rafmacalaba/datause-encoder-data huggingface dataset:
- 42 -

The simple level of engineering related fuel choice is that which focussed solely on the characteristics of the planc itself, while the more detailed utudy looks at the whole context in which a fuel choice li to be made. Examples of both approaches are discussed in some detail oince they illustrate both how the approach ie used and its strengths and weaknesses.

Non sito specific Choice of Power oeneration echanoloav Many studies of the power market attempt to compare different fuels together with the dlfferent technologles available in order to make predictions about future fuel use. One very recent study by Moore and Crousillat (19911 looks at the prospects for gas-fueled combined cycle power generation with specific reference to its future use in developing countries. The conclusions to the study indicate the attempt to draw general conclusions. The advantages are claimed to bet

- (a) a lower capital cost of about $600/kw compared to steam thermal at $800-1500/kw, depending on whether lt is conventional (coal or oil) steam of coal fluidized bed and on the degree of stack emission control equipment;

- (b) thermal efficiency of about 50O compared to 40% or less for the alternatives;

- (c) better environmental performance;

- (d) shorter construction timel

- (e) shorter startup and loading times.

The disadvantages are:

- (a) the limited fuel-switching capability compared to a conventional steam unit, which can be designed for gas, oil and coal firing;

- (b) poor operating performance so far in developing countries largely associated with inadequate preparation for the transfer of the high technology system.

In addition it was shown that for under sensitivity analysis the gas fueled combined cycle plant was least cost over a wide range of situatlons.

The study takes 1994 as its commissioning date for new plant and coneLders base load systems with gas combined cycle or coal or oil alternatives for both large (5000 MW) and small (1000 MW) installed capacity systems. It does not make allowance for high altltude or high ambLent temperature, both of which
19 40% of the power in the wind into rotary power. In remote locations with mean monthly windspeed in excess of 3 m/sec, wind can be the most economic power source for water pumping.

56. Since 1979, significant operating experience with PV pumping has been gained through UNDP and USAID funded projects. Major projects include the Mali Aqua Viva Program, Desert Development in Egypt, Solar Pumping in Botswana, Remote Village Water Supply in India, and the UNDP Pump Test Project. Small PV pumping systems are in place throughout the Carribean, Africa, South and Southeast Asia.

57. In the developing world, wind pumps are produced in Kenya, Ethiopia, Mall, South Africa, India, Pakistan, China, Thailand, Philippines, Peru, Argentina and Brazil. Data on installed windpump capacity has not been gathered on a global scale. Nonetheless, as over 50 known windpump manufacturers were operating globally in 1983 (20 for more than 20 years),<sup>2</sup> '/ it is evident that the industry serves a significant global market.

<!-- Start of picture text --> Village Water Supply Power Source Costs<br>20 Liters/capita, head = 40m<br>Power source costs only ($/m3)<br>Diesel 0 15c/l<br>1.2 I Diesel 0 45c/1<br>l \ind 0 3m/sec<br>Wind W 0 4mn/sec<br>0.9 _ 3< PV 0 4kWh/mt2<br>-0 PV@ S kWh/zn2<br>0.8-x<br>0.3. I<br>100 300 500 700 900 1100<br>Village Population<br><!-- End of picture text --> Figure 8 Village Water Supply Costs: PV, Wind & Diesel IT Power LTD, Wind Technology Assessment Study, Vol 1, pp 16, February, 1983.

21/
20 conditions are "worst-case," i.e., conditions on days when the highest ozone levels are observed. In the unlikely event that changes in precursor emissions occurred at night, effects.on ozone could probably be ignored. To say more about temporal considerations requires considering which temporal measures are the most important determinants of health effects. Even if one does not intend to predict such effects, the analysis will be more informative if the concentration measures used accord with the measures thought to be most closely linked to health effects.

One can obtain some idea of these measures by referring to the measures used to express U.S. ambient air quality standards, which are set to protect health with a margin of safety. Staying with ozone, the most important temporal measure is the maximal one-hour average for the day. This measure is used to express the ambient standard and is used by all of the available epidemiological studies linking ozone exposure to acute health effects.12 Because of this and for other reasons, there are shortcut approaches to linking emissions to concentrations. Dowlatabadi, Krupnick, and Russell (1991) report on a variety of "ozone sensitivities" in the literature, which relate the percentage change in an ozone precursor (either HC or NOX or both) to the percentage change in daily maximum ozone readings. Ozone isopleth diagrams also are available for this purpose. However, the initial fraction of each precursor emitted by mobile sources and baseline ambient HC/NOX ratios must be known to compute the ozone effects and such diagrams are unlikely to be available for cities in developing countries.

12. There are no studies of chronic effects or of the ozone-mortality link.
. 12Table 4. Mean Consumption for Households Uving In Peru by Deciles Decomposed with respec **t** o Females, Males and Chilcrens Wage Eamings and with respect to the Households Net Entrepreneurial Income and Other Income

|Decile|Mean<br>|Dec<br>wa<br>|ile specfic<br>ge eamin<br>|mean<br>as for<br>|Decile<br>specific<br>mean net<br>entrepreneuria<br>|Decile<br>specfic<br>mean of<br>l other|
|---|---|---|---|---|---|---|
||household<br>consumption|Female<br>(15-70)|s Males<br>(15-70)|Children<br>(7-14)|income<br>for househ|Income<br>olds|
|I .................<br>|397<br>|13<br>|40<br>|2<br>|324|18|
|2 .................<br>|1,700<br>|80<br>|222<br>|15<br>|1,296<br>|87|
|3 .................<br>|3,443<br>|192<br>|793<br>|27<br>|2,268<br>|163|
|4 .................<br>|6,077<br>|387<br>|1,964<br>|42|3,270|394|
|5 .................<br>|9,478<br>|884<br>|3,634<br>|29<br>|4,203<br>|718<br>|
|6 .................<br>|13,643<br>|1,367<br>|6,086<br>|63<br>|5,244|883|
|7 .................<br>|19,082<br> <br>|1,741<br>|8,220<br>|35<br>|7,630<br>|1,456<br>|
|8 ..........<br>|.......<br>27,073<br>|4,665<br>|10,902<br>|214<br>|10,723<br>|1,924<br>|
|9 .................<br>|41,140<br>|4,718<br>|15,592<br>|53<br>|16,970|3,807|
|10 .................|302,982|20,460|31,874|326|242,670|7,651|
|All .................|42,500|3,315|7,948|85|29,461|1,691|

Note: Intis at June 1985 prices.

The results In Table 3 show that the Inequality In the distribution of consumption Is considerably higher In rural areas than In Uma, even though hours of work were more equally distributed In rural areas. To obtain Information on why inequality varies across distributions, we will examine the Impact of different income sources on overall Inequality. By dacomposing the inequaliy in the actual distribution of consumption by males, females, and children's wage earnings, and by households' net entrepreneurial Income, we may see why the consumption distributions differs across regions. By applying the decomposHion method for the A-coefficient, we obtain the results In table 5. The Interpretation Is analogous to the Interpretation of table 2. To give an Impression of the variations behind the coefficients for Peru In table 5, table 4 displays mean household consumption by deciles, corresponding meani earnings for males, females, and children, mean entrepreneurial household Income and mean other income for each decile. Since the decile-specffc mean wage earnings for females Increases wHth Increasing deciles, the corresponding Interaction coefficien **t** akes a large posHitve value, which Is In accordance wHh the estimate (0.842) In table 5. But If the decile-specHfic means are equal, then the corresponding Interaction coefficient would become zero or approximately zero.
# **III. Growth in Agricultural Trade**

World agricultural trade in 2000/01 was $1,014 billion, up from $385 billion in 1990/91.<sup>5</sup> Table 2 shows the growth rates of world exports. Real manufacturing export growth increased at similar rates during the two periods (about 8.5 percent p.a.). Agricultural trade on the other hand, decelerated significantly from close to 6 percent p.a. to 1.5 percent (table 2). Developing country export rates also decelerated both for agriculture and manufacturing. For manufacturing the decline in growth rates are modest, from a very high rate of 14.6 percent p.a. to 12.3 percent p.a. These are both very high rates. For real agricultural export growth, the decline is much larger. Annual export growth rates decline from 7.5 percent p.a. to only 2.7 percent p.a.<sup>6</sup>

**Table 2. Average Annual Real Export Growth Rates, 1990/91- 2006/07**

||World E<br>|xports (%)<br>|Tot<br>|Develo<br>al<br>|ping Countrie<br>Developi<br>Developing<br>|s Exports (%)<br>ng to<br>Countries<br>|<br>Develo<br>Industrial<br>|ping to<br>Countries<br>|
|---|---|---|---|---|---|---|---|---|
|Sector|1990-91/<br>2000-01|2000-01/<br>2006-07|1990-91/<br>2000-01|2000-01/<br>2006-07|1990-91/<br>2000-01|2000-01/<br>2006-07|1990-91/<br>2000-01|2000-01/<br>2006-07|
|Agriculture|5.7|1.5|7.5|2.7|15.0|4.5|4.4|1.1|
|Manufacturing|8.5|8.4|14.5|12.3|22.4|15.8|11.8|9.7|

Notes: Manufacturing imports are adjusted by the manufacturers' unit value; world agricultural trade are adjusted by agricultural commodity price index with world trade weights, and developing country agricultural exports are adjusted by the same index with developing country trade weights. Manufacturing is defined as SITC (5+6+7+8-68) and agriculture as SITC (0+1+2+4-27-28) in Revision 3. Industrial countries include Australia, Canada, EU15, Iceland, Japan, Norway, New Zealand, USA, and Switzerland; developing countries are included the rest of world excluding 23 industrial countries. Sources: Based on mirror data from UN COMTRADE Statistics and World Bank Commodity Price database.

When one looks at the components of the agricultural export growth rates for developing countries, there is a deceleration in their export growth rates to both developing and industrial countries. Export growth to other developing countries decrease from 15 percent p.a. to only 4.5 percent. Still, the growth rates to other developing countries are much higher at 4.5 percent p.a. versus only 1.1 percent for the exports to industrial countries.

> 5 Agricultural trade and output show large year to year fluctuations. To minimize the variance, we use two year averages throughout the paper.

> 6 One should remember that the price indices we use show a very large increase in the end years of 2006 and 2007. If the prices are overestimated, the deflated real values would be understated generating lower growth rates for the period.

5
Differences in Monthly Earnings: After Controlling for Individual Characteristics (Relative to West Java) _<u>(Percentages)</u>_

|**Province**|**Teachers**|**Other paid workers**|**Difference**|
|---|---|---|---|
|DI Aceh|3.3|-8.3**|-11.6|
|North Sumatra|10.2+|-7.0**|-17.2|
|West Sumatra|8.7|-6.7**|-15.4|
|Riau|5.2|20.9**|15.7|
|Jambi|4.2|-8.6**|-12.8|
|South Sumatra|17.3*|-3.7**|-21.1|
|Bengkulu|-1.6|-23.3**|-21.7|
|Lampung|-2.8|-17.6**|-14.8|
|Bangka Belitung|-13.8|-0.2**|13.6|
|DKI Jakarta|11.9+|21.6**|9.6|
|Central Java|-14.7**|-22.8**|-8.1|
|DI Yogyakarta|-4.0|-29.1**|-25.0|
|East Java|-23.0**|-16.5|6.5|
|Banten|-10.9+|16.0**|26.8|
|Bali|2.3|-6.3**|-8.6|
|Nusa Tenggara Barat|-14.1*|-29.8|-15.7|
|Nusa Tenggara Timur|13.3+|-20.3**|-33.6|
|West Kalimantan|25.0|17.3**|-17.2|
|Central Kalimantan|-9.4|1.5**|-7.7|
|South Kalimantan|16.1+|23.5**|10.9|
|East Kalimantan|30.0**|4.5**|7.4|
|North Sulawesi|8.0|-9.6**|-25.6|
|Central Sulawesi|-5.7|-5.7**|-17.6|
|South Sulawesi|-0.8|-13.4|0.0|
|Southeast Sulawesi|7.8|-22.4**|-12.7|
|Gorontalo|34.6**|-0.3|-30.2|
|North Maluku|21.3|22.7**|-35.0|
|Papua|88.1**|53.2|1.4|

_Source:_ Analysis of Sakernas 2004. _Note:_ Conditional differentials are derived from the coefficients on the dummy variables for provinces in the multivariate regression of earnings (that is, 100*(exp( _b_ )-1), where b is the province-specific dummy coefficient estimate. Sample of workers with secondary schooling or more. +, *, ** denote significance at the 10 percent, 5 percent and 1 percent levels.

40
# **Table 9: Cross-Country Comparisons of Costs of Software Services**

|**Country**|**Cost per fine o**|**f code**(UJS$)|**Average salary of p**|**rogrammer**(tU$$|
|---|---|---|---|---|
||**Development**|<br>**Support**|<br>**Development**|<br>**Support**|
|**United States**|18|1.1|46,550|43,395|
|**ICanada**|**10**|0.6|35,156|33,846|
|**Australia**|NA|NA|34,940|30,644|
|**Japan**|2 1|1.2|NA|NA|
|**Austria**|NA|NA|33,000|33,000|
|**Denmark**|**1**9|1.1|NA|NA|
|**England**|**1 1**|0.7|38,785|38,179|
|**France**|**1**3|0.8|36,750|41,250|
|**Germany**|22|1.3|42,058|34,848|
|**Greece**|6|0.4|NA|NA|
|**Ireland**|1**0**|0.6|NA|NA|
|**Italy**|10|.6|17,655|17,655|
|**Netherlands**|NA|NA|33,994|47,069|
|**Scotland**|NA|NA|24,842|NA|
|**Switzerland**|27|1.6|48,869|48,869__|
|**Israel**|**1 1**|0.6|NA|NA|
|**Estonia**|NA|NA|12,000|8,000|
|**Brazil**|NA|NA|20,032|20,032|
|**Colombia**|NA|NA|NA|16,000|
|**Mexico**|NA|NA|10,843|13,292|
|**Rep. of China**|NA|NA|28,266|16,366|
|**_INDIA_**|**_5_**|_0.3_|_3,638_|**_4,316_**|

_Note:_ Data refer to 1996-98 averages.

**_Source._** Adapted from Rubin (1999).

39
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POi Icy RESEARC H 'QORKING, PAIPER 1909

# Summary findings

Firms in developing countries are often said to have no incentives to invest in pollution control because they typically face weak monitoring and enforcement of environm ental regulations. But the inability of formal institutions to coontrol pollution through fines and penalties may not be as serious an impedirnent to pollution control as is generally argued, contend Dasgupta, Laplante, and Mamingi.

Capital markets may react negatively to news of adverse environmental incidents (such as spills or violations of permits) as well as positively to the announcement that a firm is using cleaner technologies. The authors assess whether capital markets in Argentina, Chile, Mexico, and the Philippines react to the announLcemenit of iei-m-specific envirormITeor1al news. They show t1lat:

> eCapital markc-ts react pos:tivel (the firms market value increases) ro _tie_ announcemenit of rewards and explicit recognition of superior environmenrta: performance.

**_*_** They react necgat:vely (the firns' vale decreases) to citizens' complaimns. Enviroinmelltal regulators in developi:ng count1ries could (1) harness mlarket forces **he** introduci:g structured progr:ams to release f-rm-specific inforrnati.)n aboet environtrrienral ncrformarnce, and (2) empower and SMaell(:.de2-S thrOLg`1 crl - acllral education progralmris.

This paper-a product of the Development Research Group-is part of tie group s ongo1ing xwork on inderiai pollution and also to study whether capital markets in developing counitries can proi-Lde ,nccnltives needed for pollutioni control. The study was funded by the Bank's Research Support Budget under the research project "Incentives for P)oluotionl Control: 'The Role of Capital Markets" (RPO 680-76). Copies of this paper are available free from the World Bank, 18 1.8 H Srtreet NW, Washington, DC 20433. Please contact Roula Yazigi, room \IC2-622, telephon,o D2.)-473-7176, fax 2d2-f2.)-3230, Internet address rvazigiCa worldhank.org. April 1998. (36 pages) _The Policy Research 'Working Paper Series dlsseminates the fin-,diZgs of l,ork 11_ **_'lr_** _'!' 'o t'ec ' 'ha r'_ a _de-elopment issiues. Aln objective of the series is tO get the findinigs out quickly. *s' it t,;r""l_ **_-Cn'''7tiI'Ž_** _or;e feesstho; 'ik papers carn the narmes of the authors anzd should be cited accordingyb. The indoi gs. 'i0!l O)i is._ **_0i:_** _paper are entirely thcose of the autho,s. The;' do not necessarily represent the_ **_lO_** _/(t "'h_ N **_i"_** _' iWnkBa. its 1i'leo :_ ' **_'''''<_** _i, j coo0ntr:es they represent._ Produced bv the Policv Research Dlsseminralon (Clorer
exported, although much of this comes not directly from the farmers but through auctions or through traders.

**Table 13: Agricultural sales by households in Nepalese districts (share of total agri sales), 2010**

|Ilam<br>Product|**Share**|Jhapa<br>**Product**|**Share**|Panchag<br>**Product**|arh<br>**Share**|
|---|---|---|---|---|---|
|**Milk**|29.4%|Tea|35.1%|Rice|65.1%|
|**Ginger**|27.6%|Main paddy|26.9%|Wheat|8.5%|
|**Other cash crops**|13.1%|Milk|6.9%|Jute|4.2%|
|**Cardamom**|5.4%|Spring/winter maize|6.6%|Sugarcane|3.1%|
|**Tea**|5.2%|Early paddy|6.2%|Tomato|3.0%|
|**Winter potato**|4.1%|Meat|4.9%|Tumeric|2.8%|
|**Meat**|3.0%|Wheat|3.3%|Oilseed|2.1%|
|**Orange**|2.0%|Summer maize|1.7%|Maize|2.1%|
|**Summer vegetables**|1.9%|Curd|1.5%|Green chilli|2.1%|
|**Black gram**|1.6%|Winter vegetables|0.9%|Other Fruits|1.6%|
|**Winter vegetables**|1.0%|Summer vegetables|0.8%|Pulses|1.4%|

_Note: The totals exclude sale of live animals Source: Nepal Living Standards Survey 2010 and Bangladesh Household Income and Expenditure Survey 2010_ Most of the tea in India and Nepal is sold through captive markets: more than 80% of producers sell their product to a single market. Bangladesh is different in that more than half of the farmers sell to two or more markets (Table 14). Indian and Nepalese producers, therefore, do not have much choice on where to sell whereas those in Bangladesh appear to have greater options. The availability of choice on where to sell products is important to how logistics systems are organized in the different markets – where there is little choice this can be a function of state intervention in agricultural markets or the influence of transport and market infrastructure, or both. For instance, where the authorities organize auctions then the market outlets can be limited. On the other hand where choice is available, there can be competition between markets which could result in poor coordination especially between small scale producers to enable them to reduce unit logistics costs.

**Table 14: Number of markets served (%)**

||**Bangladesh**|**India**|**Nepal**|
|---|---|---|---|
|1|47|82|80|
|2|33|18|13|
|3|13||5|
|>3|7||2|

_Source: Field Survey_ The main markets for Siliguri tea (95 percent) are inside India, mainly Bihar, West Bengal and Madhya Pradesh, according to the response of the officials interviewed. There is no outsourcing of tea from Nepal. This can be seen in Table 15, which shows that tea is purchased mainly in farmgate, own premises and district markets while none of the respondents purchase them across borders in Darjeeling. This is very much the same pattern in Nepal.

22
among hospitalised children (Kalter et al, 1989). The diagnosis produced by the algorithm on the basis of an interview with the mother of the dead child was compared with the diagnosis reached by a physician. It was found that the algorithm for measles and that for diarrhoea achieved high sensitivity and specificity, but that for acute lower respiratory tract infections only gave high sensitivity at the expense of specificity and vice versa. Whether sensitivity or specificity is more important must be determined by the clinical situation in each case.

In a review of health interview survey methods, Kroeger (1983) points out that the degree of correspondence between health interviews and validating examinations decreases as the difference between the layperson's and the physician's concepts and terminology increases. Zimicki (1989) supports this with the finding that the lay-reporting system works well for conditions such as diarrhoea where the diagnosis and the perception of the illness correspond.

# 4.7 Presentation of data

Methods of data presentation should be chosen with regard to their value for policy makers. Whatever classification scheme is decided upon, it is likely that a range of differing categorisations of cause of death would be incorporated in the survey report. Causes might. for example, be grouped according to the availability of cost-effective preventive or curative interventions. Such a categorisation might be of special value to policy makers invoived in decisions on resource allocation in the health sector.

The raw data from a survey of adult mortality would provide information on proportionate mortality rates, in other words, the proportion of adult deaths attributed to each cause. If combined with an estimate of the overall adult mortality rate, which could be obtained from the same survey using indirect demographic methods, overall cause-specific mortality rates could be estimated.

The data should also be tabulated by sex and by broad age-groups, giving age- and sex-specific proportionate mortality and cause-specific mortality rates. It is likely that the distribution of causes of death varies considerably with age and sex, as illustrated in Section 2.4. Geographical variations in rates may also be of interest. There are, however, limits to the subdivision of data given the limited number of deaths likely to be available for analysis.

Proportionate mortality analysis essentially gives ,equal weight to all adult deaths. An alternative is to present causes of death according to person years of life lost (PYLL) from each cause, thus giving more weight to deaths occurring early in adulthood. Two examples of this approach are illustrated in Table 9.

The first is based on deaths occurring in state caoitals in Brazil in 1984. In this study, a maximum age of 70 years was used to define "premature mortality", and so the persons years of life lost for each death was calculated as 70 minus the age of the deceased. The choice of 70 years is, of course, essentially arbitrary, and different limits have been used in different studies. Childhood deaths were included in the 25