rafmacalaba/datause-encoder-data huggingface dataset:
# **Table 8. Climate Change Vulnerability of Countries with the Largest Poor Rural LECZ Populations**

|**Country**|**Rural LECZ**<br>**Population in**<br>**Areas with**<br>**High Infant**<br>**Mortality ('000)**|**Rural LECZ**<br>**Population in**<br>**Areas with**<br>**Malnourished**<br>**Children ('000)**|**% of**<br>**Coastal**<br>**GDP**<br>**Exposed**|**% of**<br>**Coastal**<br>**Agricultural**<br>**Area**<br>**Exposed**|**% of**<br>**Coastal**<br>**Wetlands**<br>**Area**<br>**Impacted**|**Growth**<br>**(%) of**<br>**Rural**<br>**LECZ**<br>**Population**<br>**2000-2010**|
|---|---|---|---|---|---|---|
|India|19,419.9|14,635.0|27.7%|23.6%|32.3%|20.5%|
|Bangladesh|19,143.5|19,092.3|19.0%|17.5%|24.3%|15.7%|
|Myanmar|7,791.0|3,001.2|48.9%|22.9%|50.2%|0.2%|
|Cambodia|3,306.5|1,384.5|2.7%|1.0%|1.5%|12.0%|
|Nigeria|2,175.1|450.5|22.0%|100.0%|38.8%|35.8%|
|Pakistan|1,694.1|842.9|38.6%|2.7%|61.4%|22.9%|
|Iraq|1,324.3|211.2|..|..|..|31.1%|
|Mozambique|1,041.2|265.7|55.0%|23.6%|47.1%|33.0%|
|Senegal|802.9|194.7|21.1%|2.0%|22.0%|22.6%|
|Brazil|759.6|127.4|28.5%|16.5%|11.5%|10.1%|
|China|624.7|1,117.5|17.1%|11.7%|39.8%|1.7%|
|Indonesia|416.0|4,466.6|38.7%|26.1%|27.0%|13.4%|
|Philippines|359.6|1,564.4|52.3%|30.7%|45.0%|25.0%|
|Vietnam|314.5|10,764.0|31.7%|23.8%|29.4%|11.3%|
|Thailand|9.4|955.0|31.6%|11.6%|14.7%|12.4%|
|**Total**|**59,182.3**|**59,072.9**|**31.1%**|**22.4%**|**31.8%**|**17.5%**|

The low elevation coastal zone (LECZ) is the contiguous area along the coast that is less than 10 m above sea level.

High infant mortality is 50 or more deaths within the first year of life per 1,000 births (or 500 deaths/10,000 live births). Child malnutrition counts are the product of malnutrition rates and population counts. Malnutrition rates are based on the percentage of children with a weight‐for‐age z‐score more than two standard deviations below the median of the NCHS/CDC/WHO International Reference Population. See the appendix for details on the spatial methods in calculating these coastal population distributions. Across all developing countries, the 15 countries in this table account for 92.0% of all rural LECZ populations in areas with high infant mortality in 2000 and 94.7% of all rural LECZ populations in locations with malnourished children.

Data for % of coastal GDP, agricultural area and wetlands exposed to a 1 meter (m) sea‐level rise accompanied by a 10% intensification of storm surges are from Dasgupta, S., Laplante, B., Murray, S. and Wheeler, D. 2009. "Sea‐ Level Rise and Storm Surges: A Comparative Analysis of Impacts in Developing Countries." Policy Research Working Paper 4901, the World Bank, Washington, D.C. April. Available at <u>http://econ.worldbank.org/WBSITE/EXTERNAL/EXTDEC/EXTRESEARCH/0,,contentMDK:22270368~pagePK:642148 25~piPK:64214943~theSitePK:469382,00.html</u> 22
to-face (F2F). For those in red zone areas, in lieu of going door-to-door, the field officers relied on the assistance of village/community/neighborhood chiefs<sup>15</sup> to verify household location. In addition, interviews were carried out via the Drop-Off-Pick-Up (DOPU) method, where the respondents first fill out the questionnaires on their own account. These questionnaires are then picked up by the fieldwork officers, who then proceed to verify the respondents’ answers on select key variables<sup>16</sup> via phone calls, using the quick questions format. If the implementation of the DOPU method was not feasible, then Statistics Indonesia resorted to the Computer-Assisted Telephone Interviewing (CATI) method instead.

This raises the concern that the August 2020 round is inherently different from previous Sakernas rounds, which challenges the parallel trends assumption. The different survey processes in green and red zone areas could also increase measurement errors and potentially bias our estimated COVID effect. Unfortunately, Statistics Indonesia does not disseminate the list of green and red enumeration areas.

To establish credibility in our estimates, we compare sample distributions in the August 2020 round vis-à-vis the preceding round (August 2019). Appendix Figure 1 overwhelmingly suggests a close match in the unweighted distributions of respondents by age and gender between the August 2020 and 2019 rounds.

> 15 In Indonesia, community units are referred to as _Rukun Warga_ (RW), while neighborhood units are referred to as _Rukun Tetangga_ (RT), and these are the smallest administration units in Indonesia. Each RT/RW usually consists of several households in close proximity to each other, with an elected chief who play instrumental roles in administrative functions, such as issuing family cards, individual identity cards, and reference letters indicating household poverty status.

> 16 These variables include: (1) whether the respondent has been working for the past week; (2) whether the respondent has been engaged in any income-earning activities; (3) whether the respondent has been assisting family/non-family businesses; (4) whether the respondent actually has a job/business, but has been temporarily not working in the past week; (5) the respondent’s main task in their workplace; (6) main product/services from the respondent’s occupation; (7) the respondent’s main work sector; (8) the respondent’s main work status; (9) the respondent’s income from their main employment; (10) whether the respondent has been looking for jobs in the past week; (11) whether the respondent has been preparing for a new business in the past week; (12) why has the respondent not been looking for work or preparing for new businesses, if their answer to (11) is “No”.

14
31 _Drugs_ have an imporlant role to r'.y in the care of HIV-positive patients at all stage of the disease. Many of the symptoms can be managed adequately and much relief and comfort provided with inexpensive essential drus. As regards specifc needs for drugs and supplies, for the most part they are the same essential drugs provided for primary health care througbout Ahia. In particular, needs are for antibiotia, anti-fungals, antidiarrheal and oral rehydration solutions anti-tuberculosis drugs, analgesi and antiseptics and supplies, particularly gloves The more complex and expensive drugs such r imphotericin B, acydovir, experimental drugs, and some of the anticancer drugs, require diapostic, nursing, laboratory, and management skills which are usually available only at the central teaching hospital leveL As a result, the overall economic impact of the purchase of these drugs may not be overwhelming, prvidig tbey are purchased only in quantities which can be used properly at the appropriate lewis of car. The most significant economic impact is likly to be caused by the more routine essential drugs, which wili be required in large quantitieL In view of the expected numbers of new **patients, special** effort will need to be made to procure them as cheaply as posibl, and distribute them widely. Many sexually active HIV-positive patients are willing to use condoms both as contraceptives and to protect thir partnes Provision of adequate supplies of condoms to those who know they are HIV-positive and are willing to use them should be a very high priority. Condoms were added to the WHO Model List of Essential **Drugs** in December 1987.

Decisions will soon need to be made about what conditions can be cared for at which lewls of the bealth system The fact that many of the mast commonly used drugs for HIV are provided to rural health centers sugets that with the addition of only a few drugs, treatment of some manifestations of HIV could be decentralized to a lower level, provided staff were given guidelines, training, and appropriate quantities of drugs. Management protocols for HIV are urgently needed, to prevent shortages of essential drugs from reducing the quality of care for both HIV-negative and HIV-positive patients alike. They are also needed to prevent the sense of helplessness and frustration on the part of the medical and nursing staff from expressing itself in requests for 'Whigh-tech' solutions to the problem and sophisticated drugs and test kits, or in "burn-out of medical staff. Realistic, feasible treatment guidelines and protocols would do much to reassure staff that they are doing as much as can be expected for their patients. As the epidemic spreads, some consistency of management across hospitals would reduce "shopping" and resultant double counting of cases since management would be approximately the same in most places.

# Conclusions

Shortages of drugs in Africa are caused not only by lack of funds, although in many countries this is the major reason. Poor utilization and **watap** of drug in both public and private sectors are also responsible and
[POL I(Y RESI ARCII WORKING PAPER 1448

# Summary findings

l)asgupta, Mody, Roy, and Wheeler develop comparative indices of environmental policy and performance **for** 31 countries using a quantified analysis of reports prepared for the Ulnited Nations Conference on Environment **anid** Developmentn In cross-country regressions, they find a very strong, continuous association betwcen their indicators and national income per capita, particularly whcn adjusted for purchasing power parity.

natural resource protectin. With increased urhaniaiii'ue and industrialization, countrics move from initial regulation of water pollution to **air** pollution contrnl The authors highligilt **the** importance of institutional developmcnt. Environmental regulationi **is moBre** advanced in developing countries with relatively **secuirc** property rights, effective legal and judicial systems, and efficient ptublic **administration.** Their results suggest a charactcristic progression in development. Poor agrarian economies .ocus first on This paper **-** a product of the Environment, Infrastructure, and Agriculture Division, Policy Research Depat tment -- is part of a larger effort in the department to study the relationship between environmental regulation and economic development. Copies of the paper are available frec from the World Bank, 1818 H Street NW, Washington, DC 20433. Please contact Elizabeth Schaper, room NIO-037. extension 33457 (27 pages). April 1995.

_The Policy_ **_Research_** _Working Paper_ **_Series_** _disseminates the findings of_ **_uwk_** _in pogress to encourage the exchange of idLas abIout development issues. An_ **_objectiuv_** _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_** _used and cited accordingly._ **_The findings,_** _interpretations. and conclusions_ **_are the_** _authors_ **_own_** _and should not_ **_be_** _attributed to_ **_the_** _World Bank._ its _F.recutive Board of Directors._ **_or_** _any of its mernber countries._ Produced by the Policy Research Dissemination Center
In Thailand, using the first definition of skilled workers (senior secondary education and above), average skill premiums declined over time by about 20 percent (mostly after 1994), while using the second definition skilled premiums remained unchanged. These results for Thailand are based on regressions which included 1-digit industry affiliations and the sample of all members of the household. When the alternative sample of heads of household only was used (a significantly older group of workers) which allowed for 2- digit industry affiliations, average standardized skill premiums show a decline for both definitions (more using the first definition of skill).

The results for Vietnam indicate a spectacular increase in skill premiums over time, consistent with other findings for Vietnam in this report. At the beginning of the period (1992), and before the _Doi Moi_ reforms impacted the labor market, average skill premiums were actually negative (secondary and above) or indicated a small skill premium (tertiary qualifications). Subsequently, skill premiums increased monotonically. Most of the increase took place between 1998 and 2004 (secondary and above) and between 2004 and 2006 (tertiary).

In the case of Cambodia the two definitions of skill are Lower Secondary and above and Senior Secondary and above<sup>7</sup> . Between 1997 and 2003-4, large increases in average skill premiums are observed in Cambodia for both skill definitions. Premiums more than tripled (lower secondary and above) and more than doubled (senior secondary and above). However, premiums seem to have declined somewhat subsequently, this possibly reflecting data comparability issues between the 2007 and earlier surveys. Overall, skill premiums tripled (lower secondary and above definition) / displayed a moderate increase (senior secondary or higher definition).

In China, average skill premiums have increased substantially over the 1999-2005 period (second only to Mongolia and Vietnam). Finally in Mongolia, skill premiums for both

> 7 This is because the proportion of workers with university education is small, making it difficult to estimate coefficients of skill within certain industry groups.

36
20. D. Stoll, _Fishers of Men or Founders_ of EWpire? _The Wycliffe Bible Translators in Latin America,_ (Zed Press, London, 1982).

21. M. Schminck, ed., _Frontier Expansion in_ Amazonia, (University of Florida Press, Gainesville, FL, 1984).

22. J. Grasmick, _Buffalo Law_ Review, 27,4, 759-800 (1978).

23. L. Swepston, _Buffalo_ Law Reriew, _27,4, 715-756 (1978)._ _24. C.A. da Rocha Freire,_ Indigenismo e Antropologia: 0 Conselho Nacional de Protecao aos Indios na Gestao Rondon (1939-1955), (Universidade Federal do Rio de Janeiro, Museu Nacional, Rio de Janeiro, Brazil, 1990), pp. 208-246.

25. P. Poole, "Developing a Partnership of Indigenous Peoples, Conservationists, and Land Use Planners in Latin America" (The World Bank, Latin America and the Caribbean Technical Department, Washington, D.C., 1989).

26. S. Coelho dos Santos, _Os Povos mndigenas_ e a Constituinte, (Universidade Federal de Santa Catarina, Florianopolis, Brazil, 1989).

27. M. Carneiro da Cunha, _Os Direitos do Indio:_ Brasiliense, Sao Paulo, Brazil, 1987).

_Ensaios e Documentos,_ (Editora 28. S. Davis, _Victims of the Miracle,_ England, 1977).

(Cambridge University Press, Cambridge, 29. J. Pacheco de Oliveira, ed., _Os Poderes e as Terras doe Indlos,_ (museu Nacional, Rio De Janeiro, Brazil, 1989).

30. "Terras Indigenas No Brasil" Centro Ecumenico de Documentacao e Informacao (CEDI) and Projeto Estudo sobre Terras Indtgenas no Brasil (PETI), Sao Paulo and Rio de Janeiro, Brazil, 1990, p. 9.

31. A. Wali and S. Davis, "Protecting Amerindian Lands: A Review of World Bank Experience with Indigenous Land Regularization Programs in Lowland South America" (Latin America and the Caribbean Technical Department of The World Bank, #19, Washington D.C., 1992).

32. "Terras Indigenas No Brasil" Centro Ecumenico de Documentacao e Informacao (CEDI) and Projeto Estudo sobre Terras Indigenas no Brasil (PETI), Sao Paulo and Rio de Janeiro, Brazil, 1987.

# 33. Cultural Survival Quarterly 1992.

34. J. Brooke, _The New York Times_ Sunday Dec. 1, 1991, p. 25.

35. W. Carter, _Aymara Communities and_ the _Bolivian Agrarian Reform_ (University of Florida Press, Gainesville, FL, 1964).

36. T. Caroll in Land _Reform and Social Revolution in Bolivia,_ D. Heath, C. Erasmus and H. Buechler, eds. 'Praeger, New York, NY, 1969), pp.

37. P. Van den Berghe, ed., _Class and Ethnicity in Peru (E.J. Brill, Leiden, 1974)._ _38. A. Chirif,_ America Indigena 35, 265-295 (1975).

39. C. Mora, _America Indigena_ 43, 569-584 (1983).

40. J. Uquillas and S. Davis in _Derecbos Territoriales Indigenas y Ecologia en las Selvas Ti jpicales_ de _America,_ (op.cit. note #7).
Since the results in Table 3 depend on the arbitrary threshold levels chosen by the implementing institution to accept/reject clients, we ran a sensitivity analysis moving the threshold levels between the 25th and 75th percentile (rejecting from 25 percent up to 75 percent of screened entrepreneurs, respectively). We used the whole sample of banked and unbanked entrepreneurs to carry out these sensitivity exercises. Figures A1 and A2 in the Appendix illustrate the distribution of each score and the range used for the sensitivity analysis.

**Figure 1. Sensitivity Analysis for Testing Hypothesis 1: Risk Reduction—Moving the EFL Score Threshold**

<!-- Start of picture text --> Original Threshold<br>25%* 30%** 35%** 40%** 45%*** 50%*** 55%*** 60%** 65%** 70%** 75%**<br>Thresholds (percentage of entrepreneurs rejected by EFL)<br>Difference (EFL rejected - EFL accepted) 90% confidence interval<br>10<br>8<br>6<br>4<br>2<br>Days in arrears 6 months after application<br>0<br><!-- End of picture text --> _Note:_ The figure includes only entrepreneurs who were accepted under the traditional screening method. It illustrates the difference in the number of days in arrears between entrepreneurs rejected based on an EFL score and accepted under the traditional model versus entrepreneurs accepted under both methods. ***, **, * indicate that the difference is statistically significant at the 1%, 5%, and 10% level, respectively.

Figure 1 illustrates how the difference (between EFL-rejected and EFL-accepted entrepreneurs) in the average number of days in arrears (six months after the EFL tool application) varies when moving the EFL score threshold—while keeping the traditional credit score threshold fixed. Entrepreneurs who were rejected based on their EFL score have a significantly greater number of days in arrears than entrepreneurs accepted based on their EFL score for all hypothetical threshold levels.

In Figure 2, we examine how the average number of days in arrears six months after being screened by the EFL tool changes when moving the traditional credit score threshold while keeping the EFL score threshold fixed. The implementing institution had set the traditional credit score threshold quite low (at the 19th percentile), but the results in Figure 2 suggest that the EFL tool is 15
SENEGAL’S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE

# Roads

## **Achievements**

The existing network of 18,063 km of roads is adequate to provide basic regional, national, and international connectivity, linking Dakar to international border crossings and provincial capitals in the interior. This is generally true even if Senegal’s road density indicators, both for classified and total network, are lower than African averages for low- and middle-income countries (table 3). This reflects an efficient network design that has given priority to connecting Dakar and other relatively large cities (with a population of 50,000 or more) to major ports as well as provincial capitals and cities (with populations of over 25,000).

**Table 3. Senegal’s road indicators**

||Unit|Low-income<br>countries|**Senegal**|Middle-income<br>countries|
|---|---|---|---|---|
|Total road network density|km/1,000 km<sup>2</sup>of arable land|132.1|**93.8**|318.4|
|Classified road network<br>density|km/1,000 km<sup>2</sup>of arable land|88.2|**81.4**|278.4|
|Rural Accessibility Index—<br>HH survey|% of rural population within 2 km of all-season road|34.1|**29.0**|62.7|
|GIS rural accessibility|% of rural population within 2 km of all-season road|23.1|**25.7**|31.5|
|Paved road traffic|AADT|1,341.1|**944.9**|3,797.7|
|Unpaved road traffic|AADT|38.5|**30.8**|74.7|
|Paved network condition*|% in good or fair condition|86.2|**61.0**|82.0|
|Unpaved network condition*|% in good or fair condition|55.8|**37**|57.6|
|Perceived transport quality|% firms identifying roads as major business<br>constraint|27.6|**27.4**|18.2|
|Overengineering|% of main road network paved relatively to low traffic|29.6|**19.3**|18.4|
|Underengineering|% of main road network paved relatively to high<br>traffic|13.5|**0**|20|

_Source_ : Gwilliam and others 2008. Derived from the AICD national database (www.infrastructureafrica.org/aicd/tools/data). _Note:_ *2009 data (AL).GIS = geographic information system; AADT = average annual daily traffic.

Good connectivity has been matched by a good selection of road standards in Senegal. Decisions related to whether a road should be paved or not seem to be rooted in observed traffic patterns. In fact, contrary to most African countries, there is no indication of underengineering of roads in Senegal and not even 20 percent of the roads can be classified as overengineered (this is well below the road overengineering levels observed across African countries and cited as typical examples of fiscal mismanagement) (figure 5).<sup>1</sup>

> 1 Overengineered roads are paved although traffic levels are below 300 vehicles per day—the threshold level that justifies paving. Underengineered roads are not paved although traffic levels are higher than 300 vehicles per day.

9
Moreover, precarious types of employment, such as unpaid work, are significant. Unpaid family workers represent a sixth of employment. The great majority of these workers are in the agricultural sector (Table 12). This means that farm households in the rural sector are a significant source of employment, especially for women. Agricultural employment is notoriously of low productivity, and offers low work hours. Unpaid family workers and workers in the agricultural sector have the lowest number of work hours (Table 13). In addition, there is evidence that unpaid work has been a growing source of employment in the period 2007-2009 (going from 12.7 percent of employment in 2007 to 16.8 percent in 2009), despite an overall decrease in the share of agriculture in total employment (from 49.3 percent to 47.6 percent).

**Table 12: Employment by sector in Vietnam in 2009 (%)**

|**Employment Status**|**Agriculture**|**Industry**|**Service**|**Total**|
|---|---|---|---|---|
|Employer|33.4|25.7|41.0|100|
|Self-account worker|63.3|8.3|28.4|100|
|Unpaid family worker|80.4|4.9|14.7|100|
|Wage worker|12.4|47.7|39.8|100|
|Member of cooperative|35.0|50.0|15.0|100|
|Others|0.0|48.4|51.6|100|
|Total|47.6|21.8|30.6|100|

_Source: (LFS, 2009)_

**Table 13: Average weekly work hours and standard deviation (2009)**

||Agricultural|Industry|Service|All|
|---|---|---|---|---|
|Employer|44.1|53.9|55.1|51.1|
||13.9|12.5|14.7|14.7|
|Self-account worker|36.6|44.4|48.4|40.6|
||13.8|13.9|16.7|15.6|
|Unpaid family worker|36.2|42.6|44.9|37.8|
||13.5|14.2|18.4|14.7|
|Wage work|46.5|51.2|46.2|48.6|
||14.9|9.4|11.9|11.5|
|Member of cooperative|34.2|45.8|50.0|42.3|
||12.1|15.1|20.9|16.0|
|Others|--|51.4|49.6|50.5|
||--|7.7|11.3|9.7|
|Total|37.6|49.8|47.6|43.3|
||14.2|11.1|15.0|14.9|

_Source: (LFS, 2009)_ 16