Estimating Poverty Rates in Target Populations : An Assessment of the Simple Poverty Scorecard and Alternative Approaches
The performance of the Simple Poverty Scorecard is compared against the performance of established regression-based estimators. All estimates are benchmarked against observed poverty status based on household expenditure (or income) data from house...
| Main Authors: | , , , , , |
|---|---|
| Language: | English en_US |
| Published: |
World Bank, Washington, DC
2016
|
| Subjects: | |
| Online Access: | http://documents.worldbank.org/curated/en/2016/08/26695758/estimating-poverty-rates-target-populations-assessment-simple-poverty-scorecard-alternative-approaches http://hdl.handle.net/10986/25038 |
| Summary: | The performance of the Simple Poverty
Scorecard is compared against the performance of established
regression-based estimators. All estimates are benchmarked
against observed poverty status based on household
expenditure (or income) data from household socioeconomic
surveys that span nearly a decade and are representative of
subnational populations. When the models all adopt the same
"one-size-fits-all" training approach, there is no
meaningful difference in performance and the Simple Poverty
Scorecard is as good as any of the regression-based
estimators. The findings change, however, when the
regression-based estimators are "trained" on
"training sets" that more closely resemble
potential subpopulation test sets. In this case,
regression-based models outperform the nationally calculated
Simple Poverty Scorecard in terms of bias and variance.
These findings highlight the fundamental trade-off between
simplicity of use and accuracy. |
|---|