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Mission of the DCS

Managing for Development Results - Role of NSO in Monitoring and Evaluation of National Development – Dr. Amara Satharasinghe Director Department of Census and Statistics. Mission of the DCS.

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Mission of the DCS

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  1. Managing for Development Results- Role of NSO in Monitoring and Evaluation of National Development –Dr. Amara SatharasingheDirector Department of Census and Statistics

  2. Mission of the DCS The mission of the Department of Census and Statistics is to collect, compile and disseminate relevant, reliable and up-to-date statistical information required to plan a better future for our country and the people of Sri Lanka, to monitor the progress of development and other socio-economic activities and to measure the impact of various governmental policies on the economy of our country and the living standards of the people.

  3. Role of DCS in Results Based Management of National Development Programmes • DCS compiles socio-economic and demographic data for Sri Lanka • Generally these statistics are compiled at regular intervals • These statistics are useful for planning and monitoring of national development programmes • This presentation elaborates how the poverty statistics compiled by the DCS contributed to reduce poverty in Sri Lanka from 22.7% in 2002 to 15% in 2006 • The belief that Sri Lanka would not achieve MDG goal on poverty has now been proved wrong

  4. Millennium Development Goals MDG: A set of measures to bring about an improvement in living standards of the people, by the year 2015, considering 1990 as the base year • Endorsed by 189 countries at the UN Millennium General Assembly in Sept 2000 • Aim to halve the proportion of people in extreme poverty by 2015 • Set targets for reduction in poverty, improvements in health and education, and protection of the environment

  5. What is poverty? Poverty is a condition in which a person or community is deprived of or lacks the essentials for a minimum standard of well being and life.

  6. Declined from 26.1% in 1990/91 to 22.7% in 2002 Targets already been achieved in the urban sector Risen in estate sector households reaching 30% in 2002 Vary considerably across districts Under these circumstances, it was thought Sri Lanka would not achieve the MDG goal on poverty But because of decisions taken by the government based on the data compiled by DCS poverty in Sri Lanka dropped to 15% by 2006 Goal 1: Poverty eradication Headcount ratio

  7. Measuring poverty: Income poverty indicators • Poverty has been mostly measured and analyzed on the basis of a set of income poverty indicators : Headcount ratio • A person is considered poor if his or her consumption or income level falls below some minimum level (Poverty Line) necessary to meet basic needs. • This approach is very useful for defining pro-poor economic policiesrelated to income such as employment, wages, prices, taxes and subsidies policies.

  8. Measuring poverty: Income poverty indicators • Household Income and Expenditure Survey is the Source of data for estimation of poverty statistics. • Poverty statistics are disaggregated at district level and above. Sample size is not sufficient to estimate poverty statistics at DS division level or below. • DCS is therefore, conducted a special study to compile poverty statistics at DS division level

  9. Small area estimation of poverty • Household expenditure survey data cannot yield precise estimates of poverty or inequality for small areas such as DS, GN divisions, for which no or few observations are available. • Census data are more plentiful, but typically exclude income and expenditure data. • In recent years, a widespread use is seen, in use of small-area “poverty maps” based on census data, enriched by relationships estimated from household surveys that predict variables not covered by the census. • These methods are used to estimate putatively precise estimates of poverty for areaswith sampleas small as 25,000 households. • Poverty at DS division level was estimated and findings were mapped

  10. Poverty Mapping: Poverty mapping is a spatial representation of poverty and it is useful for: • Identifying areas where development lags and where investments in infrastructure and services could have the greatest impact • targeting of public expenditures by identifying areas where the neediest populations are located • State- and local-level decision-making • Increase transparency of public decision-making, by raising awareness of poverty, igniting policy debates at local and national levels, and encouraging broader civil society participation in decision-making

  11. Findings were very reaveling and useful • Areas that should be given priority could be easily seen from the map • Government selected 119 DS divisions to prioritize development programmes • Findings were even used in allocating funds to Divisional Secretariats • DCS went one more step forward to estimate poverty at next administrative level through an exploratory study

  12. Measuring poverty: Unsatisfied Basic Needs Approach- An exploratory study - • The income poverty approach deals with basic needs whose satisfaction depends mainly on the incomeability of the households to acquire these needs • There are, other important basic needs whose satisfaction depends to a large extent on factors other than income • Ability of a household to satisfy its needs such as drinking water, sanitation, health, education depends not only on its ability to pay for thembut also on their availability and accessibility

  13. Measuring poverty: Construction of UBNI • The main basic needs areas such as education, health, were defined. • For each of the area, a set of indicators was selected. • Statistically all indicators were combined into one index called UBNI. • The UBNI is a proxy continuum measure of the level of poverty. • UBNI was used to rank GN divisions according to the different states of of poverty such as very high, high, medium, low and very low.

  14. Indicators used for the construction of UBNI • Percentage of households not having improved sanitary facilities (Percentage of Households not having Water seal toilets.) • Percentage of households using kerosene for lighting • Percentage of households using firewood for cooking • Percentage of housing units not having permanent materials for wall (Materials such as Brick, Cabook, Cement blocks, etc. were classified as permanent materials.) • Percentage of housing units not having permanent materials for floor (Materials such as Cement, Terrazzo, Tile, Granite, etc. were classified as permanent materials.) • Percentage of housing units not having permanent materials for roof (Materials such as Tile, Asbestos, Concrete, Metal sheets etc were classified as permanent materials.) • Percentage of household heads who have not passed G.C.E. A/L or above • Percentage of household heads who are not paid employees (Paid employees are those who work for wages/ salaries and who work 52 weeks per year.) • Percentage household members aged 20 years and above who have not passed G.C.E. A/L and above examinations

  15. Scatter diagram: UBNI and Headcount ratio at DS division level

  16. GN divisions with highest values for UBNI (Most poor GN divisions) Most poor 15 GN divisions as measured by UBNI

  17. GN divisions with lowest values for UBNI (Least poor GN divisions) Least poor 15 GN divisions as measured by UBNI

  18. Red tones indicate high-poverty areas and Green tones are low or moderate poverty areas

  19. Poverty levels of DS (Headcount Ratio) and GN divisions (UBNI) Colombo District

  20. Poverty levels of DS (Headcount Ratio) and GN divisions (UBNI) Badulla Red tones indicate high-poverty areas and Green tones are low or moderate poverty areas

  21. Summaray • Poverty statistics at lower level of administrative units were required for planning development programmes • DCS had been compiling poverty statistics only at higher levels of administrative divisions • DCS conducted two special studies to compile poverty statistics at lower levels administrative divisions responding to the data needs • Government directly used the findings of these studies and gave priority to develop most deprived areas • Most probably this may have indirectly contributed to reduce poverty in Sri Lanka

  22. Thank you

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