1800<br>1992 1995 1998 2001 2004 2007 1992 1995 1998 2001 2004 2007<br>Capital Export<br><!-- End of picture text --> 26
Table 2-2 Summary Statistics for Spillover Variables that are calculated based on sources of FDI

|||Horizo|ntal_HK|Backw|ard_HK|Forwa|rd_HK|Horizo|ntal_FR|Backw|ard_FR|Forw|ard_FR|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
||Number||||||||||Std||Std|
|Year|<br>of Obs|Mean|Std. Dev.|Mean|Std. Dev.|Mean|Std. Dev.|Mean|Std. Dev.|Mean|.<br>Dev.|Mean|.<br>Dev.|
|1998|95,879|0.097|0.068|0.026|0.015|0.033|0.037|0.059|0.069|0.033|0.021|0.037|0.059|
|1999|103,945|0.106|0.070|0.030|0.016|0.036|0.041|0.075|0.073|0.036|0.023|0.041|0.075|
|2000|102,465|0.112|0.072|0.033|0.018|0.038|0.048|0.089|0.077|0.038|0.024|0.048|0.089|
|2001|114,461|0.114|0.070|0.033|0.017|0.038|0.049|0.095|0.086|0.038|0.026|0.049|0.095|
|2002|122,218|0.112|0.070|0.032|0.018|0.041|0.052|0.097|0.082|0.041|0.026|0.052|0.097|
|2003|138,158|0.117|0.073|0.033|0.018|0.042|0.057|0.113|0.089|0.042|0.029|0.057|0.113|
|2004|202,551|0.116|0.067|0.034|0.019|0.048|0.065|0.126|0.102|0.048|0.033|0.065|0.126|
|2005|194,120|0.115|0.068|0.034|0.020|0.048|0.071|0.135|0.102|0.048|0.031|0.071|0.135|
|2006|216,924|0.114|0.067|0.034|0.019|0.051|0.074|0.144|0.104|0.051|0.032|0.074|0.144|
|2007|254,905|0.109|0.063|0.033|0.018|0.050|0.074|0.139|0.103|0.050|0.031|0.074|0.139|

35
it dicult to obtain travel documents, also helped improve conditions to migrate internationally.

Figure (A.1) shows migration trends to the top ve destination countries for labor employment.<sup>3</sup> Malaysia, Qatar, and the United Arab Emirates , countries Nepal signed treaties with, are among the most favored destinations for work. India, not shown in the gure, is the largest recipient country of Nepalese workers. Due to the open border the two countries share, it is dicult to track migrants and most workers migrating to India do not report to the Department of Foreign Employment, which keeps the records. Additionally, many workers migrating to countries other than India travel through India, so labor-related migration might be signicantly higher than is ocially reported. With these outows of workers, it is not surprising that remittances have become major nancial ows to Nepal.

Remittance income has become a major factor in the economic development of Nepal. According to the Ministry of Finance (2014), Nepalese households received 430 billion and 560 billion rupees, accounting for 25.7% and 29.1% of the GDP in scal years 2012-13 and 2013-14, respectively. About 32% of Nepalese households received remittances in 2004 (World Bank, 2006). At the country level, remittances have helped sustain the balance of payments, covering 169.5% of imports and are equivalent to 82.9% of the foreign reserves in 2013 (World Bank, 2014a). This trend is likely to continue in the near future, as the growth in outows of migrant workers is on the rise. Migrant outows grew by 16% between 2012 and 2013 (World Bank, 2014a). Remittances sent through unocial channels could be as large. Thus, resource inows from abroad are becoming an increasingly larger share of household budgets to a growing number of families in Nepal.

# 2.2 Employment

International migration and paid-employment are male-dominated phenomena in Nepal. The labor migration trend by gender is presented in Figure (A.2).<sup>3</sup> Among labor-related migrants, only 6.0% (about 23,000), 6.2% (about 28,000) and 5.6% (about 30,000) of migrants were female in 2011, 2012 and 2013, respectively. In my sample, 15.6% of migrants are female.<sup>3</sup> Similarly,

> 3 Workers going abroad are required to obtain labor-permits from the Department of Foreign Employment. Migrants can apply on their own or can apply through foreign-employment recruiting agencies. The numbers reported in Figure (A.1) are those who opted to apply through the recruiting agencies and were issued the permit. Many of the females migrating abroad from Nepal tend to migrate along with their male household members and not necessarily for employment purposes. Therefore, NLSS, which asks if the household has members abroad, is likely to have a higher percentage of female migrants in the sample than reported here.

5