Using Survey-to-Survey Imputation to Fill Poverty Data Gaps at a Low Cost: Evidence from a Randomized Survey Experiment

Hai-Anh Dang (), Talip Kilic, Vladimir Hlasny, Kseniya Abanokova and Calogero Carletto

No 1392, GLO Discussion Paper Series from Global Labor Organization (GLO)

Abstract: Survey data on household consumption are often unavailable or incomparable over time in many low- and middle-income countries. Based on a unique randomized survey experiment implemented in Tanzania, this study offers new and rigorous evidence demonstrating that survey-to-survey imputation can fill consumption data gaps and provide low-cost and reliable poverty estimates. Basic imputation models featuring utility expenditures, together with a modest set of predictors on demographics, employment, household assets and housing, yield accurate predictions. Imputation accuracy is robust to varying survey questionnaire length; the choice of base surveys for estimating the imputation model; different poverty lines; and alternative (quarterly or monthly) CPI deflators. The proposed approach to imputation also performs better than multiple imputation and a range of machine learning techniques. In the case of a target survey with modified (e.g., shortened or aggregated) food or non-food consumption modules, imputation models including food or non-food consumption as predictors do well only if the distributions of the predictors are standardized vis-à-vis the base survey. For best-performing models to reach acceptable levels of accuracy, the minimum-required sample size should be 1,000 for both base and target surveys. The discussion expands on the implications of the findings for the design of future surveys.

Keywords: consumption; poverty; survey-to-survey imputation; household surveys; Tanzania (search for similar items in EconPapers)
JEL-codes: C15 I32 O15 (search for similar items in EconPapers)
Date: 2024
New Economics Papers: this item is included in nep-dev
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Citations: View citations in EconPapers (2)

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Related works:
Working Paper: Using Survey-to-Survey Imputation to Fill Poverty Data Gaps at a Low Cost: Evidence from a Randomized Survey Experiment (2024)
Working Paper: Using Survey-to-Survey Imputation to Fill Poverty Data Gaps at a Low Cost: Evidence from a Randomized Survey Experiment (2024)
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:glodps:1392

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