Artificial Inflation or Deflation? Assessing the Item Count Technique in Comparative Surveys

Abstract

While the popularity of using the item count technique (ICT) or list experiment to obtain estimates of attitudes and behaviors subject to social desirability bias has increased in recent years among political scientists, many of the empirical properties of the technique remain untested. In this paper, we explore whether estimates are biased due to the different list lengths provided to control and treatment groups rather than due to the substance of the treatment items. By using face-to-face survey data from national probability samples of households in Uruguay and Honduras, we assess how effective the ICT is in the context of face-to-face surveys-where social desirability bias should be strongest-and in developing contexts-where literacy rates raise questions about the capability of respondents to engage in cognitively taxing process required by ICT. We find little evidence that the ICT overestimates the incidence of behaviors and instead find that the ICT provides extremely conservative estimates of high incidence behaviors. Thus, the ICT may be more useful for detecting low prevalence attitudes and behaviors and may overstate social desirability bias when the technique is used for higher frequency socially desirable attitudes and behaviors. However, we do not find strong evidence of variance in deflationary effects across common demographic subgroups, suggesting that multivariate estimates using the ICT may not be biased. © 2013 Springer Science+Business Media New York.