Placebo Statements in List Experiments

13 Pages Posted: 11 Jun 2019

See all articles by Guillem Riambau

Guillem Riambau

National University of Singapore (NUS) - Yale-NUS College

Kai Ostwald

University of British Columbia (UBC)

Date Written: May 26, 2019


List experiments are a widely used survey technique for estimating the prevalence of socially sensitive attitudes or behaviors. Their design, however, makes them vulnerable to bias: because treatment group respondents see a greater number of items (J+1) than control group respondents (J), the treatment group mean may be mechanically inflated due simply to the greater number of items. The few previous studies that directly examine this do not arrive at definitive conclusions. We find clear evidence of inflation in an original dataset, though only among respondents with low educational attainment. Furthermore, we use available data from previous studies and find similar heterogeneous patterns. The evidence of heterogeneous effects has implications for the interpretation of previous research using list experiments, especially in developing world contexts. We recommend a simple solution: using a necessarily false placebo statement for the control group equalizes list lengths, thereby protecting against mechanical inflation without imposing costs or altering interpretations.

Keywords: List experiment, item count technique, survey design, placebo statement, satisficing, social desirability bias

Suggested Citation

Riambau, Guillem and Ostwald, Kai, Placebo Statements in List Experiments (May 26, 2019). Available at SSRN: or

Guillem Riambau (Contact Author)

National University of Singapore (NUS) - Yale-NUS College ( email )


Kai Ostwald

University of British Columbia (UBC) ( email )

1855 West Mall
Vancouver, British Columbia BC V6T 1Z4


Here is the Coronavirus
related research on SSRN

Paper statistics

Abstract Views
PlumX Metrics