Today’s post is yet another entry in what I guess has become a mini-series on corruption experience surveys. In the first post, from a few weeks back, I discussed the question whether, when trying to assess and compare bribery prevalence across jurisdictions using such surveys, the correct denominator should be all respondents, or only those who had contact with government officials. That post bracketed questions about whether respondents would honestly admit bribery in light of the “social desirability bias” problem (the reluctance to admit, even on an anonymous survey, that one has engaged in socially undesirable activities). My two more recent posts have focused on that problem, first criticizing one of the most common strategies for mitigating the social desirability bias problem (indirect questioning), and then, in last week’s post, trying to be a bit more constructive by calling attention to one potentially more promising solution, the so-called unmatched count technique (UCT), also known as the item count technique or list method. Today I want to continue in that latter vein by calling attention to yet another strategy for ameliorating social desirability bias in corruption surveys: the “crosswise model.”
As with the UCT, the crosswise model was developed outside the corruption field (see here and here) and has been deployed in other areas, but it has only recently been introduced into survey work on corruption. The scholars responsible for pioneering the use of the crosswise model in the study of corruption are Daniel Gingerich, Virginia Oliveros, Ana Corbacho, and Mauricio Ruiz-Vega, in (so far) two important papers, the first of which focuses primarily on the methodology, and the second of which applies the method to address the extent to which individual attitudes about corruption are influenced by beliefs about the extent of corruption in the society. (Both papers focus on Costa Rica, where the survey was fielded.) Those who are interested should check out the original papers by following the links above. Here I’ll just try to give a brief, non-technical flavor of the technique, and say a bit about why I think it might be useful not only for academics conducting their particular projects, but also for organizations that regularly field more comprehensive surveys on corruption, such as Transparency International’s Global Corruption Barometer.
The basic intuition behind the crosswise model is actually fairly straightforward, though it might not be immediately intuitive to everyone. Here’s the basic idea: Continue reading