World Bank Poverty and Environment Nexus Study in Lao PDR – Some National Perspectives

World Bank Poverty and Environment Nexus Study in Lao PDR – Some National Perspectives Bjorn Larsen Environmental Economist - Consultant World Bank Claude Saint-Pierre Associate Partner,Tercia Consulting – Consultant World Bank Jostein Nygard Task Team Leader/Task Manager – World Bank Lao PDR National Consultation Workshop Vientiane, 1-2 August 2005 ERI/STEA and World Bank (EASEN)

Why are poverty and environment linkages important? Water Supply and Sanitation Natural Resources Outline of Presentation

The Government’s National Growth and Poverty Eradication Strategy (NGPES) explicitly recognizes the importance of natural resources and environmental services in poverty eradication and quality of life The Government’s definition of poverty includes important environmental dimensions such as access to safe water and sanitation Poverty and Environment in Lao PDR National Policy

The poor tend to have: Higher risk of disease (lack of water and sanitation, more frequently exposed to harmful smoke from solid fuel burning) Less access to medical services Less financial resources to pay for quality health services Less resources for averting behavior Income losses from illness (informal sector; self-employed; etc) PEN Linkages- Environmental Health

PEN Linkages- Death Rates in Lao PDR Data are at district level. Death rates are from Census 1995. Poverty incidence is from ADB.

PEN Linkages-Some findings from Vietnam PEN Study ARI in all age groups

The poor tend to: Be more dependent on natural resources Have less assets (savings) to cope with difficult times Have less education and skills for alternative income generation, and are often more economically isolated (e.g. less road access) Therefore more affected by natural resource losses (agricultural land degradation, forest degradation and NTFP losses) And are more vulnerable to shocks (drought, flooding etc) PEN Linkages-Natural Resources

Water Supply and Sanitation Water Supply - Substantial reduction in households having no water supply (surface water) or unprotected water supply - Increase in improved water supply has been mainly through protected groundwater and GFS (category: other water supply)

Water Supply and Sanitation Sanitation - Sanitation/latrine coverage is lagging behind improved water supply - Reduction in number of households having no toilet facility has been slower than the reduction in households having no improved water supply

Water Supply and Sanitation Households using Surface Water • Reliance on surface water (no improved water supply) is often found • to be a high risk factor of diarrheal illness • The poor are lagging behind. 30% continue to rely on surface water • The disproportionate reliance on surface water of the poor did not • change from 1995 to 2002/03

Water Supply and Sanitation Households with No Toilet Facility • Having no toilet facility is often found to be a high risk factor of diarrheal • illness • The poor are lagging behind. 69% of the poor did not have a toilet facility • in 2002/03 • The reduction in households with no toilet facility was larger among the • non-poor from 1995 to 2002/03

Water Supply and Sanitation Rural Households using Surface Water Rural Households with No Toilet Facility By poverty quintiles. Source: Calculated from LECS III. Quintile 1 is the poorest households.

Water Supply and Sanitation-Factors influencing coverage rates Likelihood of Using Surface Water or Not Having Toilet • Rural households are 6-7 times more likely to have no WSS (rely on surface • water and have no toilet facility) than urban households • Households with no access to road are 2-3 times more likely to have no • WSS than households with access to road • Illiterate households are 1.4-4.4 times more likely to have no WSS than • literate households Odds ratios are from logistic regression. Data are from LECS III. Note that the poor vs non-poor odds ratio is different than the figures in preceding slides. This is because the odds ratio in this chart reflects controlling for the other factors in the chart.

Why do the Factors influence WSS coverage rates? Supply side: Rural (less pollution from wastewater so urban has received priority?) No road access (higher cost of provision?) Demand side: No road access (less contact with authorities?) No education (lower appreciation/knowledge of health risk; less capacity to communicate needs?) Poor (cannot afford services and maintenance?) Water Supply and Sanitation

Sustainability of WSS Services The supply and demand factors discussed in previous slide are linked to the PEN Case Study on factors influencing the sustainability of rural WSS (MoH/ERI/World Bank) Supply side factors: Rural areas with No or Limited road access: Underscores the importance of government and donor commitment in serving poor and less accessible communities, while taking into consideration plans for village consolidation and spontaneous village migration Demand side factors: No road access (isolation), low education, and poverty: Underscores the importance of reaching out to communities, community participation in WSS options and design, awareness raising and training in WSS management, and sustainable financial mechanisms for operation and maintenance Water Supply and Sanitation

Water Supply and Sanitation Urban: Piped Water Supply Coverage in Relation to Poverty • The difference in piped water supply coverage between the poorest and • the richest is about 50% {(46%-29%)/29%} • - This difference is similar to reliance on surface water in rural areas Poverty quintiles and WSS are from LECS III. Quintile 1 is the poorest households.

Water Supply and Sanitation Urban: Household Toilet Facilities in Relation to Poverty • - The disparity between poor and non-poor households having toilet facility • is much smaller in urban areas than in rural areas • Urban coverage rate for household toilet facilities is substantially higher • than in rural areas (see earlier slide for rural areas) Poverty quintiles are from LECS III. Quintile 1 is the poorest households.

Water Supply and Sanitation Urban: Likelihood of No Piped Water or No Toilet Facility • Household illiteracy is also an important factor in urban areas in • not having piped water supply and toilet facility (after controlling • for poverty) • Illiterate households are 2.5-7.3 times more likely than literate • households of not having piped water and toilet Odds ratios from logistic regression using data from LECS III.

Water Supply and Sanitation- from Case Study Phongsaly Lamam Note: Piped water supply coverage rates by Wealth quintiles from household samples. Quintile 1 is the households with least wealth. Population Coverage rates in the two towns differs from the data in the charts. Source: URI Household Survey for PEN II study.

Dominant reason for no piped water connection: HIGH CONNECTION FEE Phongsaly: Connection fee is 500,000 kip (5 times the annual average water bill of a poor household) Lamam: Connection fee is 925,000 kip (4 times the annual average water bill of a poor household) Reducing connection fee – increasing the water tariff……….An option for increasing coverage for poor households Increasing Coverage for the Poor- Findings from Case Study in Two Towns

Critical Linkages in PEN Study: Road development - Natural Resources - Poverty Eradication Important Policy Context: -Village consolidation/focal villages/ spontaneous migration to roads -Stabilization of shifting cultivation -Forest protection Natural Resources

Number of obs = 127 districts Adj R-squared = 0.4893 LN (Poverty Incidence 1997) Coef. T-statistic* Poverty: UXO .6344309 3.58 Higher Road Access -.0052585 -2.71 Lower No Education .0136776 3.90 Higher Agric Land -.0000232 -2.16 Lower Drought97 .5803006 4.13 Higher UXO is percent of villages affected by UXOs from the UXO national survey in 1997. Road Access is the percentage of district villages within 6 km to a main or secondary road. No Education is the percentage of district population without education (Census 95). Drought97=Houaphanh+Oudomxay+Phongsaly is a dummy variable to capture the three provinces that were hardest hit by drought in 1997 (as estimated percent of population affected). Agric Land is per rural capita agricultural land (Satellite data from 1997). *T-statistic > 2.0 indicates a statistically significant association between poverty incidence and the factors in the table at a 95% confidence level. Factors Associated with Poverty- Relevant Factors for the PEN Study

UXOs and Poverty Percentage of Villages in District Affected by UXOs Source: From the UXO survey data 1997.

UXOs and Poverty Percentage of Villages in Districts Affected by UXOs In Relation to Poverty Incidence • The districts with the highest poverty incidence is by far more contaminated • by UXOs than the districts with lower poverty incidence in both the South • and Central regions Southern Region Central Region Source: Calculated from the UXO survey data 1997, and ADB district poverty incidence from LECS II (1997). Districts are grouped according to poverty incidence. Quintile 1 is the districts with lowest poverty Incidence.

UXOs and Poverty Correlation with UXO Problem • - Districts with more UXO problems tend to have less paddy rice area. Paddy • rice is an important factor for bringing households out of poverty • Districts with more UXO problems tend have less educated households. • Education is vital for poverty eradication • Districts with more UXO problems also tend to have worse health status as • indicated by higher death rates Note: All correlation coefficients are statistically significant at 95% level. Data are at district level. No education, death rate, and population density data are from the Census 1995. Paddy area is from the 1998 Agric Census. UXO data are from the 1997 national UXO survey.

Poor districts with UXO problems are at a disadvantage in poverty eradication – they have less paddy field cultivation, lower education levels, and suffer from poor health status Village consolidation and village migration need to explicitly consider UXO contamination to minimize risk of UXO accidents, identify localities with lower UXO contamination, and optimize UXO clearance for economic development Income diversification is much needed in UXO contaminated districts. Road development and education are essentials for economic integration and poverty eradication. UXOs and Poverty

Roads-Natural Resources-Poverty Percent of Villages within 6 km to Main or Secondary Road In Relation to Poverty Incidence • Only 51% of villages have access to road in the group of districts • with highest poverty incidence • -90% of villages have access to road in the group of districts with • lowest poverty incidence. Districts are grouped by poverty incidence (LECS II 1997/ADB incidence data). Quintile 1 is the group of districts with lowest poverty incidence.

Roads-Natural Resources-Poverty Correlation with Road Development • There is a positive correlation between village access to road and • agricultural development, both in terms of paddy fields and total crop • land • There is a very strong negative correlation between access to road and • evergreen forest cover • - For overall forest cover, however, the negative correlation is weak Road access is defined as main or secondary road within 6 km of village. All correlations are statistically significant at 95% level, except evergreen forest with road density.

Road development is essential for poverty eradication Over the long term, however, road development is associated with loss in evergreen forest Thus road development, and village consolidation and migration, must go hand in hand with implementation of forest protection measures to sustain NTFPs in old-growth forest which is an important source of income for both poor and non-poor households Roads-Natural Resources-Poverty

Forest Resources National Forest Cover in Relation to Poverty Incidence • There is little difference in overall forest cover between districts with low and • high poverty incidence • However, the remaining evergreen forest in Lao PDR is concentrated in • the poorer districts Forest data for each district are from 1997 satellite data. Districts are grouped According to poverty incidence (LECS II 1997/ADB district data. Quintile 1 is the districts with lowest poverty Incidence.

Evergreen Forest Resources • Districts with more villages having road access have lower evergreen • forest cover, suggesting a long-term influence of road development on • evergreen forest (this relationship is not found for total forest cover which • Includes regrowth forest) • Evergreen forest is important for some of the NTFPs with national • significance for household income Number of obs = 133 Adj R-squared = 0.3801 Dependent variable: Evergreen Forest Cover 1997 Coef. t P>t Road Access -.0019741 -4.24 0.000 UXO problem -.0441216 -0.81 0.418 Agric Land 1997 -2.38e-07 -2.55 0.012 Thai Border -.0576864 -1.85 0.067 Paddy Area 1998 -.1359547 -0.70 0.485 North -.1608625 -5.00 0.000 South .0993192 . 3.00 0.003 Forest and agricultural land data are from 1997 satellite data. Paddy area is from the 1998 Agric Census. UXO data are from the 1997 national UXO survey. Road access is % of villages In district with main or secondary road within 6 km. North and South represent regional differences not reflected in the other variables. “Thai border” is districts bordering to Thailand.

NTFPs and Poverty NTFP Annual Household Income in Relation to Poverty • Household reported income is presented in the chart below. While • self-reported income is often not very reliable, the figures suggest that • both poor and non-poor households derive significant income from • NTFPs (statistically, there is no difference in income across household • wealth groups) Households are grouped into three wealth categories based on asset scores. Group 1 is the households with lowest asset score. Source: NTFP Household Survey in Namo and Phouvong. NAFRI for PEN II.

Some findings from the NTFP Case Study (NAFRI/ERI/World Bank): NTFPs are an important source of income for poor households, and especially for upland rice farmers NTFPs are declining in supply especially in the North where there is high demand and less forest cover New villages derive less income from NTFP – is it due to reduced access to NTFPs or access to alternative income sources? Some implications: Village consolidation needs to consider possible losses in household income at least in the short term Forest protection needs to be particularly vigilant in areas with new road development. While road development undoubtedly reduces poverty in the longer run, forest resource losses may reduce household income. The finding that NTFP income is strongly correlated with upland rice farmers need to be further understood in order to minimize possible NTFP income losses with stabilization of shifting cultivation. NTFPs and Poverty

Thank you

World Bank Poverty and Environment Nexus Study in Lao PDR – Some National Perspectives