rafmacalaba/data-use-mentions-extended huggingface dataset:
WPS3817

# **Unpackaging Demand for Water Service Quality: Evidence from Conjoint Surveys in Sri Lanka**

**Jui-Chen Yang, Subhrendu K. Pattanayak, F. Reed Jonson, Carol Mansfield,**

**Caroline van den Berg, and Kelly Jones**<sup>♠</sup>

### Abstract

_In the early 2000s, the Government of Sri Lanka considered engaging private sector operators to manage water and sewerage services in two separate service areas: one in the town of Negombo (north of Colombo), and one stretching along the coastal strip (south from Colombo) from the towns of Kalutara to Galle. Since then, the government has abandoned the idea of setting up a public-private partnership in these two areas. This paper is part of a series of investigations to determine how these pilot private sector transactions (forming part of the overall water sector reform strategy) could be designed in such a manner that they would benefit the poor._ _This paper describes the results of a conjoint survey evaluating the factors that drive customer demand for alternative water supply and sanitation services in Sri Lanka. We demonstrate how conjoint surveys can be used to un-package household demand for attributes of urban services and improve the design of infrastructure policies. We present conjoint surveys as a tool for field experiments and source of valuable empirical data. In our study of three coastal towns in southwestern Sri Lanka the conjoint survey allows us to compare household preferences for four water supply attributes – price, quantity, safety, and reliability. Sub-populations of poor and non-poor households are examined to determine if demand is heterogeneous. Our case study suggests that households care about service quality (not just price). In general, we find that households have diverse preferences in terms of quantity, safety, and service options, but not with regard to hours of supply. In particular we find that the poor have lower ability to tradeoff income for services, a finding that has significant equity implications in terms of allocating scarce public services and achieving universal
feasible. We discuss the existing definitions of SMEs below and explore to what extent the difference in definitions is associated with observed variation in the level of SME financing. In addition, we supplement the information on SME definitions available from the _Financial Access 2010_ survey with the information available from public sources.<sup>9</sup> The most common definitions used by regulators are based on the number of employees, sales and/or loan size. The most common among the three is the number-of-employees criterion. Sixty-eight countries provided information on the SME definition criteria used by the financial regulator. Fifty of them use the number-of-employees criterion, and 29 out of these 50 also use the other two criteria. A total of 41 regulators use maximum sales value criteria and 15 use maximum loan value criteria to define an SME (Table 2).

Number of employees and sale volumes are probably the most accurate parameters to define SME, but these data are not always available from lenders. Banks may collect this information at the time of evaluating loan applications, but often do not keep it in their systems and as a result they are not able to report lending volumes based on these criteria. As a result, some countries choose to rely on loan size as a proxy when collecting information on SME finance from financial institutions. Extracting information on loans to firms below a certain size and loans to individual entrepreneurs can be a reasonable approximation for SME lending volume. In _Financial Access 2010_ only 15 countries stated that they use loan size as a proxy for defining an SME. Similar to the definitions based on the number of employees and sales, there is a substantial amount of variation among countries.

Data availability and quality for SME lending depend on the way financial institutions and credit registries handle firm level data from loan applications, as they are the primary data collectors. Financial regulators collect these data from institutions and aggregate them. In this respect, there seems to be a need to harmonize SME definitions within each country even though such a task might
_iS_ the median height (in cm) for children of sex s and age a in the reference population; and as7a is the standard deviation in height (in cm) for children of sex s and age a in the reference population.

# III. **DATA THE GUATEMALAN SURVEY OF FAMILY HEALTH**

The data for the empirical analysis come from the Guatemalan Survey of Family Health (EGSF) conducted in Guatemala between May and October 1995.2 The survey focused on a large set of determinants of the health treatment process including the family's economic situation and social support network and women's health beliefs on the nature and causation of illness. The data collection process comprised an ethnographic study of four rural communities, an individual survey of 2872 women of ages

> 2 See Peterson, Goldman and Pebley (1995) for a thorough description of the EGSF.

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WPS3484

# The Relative Richness of the Poor? Natural Resources, Human Capital and Economic Growth<sup>_∗_</sup>

Claudio Bravo-Ortega<sup>_†_</sup> Jos ́e De Gregorio<sup>_‡_</sup> World Bank Banco Central de Chile and Department of Economics Universidad de Chile Comments welcome Comments welcome

## **Abstract**

Are natural resources a blessing or a curse? In this paper we present a model in which natural resources have a positive effect on level of income and a negative effect on its growth rate. The positive and permanent effect on income implies a welfare gain. There is a growth effect stemming from a composition effect. However, we show that this effect can be offset by having a large level of human capital. We test our model using panel data for the period 1970-1990. We extend the usual specifications for economic growth regressions by incorporating an interaction term between human capital and natural resources, showing that high levels of human capital may outweigh the negative effects of the natural resource abundance on growth. We also review the historical experience of Scandinavian countries, which in contrast to Latin America, another region well endowed with natural resources, shows how it is possible to grow fast based on natural resources.

## JEL Classification: J24, O41, O57, Q00.

> _∗_ We would to thank specially to Maurice Obstfeld for his comments that helped greatly improve our empirical work. We also would like to thank Pranab Bardhan, A. De Michaelis, Julian di Giovanni, Andr ́es G ́omez-Lobo, Botond K ̋oszegi, Patricio Meller, Ted Miguel, David Romer, J.P. Stijns and the participants of the Seminars at the Universidad de Chile, University of California at Berkeley, and at the World Bank and Central Bank of Chile joint conference on Natural Resources and Growth for their helpful comments. Claudio Bravo-Ortega would also like to thank CIEPLAN and the Ministry of the Economy for their
reduction, most notably in Asia, although there are considerable geographical, sectoral, and structural differences in the speed with which poverty reduction is delivered in the context of growth (Ravallion 2000). Growth has been found to be important specifically for increased climate change adaptive capacity. For example, examining time series data across countries over the last 50 years, Dell et al. (2008, 2009) found that higher temperatures significantly reduced economic growth rates in poor countries but not in rich countries. Raddatz (2009) showed large declines in GDP per capita from climate-related disasters in low-income countries; in percentage terms, these declines were four times the size of the declines in rich economies. Noy (2009) showed that higher GDP per capita and better institutional and human development indicators reduced losses from climate-related disasters. Raddatz (2009) also found that the larger impacts in low-income countries are much more than could be explained by the relatively high share of agriculture in these countries, so this issue is not simply solved by diversification away from agriculture. Although they are difficult to identify statistically, Fomby et al. (2012) also found losses in both agricultural and non-agricultural growth, although the type of shocks appears to affect generalizations on this issue.

Unfortunately, engineering these growth and poverty reduction processes in a world of environmental change is problematic. It is generally acknowledged that the pressures of climate and other environmental changes will have serious implications for the growth prospects of some of the poorest countries in the developing world over the coming decades (IPCC 2007; World Bank 2010a). Changes in climatic conditions will change the mean return to agriculture and increase its variance. Furthermore, the increased impacts of extreme weather events will affect the accumulation of productive assets, not least in low-lying areas such as coastal cities, where the potential returns to economic activity are 2
same districts as the zones and representative of their district. Within each district, on average 52% of firms were located inside zones. Most firms in the survey are located in India, followed by Bangladesh, Nepal, and Bhutan. The largest sectors represented among the firms are in the food sector, followed by plastics, and metals. Firms inside zones tend to be slightly younger, have more employees, and less capital than those outside zones.

Table 2 presents additional descriptives for firms within zones by the type of zone.

> 1The administrative data were drawn from the following sources: India - The Annual Survey of Industries, 2015; Bangladesh - The Bangladesh Economic Census, 2013; Bhutan - An establishment census obtained from the Ministry of Economic Affairs; and for Nepal - an establishment census obtained from the Ministry of Industry, Commerce, and Supplies.

4
average inflation rate between the ESPS and PSF surveys. The second line corresponds to the satisfaction of individual basic needs. It is computed using the average non-food per adult equivalent expenditure of households for which food consumption per adult equivalent is between 0.95 and 1.05 the nutrition poverty line. This average is added to the nutrition threshold to obtain the basic needs line. Table S1.4 reports the values of the poverty thresholds for Dakar, other towns and rural areas.<sup>6</sup>

**Table S1.4: Nutrition and basic needs poverty lines**

||Nutrition poverty line|Basic needs poverty line|
|---|---|---|
|Dakar|396|835|
|Other towns|369|647|
|Rural areas|356|558|

Source: « Pauvreté et Structure Familiale » (PSF) survey, authors' calculations. Note: Poverty lines per urbanization strata in Senegal.Values are given in CFA francs.

Using these thresholds, we can compute FGT indexes for both the PSF and ESPS surveys.

The results are reported in table S1.5. Not much difference is found between the values of the FGT indexes. PSF finds more people under the nutrition threshold (16.7% versus 12.5%), but less under the basic needs one (42.8% versus 45%).

**Table S1.5: FGT indexes for PSF and ESPS surveys**

|Index|Nutrition po<br>PSF|verty line<br>ESPS|Basic needs po<br>PSF|verty line<br>ESPS|
|---|---|---|---|---|
|Poverty headcount|0.167|0.125|0.428|0.450|
|Mean poverty gap|0.042|0.027|0.143|0.130|
|Meansquared
recipients. Thresholds for eligibility in 2022 varied from 1330/person per month in Shanghai (equivalent to USD 10/day in 2017 PPP) to 402/person per month in rural Guizhou (equivalent to USD3.7/day in 2017 PPP). The _Tekun_ assistance program is aimed at helping the elderly, the disabled, and those aged below 16 without any supporter nor source of income and who are unable to work. The Tekun beneficiaries receive basic living arrangements, tendance, medical treatment, and proper burial. In 2018, 5.28 million individuals benefited from the Tekun assistance program, with average annual benefits of 10,650 yuan for urban recipients and 6,745 yuan for rural recipients. The Dibao and Tekun programs are mutually exclusive so that an individual cannot be a beneficiary of both programs simultaneously. Dibao and Tekun are also considered as the entry to other social assistance programs, such as housing, medical and education supports. Once eligibility for these cash programs is established, a package of services is also provided, according to specific household composition and needs,

# Data and Methodology

## **Data**

We exploit several data sources, including a micro-level household survey dataset and aggregate-level statistics from administrative data. The main household survey data used is the 2018 China Family Panel Study (CFPS), which is a biennial longitudinal study with a 2010 baseline. This is a nationally representative survey that collects community, household, and individual sociodemographic characteristics of contemporary China. The estimated geographical distribution of the population using the CFPS is comparable to reports based on official data. For all estimations, we use CFPS individual weights to account for differences in the probability of selection of each group and ensure that the total weighted number of people matches with the population in the country, as reported by the National Bureau of Statistics.<sup>9</sup> The information collected is suitable for carrying out fiscal incidence analysis as it includes individual labor income, household agricultural and business operation income, household rental
# 8. Conclusion

Recent studies have focused attention on the loss of human lives and immediate birth outcomes as a result of water pollution. In a departure from previous studies, this paper underscores the long‐lasting health damages, and decreased economic capability that survivors of water pollution endure. We find a statistically significant negative effect of early‐life exposure to nitrogen pollution on women’s height in India, with supporting evidence of a decrease in child height in Vietnam, and infant HAZ scores and increased incidence of stunting in Africa. These results are robust to several checks for confounding factors. By demonstrating the long‐term effects of nitrogen pollution, our results draw attention to the critical role that local environmental spillovers play for population health outcomes and highlight the need for closer policy attention to nitrogen pollution.

The policy relevance of our results is underscored by the fact that health effects also emerge at levels well below prescribed limits, raising questions about what constitutes safe standards for nitrates in water. Emerging evidence from epidemiological studies has also found relationships between nitrate ingestion and cancer, thyroid disease, and adverse pregnancy outcomes, such as neural tube defects, at concentrations below regulatory limits (Temkin et al., forthcoming; Ward et al. 2018). Even as far back as 1977, a report by the U.S. National Academy of Sciences warned that “there is little margin of safety” in the 10 mg/L safety limit for nitrates (National Research Council 1977). More research and assessments across even more geographies and populations are needed to make definitive claims. It is possible that future research will uncover even more health effects as more data become available to link <mark>exposures that began decades ago to diseases that develop today.</mark> However, the body of evidence so far suggests that there still remains a great deal of uncertainty surrounding drinking water standards for nitrates set by environmental agencies. The magnitude of people impacted by nitrate contaminated water is, therefore, likely to be much larger than
adopted it in the early 1900s and Japan now serves as Asia’s leading example of urban development using LR. The success and acceptability of Germany’s model for LR is a result of a number of factors, including: 1) its long-standing history of well stablished property rights; 2) its streamlined and transparent evaluation and implementation process; and 3) the strong judicial system in place to address public claims.

Germany’s model provides considerable insight into establishing institutions and processes to carry out land redevelopment, recognizing their own legal framework. While many countries may not have the institutional structures to carry out LR, lessons from Germany on land valuation techniques and the evolution of price data management instruct others on how to construct a sound foundation on which to develop a comprehensive land management strategy. Adopting Germany’s model requires a cognizance of the country specific challenges related to the extent of democracy in public process, legal framework and institutional strength and technical know-how of local bodies.

One particular process that should be highlighted in the German LR process is the method of land valuation. Land valuation processes in Germany are relatively well managed and transparent (Kertscher 2004 and Seidel 2006). In Germany, land valuation processes are defined by the law. The law mandates the setting up of valuation committees, the definition of standardized market values, and the method for collecting purchase price data.

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the family depends on the actions of the adolescent girl, it might place a heavy burden on her and to cause adverse effects on her mental health.

Three potential concerns are worth addressing. First, the UCT experiment was run simultaneously with the CCT experiment. Although the two experiments were run in different EAs, beneficiaries in the UCT arm were aware of the schooling requirements in the CCT arm. The impact of the UCT arm as a „positive income shock‟ should be interpreted in this context.

A second concern might be that we are detecting a change in the reference point for mental health among program beneficiaries in Round 2 rather than an actual improvement in mental health. We see no compelling reason for this, since it would imply that the reference point (the “usual” state) of program beneficiaries was lower at the first follow-up compared with the control group. If anything, we would expect the reference point to have _improved_ for girls in the treatment group. Moreover, if the reference point had indeed changed, then the fact that the observed treatment effects did not persist in Round 3 implies that the reference point shifted back after the intervention ended. Again, this shift would have been in the opposite direction of what we would expect. This seems like an improbable sequence of events.

A third concern may be that, while the cash transfer intervention was in progress, beneficiaries found it (socially) desirable to answer our mental health questions more optimistically than the control group. Again, we have little reason to believe that our results are driven by this type of behavior. The items of the GHQ-12 are phrased such that there are no obviously correct or incorrect answers, so it is unclear what the socially desirable answer would be. Nor was there any reason for treated girls to expect that truthfully answering the mental health questions would have had any unwelcome consequences.

26
Policy Research Working Paper 8004

# **Abstract**

Since the 1990s, India has seen robust economic growth, rising wages, steady fertility decline, increased urbanization, and expanded educational attainment for males and females. But unlike other countries that have undergone similar transitions, urban women’s employment has refused to budge, never crossing the 25 percent mark. This paper fills a critical gap in policy research on women’s employment in India. The discussion is situated in the normative construction of motherhood and the gendered nature of caregiving in India. The analysis uses pooled data from six rounds of the National Sample Surveys to examine the effects of having a young child on mothers’ employment in urban India over 1983–2011. The analysis also looks at household structure, and analyzes the effects of other household members on women’s labor supply. The results show that although the onus of childbearing may have reduced, that of caregiving has increased. Having a young child in the home depresses mothers’ employment, an inverse relationship that has intensified over time. Further, living in a household with older children and women over the age of 50 is positively associated with women’s employment. These results show that the care of young children is an increasingly important issue in women’s employment decisions, in a context where formal childcare is practically nonexistent. These results have significant implications for policy to raise women’s labor force participation in India.

This paper is a product of the Social, Urban, Rural and Resilience Global Practice Group. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at mdas@worldbank.org.

_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
|**Score**|<br>**Distance to road (km)**|**Land cover**|**Lithology**|**Slope (degree)**|<br>**Rainfall (mm)**|
|---|---|---|---|---|---|
|2|750-1,000|Forest|Valley<br>Alluvium<br>and<br>Colluvium, Marsh Clay and<br>Peat, Estuarine deposit|<br> <br>5-10|600-700|
|3|500-750|N. A.|N. A.|10-15|700-750|
|4|N. A.|N. A.|N. A.|N. A.|750-800|
|5|N. A.|N. A.|Girujan<br>Clay<br>Formation,<br>Tidal Mud Deposit, Bokabil|<br>N. A.|N. A.|
|6|250-500|Agriculture|N. A.|15-20|800-850|
|7|N. A.|N. A.|N. A.|N. A.|850-900|
|8|N. A.|N. A.|N. A.|N. A.|N. A.|
|9|0-250|Human<br>intervention|Dihing, Dupitila and Tipam|>20|>900|

# **3.2. Landslide and non-landslide locations inventory**

The second step of the proposed approach is to compile an inventory of past landslide locations and develop an inventory of non-landslide locations (i.e., locations where no landslides occurred in the past). Point-based data for past landslides in the CHT and Sylhet divisions were compiled from multiple sources, including Ahmed et al. (2014),
leads to a growth in employment of approximately 5 percentage points in the overall sample, as well as for SMEs and MSMEs. We test that this is statistically higher at the 1% confidence interval than the estimate for subsample of large firms.

Overall, the results from the matched sample provide more substantive evidence for the positive effect of CB reform on employment growth. More closely aligning the treatment and control countries in their propensity to undertake regulatory reform and the overall level and growth of income produces a smaller grouping of control countries. However, the estimates for the overall sample as well as the relative size of the impact for the subsamples continue to hold.

Our second strategy to strengthen the causal impact from firm financing to employment growth relies on supplementing the credit bureau reform analysis presented above with exogenous cross-industry variation in dependence on external financing. As set out in equation (3), following Rajan and Zingales (1998), this involves estimating the effect of the interaction between the CB reform dummy and the industry level index of external finance dependence. This variable varies at the country level depending on if and when CBs were set up in a country, and further breaks down firms in reform countries by the level of external finance dependence in the sector the firm operates.

Since the external finance dependence index is only calculated for firms in the manufacturing sector, we first repeat the estimation in equation (2) (Table 6) over this subsample to confirm that the underlying effect still exists (Appendix Table A6).

In columns (5) to (8) of Table 7, we regress _Employment growth_ on _CB Reform x EFD_ and find strong evidence that the effect of CB reform does appear to vary by industry. The interaction between CB reform and the external finance dependence variable is positive and significant for the overall sample as well as for all three sub-samples. That the effect of CB 26