Short and Long Recall Errors in Retrospective Household Surveys: Evidence from a Developing Country

Abstract

While recall errors in retrospective data from household surveys may generate estimation biases, the nature and the relative magnitude of the errors are still largely unknown, especially in the context of developing countries. To bridge this gap in the existing studies, we conduct a resurvey of respondents of the Vietnam Household Living Standards Survey (VHLSS) 2006. The combined data set allows us to investigate a variety of short-term and long-term errors associated with recall surveys. First, our empirical results suggest that when we ask total expenditure rather than categorized expenditures, long recall errors are no worse than short recall errors. Second, we found mean-reversion only for long recall errors in the sum of categorized expenditures but not necessarily for total expenditure. Finally, the inclusion of household size, asset, income, and geographical dummy variables in regression analyses may mitigate the biases arising from measurement errors.

How altruism works during a pandemic: Examining the roles of financial support and degrees of individual altruism on international remittance

“…Furthermore, we conducted a one-time survey for this research using an online format because of an unexpected pandemic. Although we designed the details of the survey for respondents to answer easily and concisely, as explained in Section IV, the retrospective-based survey may pose a risk of measurement error (Beegle et al, 2012;Gibson & Kim, 2010;Sawada et al, 2019). Nevertheless, the findings contribute to a better understanding of the mechanism of motives for international remittances; above all, the findings cast light on the relationship between public and private transfers in unordinary times.…”

Organic Nutrient Source Allocation and Use in Smallholder Farming Communities: What Are We Missing?

“…They were then asked to "allocate" the proportion of ONS they retained in-field, took to other fields or fed to livestock. This technique reduces recall bias over asking farmers to estimate actual amounts (Sawada et al, 2019;Wollburg et al, 2020).…”