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Application of a small area estimation method to make better use of existing data in Bangladesh Nobuo Yoshida April 20, 2011.

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Presentation on theme: "Application of a small area estimation method to make better use of existing data in Bangladesh Nobuo Yoshida April 20, 2011."— Presentation transcript:

1 Application of a small area estimation method to make better use of existing data in Bangladesh Nobuo Yoshida April 20, 2011

2 Demand for more frequent and disaggregated poverty data is rising  In many developing countries, including LICs, demand for more frequent and disaggregated poverty estimates is rising  More countries produce poverty estimates at the sub-national levels  Also, many countries try to produce poverty data more frequently

3 To produce more frequent and disaggregated poverty data (i)  A more direct approach is to  Increase frequency of household surveys  Increase the sample size  Pro  Estimation method is straightforward  Cons  Costly  Increasing non-sampling error

4 To produce more frequent and disaggregated poverty data (ii)  Apply a small area estimation method developed by Elbers, Lanjouw and Lanjouw (ELL) (2003)  Pros  Cheap  Decreasing the non-sampling error  Cons  Fairly complex method  Increasing error in execution of the method

5 What is the ELL method?  Two main features  Impute consumption in CENSUS/CWIQ without it  Imputation models are estimates in a large multi-topic survey including both consumption and other indicators

6 What is CWIQ?  CWIQ (Core Welfare Indicators Questionnaire) survey  Invented to collect data for producing simple indicators  Intended to use it for quick data collection and collect a large sample  Consumption or income is not recommended to be included  Useful to monitor simple inputs, process and output indicators  CWIQ is similar to Census in the following senses:  Questionnaire must be simple  Sample size is large  No complex welfare indicator like consumption or income

7 How does ELL work? CX X LSMS Census/CWIQ C=F(X) Ĉ =F(X) Develop imputation model Regress C on X C: Consumption X: Other indicators like employment, education Ĉ =F(X): Imputed (or predicted) Consumption

8 Pros and Cons  Data without consumption is cheap and easy to collect  It is easy to increase the sample size and frequency  Census is collected anyway (zero additional cost)  Implementing CWIQ is much cheaper than LSMS  But, new errors “imputation error”  Need to make efforts to find good imputation models

9 Application to poverty estimation at the village level HHLD selected by LSMS (3 hhlds) HHLD not selected by LSMS, but in Census (21 hhlds) Village A Ĉ ĈĈ Ĉ Ĉ Ĉ Ĉ Ĉ Ĉ Ĉ Ĉ Ĉ Ĉ Ĉ Ĉ Ĉ Ĉ Ĉ Ĉ Ĉ Ĉ Ĉ C C C C

10 Application to increase frequency C LSMS (create imputation models) CWIQ (no consumption) Ĉ f 1 (x) ĈĈĈĈĈ C C f 2 (x) t0t0 t 0 +1 t 0 +2 t 0 +3t 0 +4t 0 +5 t 0 +6

11 Challenges to apply ELL to increase frequency C C ĈĈĈĈĈ f 1 (x) f 2 (x) CRISIS f 1 (x)f 1 (x)?? Can we use the same imputation model even after a crisis hits a country? Literature suggests it is not always the case…

12 A possible solution  Collect consumption data from a small sub-sample of CWIQ surveys  Use them to recreate imputation models for each year C, X C=F t (X) Year=t Ĉ =F(X) Trade-off: the smaller the sub-sample, the cheaper but the less accurate. CWIQ

13 Bangladesh  Bangladesh Bureau of Statistics (BBS) used ELL to estimate poverty at the sub-district level  BBS is now planning to use ELL to increase frequency  DEC & PRMPR are jointly studying the effectiveness of the subsample approach

14 For more information  Contact persons  Peter Lanjouw (DECPI)  Nobuo Yoshida; Cheku Dorji; Meera Mahadehan (all PRMPR)  Ananya Basu; Faizuddin Ahmed (SASEP)  Software  POVMAP – Software to run the ELL method (http://intranet.worldbank.org/servlet/main?theSitePK=477228&contentMDK= &menuPK=546145&pagePK= &piPK= )  Future events  Dissemination of results in Dhaka, Bangladesh (September, 2011)  Second workshop for high frequency poverty data (October, 2011)

15 Brief literature list  Christiaensen, L.; P. Lanjouw; J. Luoto and D. Stifel (2010). “The Reliability of Small Area Estimation Prediction Methods to Track Poverty,” Mimeo, Development Research Group, the World Bank, Washington D.C.  Examine how well the ELL method works for increasing frequency of poverty data  Elbers, C., J.O. Lanjouw, and P. Lanjouw (2003). “Micro-level Estimation of Poverty and Inequality,” Econometrica, 71(1):  Explain the ELL method in detail  Bangladesh Poverty Mapping report, available upon request  An application of the ELL method for disaggregating poverty data in Bangladesh  Concept Note for High frequency poverty data, available upon request  Explain how the ELL method will be used for increasing frequency of poverty data in Bangladesh  Manual for POVMAP2 – available in POVMAP website


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