Non-reponse and False Response in Corruption Surveys of Firms

Abstract from a new working paper by Rahman, Li, and Jensen:

Heard melodies are sweet, but those unheard are sweeter : understanding corruption using cross-national firm-level surveys

2007-11-01

By: Rahman, Aminur; Li, Quan; Jensen, Nathan M.

http://d.repec.org/n?u=RePEc:wbk:wbrwps:4413&r=dev

Since the early 1990s, a large number of studies have been undertaken to understand the causes and consequences of corruption. Many of these studies have employed firm-level survey data from various countries. While insightful, these analyses based on firm-level surveys have largely ignored two important potential problems: nonresponse and false response by the firms. Treating firms ' responses on a sensitive issue like corruption at their face value could produce incorrect inferences and erroneous policy recommendations. We argue that the data generation of nonresponse and false response is a function of the political environment in which the firms operate. In a politically repressive environment, firms use nonresponse and false response as self-protection mechanisms. Corruption is understated as a result. We test our arguments using the World Bank enterprise survey data of more than 44,000 firms in 72 countries ! for the period 2000-2005 and find that firms in countries with less press freedom are more likely to provide nonresponse or false response on the issue of corruption. Therefore, ignoring this systematic bias in firms ' responses could result in underestimation of the severity of corruption in politically repressive countries. More important, this bias is a rich and underutilized source of information on the political constraints faced by the firms. Nonresponse and false response, like unheard melodies, could be more informative than the heard melodies in the available truthful responses in firm surveys.

This is an important type of analysis. By construction, the survey serves as an experiment to test a behavioral model of firms' willingness to report corruption. This type of "incidental survey experiment" is a nice way to perform secondary data analysis. Not only do we learn something about behavior, but we also learn something about the data itself.