Recall Bias Revisited: Measure Farm Labor Using Mixed-Mode Surveys and Multiple Imputation. A new GLO Discussion Paper by GLO Fellow Hai-Anh Dang and Calogero Carletto.

A new GLO Discussion Paper suggests that imputation-based methods of data collection results in reasonable  estimates of smallholder farm labor.

GLO Discussion Paper No. 1020, 2022

Recall Bias Revisited: Measure Farm Labor Using Mixed-Mode Surveys and Multiple Imputation  Download PDF
by Dang, Hai-Anh H. & Carletto, Calogero

GLO Fellow Hai-Anh Dang

Hai-Anh Dang

Author Abstract: Smallholder farming dominates agriculture in poorer countries. Yet, traditional recall-based surveys on smallholder farming in these countries face challenges with seasonal variations, high survey costs, poor record-keeping, and technical capacity constraints resulting in significant recall bias. We offer the first study that employs a less-costly, imputation-based alternative using mixed modes of data collection to obtain estimates on smallholder farm labor. Using data from Tanzania, we find that parsimonious imputation models based on small samples of a benchmark weekly in-person survey can offer reasonably accurate estimates. Furthermore, we also show how less accurate, but also less resource-intensive, imputation-based measures using a weekly phone survey may provide a viable alternative for the more costly weekly in-person survey. If replicated in other contexts, including for other types of variables that suffer from similar recall bias, these results could open up a new and cost-effective way to collect more accurate data at scale.

GLO Discussion Papers are research and policy papers of the GLO Network which are widely circulated to encourage discussion. Provided in cooperation with EconStor, a service of the ZBW – Leibniz Information Centre for Economics, GLO Discussion Papers are among others listed in RePEc (see IDEAS,  EconPapers)Complete list of all GLO DPs – downloadable for free.

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