Selection in Surveys: Using Randomized Incentives to Detect and Account for Nonresponse Bias

This paper addresses nonresponse bias in surveys — the distortion that arises when survey participants differ systematically from nonparticipants in ways that correlate with the survey’s outcomes of interest. The authors develop and apply methods to detect and correct for nonresponse bias using randomized financial incentives embedded in the survey design itself.

The empirical application is the “Norge i Koronatid” (NiK) survey, conducted by Statistics Norway in April–May 2020 to study the immediate labor market consequences of Norway’s COVID-19 lockdown. The NiK survey has two features that make it unusually well-suited for studying nonresponse bias: (1) it is linked to full-population administrative data, providing a verifiable ground truth for the entire Norwegian adult population; and (2) survey invitees were randomly assigned to one of five financial incentive levels (0%, 1%, 5%, 7%, or 10% probability of receiving a 1,000 NOK prepaid card), generating exogenous variation in participation rates. The final sample of 10,000 randomly drawn adults achieved a 47.4% participation rate.

Winnie Van Dijk | Macro Paper Warehouse

Selection in Surveys: Using Randomized Incentives to Detect and Account for Nonresponse Bias