Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/300249 
Year of Publication: 
2024
Series/Report no.: 
GLO Discussion Paper No. 1458
Publisher: 
Global Labor Organization (GLO), Essen
Abstract: 
Accurate poverty measurement relies on household consumption data, but such data are often inadequate, outdated or display inconsistencies over time in poorer countries. To address these data challenges, we employ survey-to-survey imputation to produce estimates for several poverty indicators including headcount poverty, extreme poverty, poverty gap, near-poverty rates, as well as mean consumption levels and the entire consumption distribution. Analyzing 22 multi-topic household surveys conducted over the past decade in Bangladesh, Ethiopia, Malawi, Nigeria, Tanzania, and Vietnam, we find encouraging results. Adding either household utility expenditures or food expenditures to basic imputation models with household-level demographic, employment, and asset variables could improve the probability of imputation accuracy between 0.1 and 0.4. Adding predictors from geospatial data could further increase imputation accuracy. The analysis also shows that a larger time interval between surveys is associated with a lower probability of predicting some poverty indicators, and that a better imputation model goodness-of-fit (R2) does not necessarily help. The results offer cost-saving inputs into future survey design.
Subjects: 
consumption
poverty
survey-to-survey imputation
household surveys
Vietnam
Ethiopia
Malawi
Nigeria
Tanzania
Sub-Saharan Africa
JEL: 
C15
I32
O15
Document Type: 
Working Paper

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