5a Indonesia case study

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Poverty Mapping Efforts in Indonesia: 

Poverty Mapping Efforts in Indonesia Asep Suryahadi The SMERU Research Institute www.smeru.or.id

Outline of Presentation: 

Outline of Presentation I. Past Efforts to Map Poverty II. New Poverty Mapping Initiative III. Uses of Poverty Maps IV. Key Problems and Challenges V. Recommendations

I. Past Efforts to Map Poverty: 

I. Past Efforts to Map Poverty Poverty reduction was never stated as development goal until 1994 In Pelita VI, four major poverty reduction programs were launched Two major efforts to map poverty were initiated: - IDT Program - Family Welfare Development Program

IDT Program: 

IDT Program Presidential Instruction on Disadvantaged Villages Targeting approach by classifying villages into poor (backward) and non-poor The classification was based on Podes (Village Potential) database Distribution of poor villages was strikingly different from distribution of poor people

Family Welfare Program: 

Family Welfare Program Managed by Family Planning Agency (BKKBN) Target households  5 welfare status: KPS, KS I, KS II, KS III, KS III+ During crisis, used for targeting of social safety net programs Contributed to mistargeting of program beneficiaries

Poverty Census: 

Poverty Census To assess poverty status of all households  more suitable for program targeting Too expensive  3 Provinces: Jakarta, East Java, South Kalimantan Conducted simultaneously with Population Census 2000 Used indicators to determine poverty status

Poverty Statistics: 

Poverty Statistics Based on Consumption Module of SUSENAS, 3 yearly since 1976 Representative at province-urban/rural Regional autonomy requires district level poverty statistics  based on Core SUSENAS: - aggregate consumption questionaire - no quantity and price information

II. New Poverty Mapping Initiative: 

II. New Poverty Mapping Initiative A new method combining detailed information from household survey and complete coverage of population census  simulated-welfare mapping Two stages: - using survey data, estimate correlation pattern - using census data, used the estimated pattern to predict consumption

Slide9: 

Simulated Welfare Mapping Method Census Survey For census household: predict per capita expenditure and error margin Econometrics

The Pilot Study: 

The Pilot Study The new poverty mapping method was introduced in a seminar at BPS in June 2001 BPS, SMERU, and World Bank collaborate in an effort to apply the method Two phases: - Pilot study of 3 Provinces: East Kalimantan, Jakarta, East Java - Application to the rest of provinces

Data Sources: 

Data Sources Consumption Module SUSENAS 1999 Core SUSENAS 1999 Population Census 2000 Podes 1999

Implementation Procedure: 

Implementation Procedure 1. Matching variables in survey and census 2. Selecting explanatory variables 3. Estimating the model 4. Simulations on census data 5. Calculation of poverty indicators

Results: Successful Replication: 

Results: Successful Replication

Slide14: 

Poverty Maps of East Kalimantan

The Importance of Error Margin: 

The Importance of Error Margin

Precision of the Estimates: 

Precision of the Estimates

Standard Error & Population Size: 

Standard Error & Population Size

III. Uses of Poverty Map: 

III. Uses of Poverty Map Capturing heterogeneity of poverty Improving targeting of interventions Articulating policy objectives Communicating distribution of welfare Evaluating impact of programs Incorporation into GIS

Benefit Relative to Other Methods: 

Benefit Relative to Other Methods Higher resolution poverty maps Based on direct measures of welfare Provide measure of precision Use existing data

Promotion of Poverty Map: 

Promotion of Poverty Map Easy access Seminar and workshop Application to other welfare indicators

Poverty Map Sustainability: 

Poverty Map Sustainability Initial production is externally driven Internalizing needs for poverty maps

IV. Key Problems & Challenges: 

IV. Key Problems & Challenges Limited technical expertise Integration of BPS & other institutions data Perception of usefulness of poverty maps

V. Recommendations: 

V. Recommendations Training and workshop Networking Facilitating data integration Supporting upstream and downstream research