A Map of the Poor or a Poor Map?
This paper evaluates the performance of different small area estimation methods using model and design-based simulation experiments. Design-based simulation experiments are carried out using the Mexican Intra Censal survey as a census of roughly 3....
| Main Authors: | , , , |
|---|---|
| Language: | English |
| Published: |
World Bank, Washington, DC
2021
|
| Subjects: | |
| Online Access: | http://documents.worldbank.org/curated/en/306321618243114157/A-Map-of-the-Poor-or-a-Poor-Map http://hdl.handle.net/10986/35442 |
| Summary: | This paper evaluates the performance of
different small area estimation methods using model and
design-based simulation experiments. Design-based simulation
experiments are carried out using the Mexican Intra Censal
survey as a census of roughly 3.9 million households from
which 500 samples are drawn using a two-stage selection
procedure similar to that of Living Standards Measurement
Study surveys. Several unit-level methods are considered as
well as a method that combines unit and area level
information, which has been proposed as an alternative when
the available census data is outdated. The findings show the
importance of selecting a proper model and data
transformation so that the model assumptions hold. A proper
data transformation can lead to a considerable improvement
in mean squared errors. The results from design-based
validation show that all small area estimation methods
represent an improvement, in terms of mean squared errors,
over direct estimates. However, methods that model unit
level welfare using only area level information suffer from
considerable bias. Because the magnitude and direction of
the bias are unknown ex ante, methods that rely only on
aggregated covariates should be used with caution, but they
may be an alternative to traditional area level models when
these are not applicable. |
|---|