Social desirability bias (SDB) is a pervasive threat to the validity of survey and experimental data. Respondents might often misreport sensitive attitudes and behaviors to appear more socially acceptable. We begin by synthesizing empirical evidence on the prevalence and magnitude of SDB across various domains, focusing on studies with individual-level benchmarks. We then critically assess commonly used strategies to mitigate SDB, highlighting how they can sometimes fail by creating confusion or inadvertently increasing perceived sensitivity. To help researchers navigate these challenges, we offer practical guidance on selecting the most suitable tools for different research contexts. Finally, we examine how SDB can distort treatment effects in experiments and discuss mitigation strategies.

More on this topic

BFI Working Paper·Jun 23, 2026

Misleading Estimates from Nonlinear Models with a Binary Outcome

Brian Curran, Bruce Meyer, and Derek Wu
Topics: Uncategorized
BFI Working Paper·Jun 15, 2026

Don’t Give Up on Lab Experiments: Why the Field Still Needs the Lab

John List
Topics: Uncategorized
BFI Working Paper·May 5, 2026

Retrospective Versus Prospective Meritocracy

Steven Durlauf
Topics: Uncategorized