Data Gaps, Data Incomparability, and Data Imputation : A Review of Poverty Measurement Methods for Data-Scarce Environments
This paper reviews methods that have been employed to estimate poverty in contexts where household consumption data are unavailable or missing. These contexts range from completely missing and partially missing consumption data in cross-sectional h...
| Main Authors: | , , |
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| Language: | English |
| Published: |
World Bank, Washington, DC
2017
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| Subjects: | |
| Online Access: | http://documents.worldbank.org/curated/en/551171513690220305/Data-gaps-data-incomparability-and-data-imputation-a-review-of-poverty-measurement-methods-for-data-scarce-environments http://hdl.handle.net/10986/29074 |
| Summary: | This paper reviews methods that have
been employed to estimate poverty in contexts where
household consumption data are unavailable or missing. These
contexts range from completely missing and partially missing
consumption data in cross-sectional household surveys, to
missing panel household data. The paper focuses on methods
that aim to compare trends and dynamic patterns of poverty
outcomes over time. It presents the various methods under a
common framework, with pedagogical discussion on the
intuition. Empirical illustrations are provided using
several rounds of household survey data from Vietnam.
Furthermore, the paper provides a practical guide with
detailed instructions on computer programs that can be used
to implement the reviewed techniques. |
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