Data Gaps, Data Incomparability, and Data Imputation: A Review of Poverty Measurement Methods for Data-Scarce Environments

Arbeitspapier

We offer a review of methods that have been employed to provide poverty estimates of 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. We focus on methods that aim to compare trends and dynamic patterns of poverty outcomes over time. We present the various existing 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, we also offer a practical guide with detailed instructions on computer programs that can be used to implement the reviewed techniques.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: GLO Discussion Paper ; No. 179

Classification and Topics

• Classification: Wirtschaft ; Statistical Simulation Methods: General ; Measurement and Analysis of Poverty ; Economic Development: Human Resources; Human Development; Income Distribution; Migration
• Subject: poverty ; mobility ; imputation ; consumption ; wealth index ; synthetic panels ; household survey

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Dang, Hai-Anh ; Jolliffe, Dean ; Carletto, Calogero
• Event: Veröffentlichung
• (who): Global Labor Organization (GLO)
• (where): Maastricht
• (when): 2018

Further information

• Handle: http://hdl.handle.net/10419/173752
• Last update: 10.03.2025, 11:42 AM CET