Corruption Is Higher Than Perceived

From a recent World Bank policy research working paper (abstract):

Misunderestimating corruption
Kraay, Aart; Kraay, Aart; Murrell, Peter

Summary: Estimates of the extent of corruption rely largely on self-reports of individuals, business managers, and government officials. Yet it is well known that survey respondents are reticent to tell the truth about activities to which social and legal stigma are attached, implying a downward bias in survey-based estimates of corruption. This paper develops a method to estimate the prevalence of reticent behavior, in order to isolate rates of corruption that fully reflect respondent reticence in answering sensitive questions. The method is based on a statistical model of how respondents behave when answering a combination of conventional and random-response survey questions. The responses to these different types of questions reflect three probabilities -- that the respondent has done the sensitive act in question, that the respondent exhibits reticence in answering sensitive questions, and that a reticent respondent is not candid in answering any specific sensitive question. These probabilities can be estimated using a method-of-moments estimator. Evidence from the 2010 World Bank Enterprise survey in Peru suggests reticence-adjusted estimates of corruption that are roughly twice as large as indicated by responses to standard questions. Reticence-adjusted estimates of corruption are also substantially higher in a set of ten Asian countries covered in the Gallup World Poll.

The measures of corruption that are currently available (Transparency International’s Corruption Perception Index and the World Bank’s Control of Corruption indicator) are sparse, and rely almost entirely on the honesty of the survey respondents. If in fact respondents are not truthful (i.e. they have something to hide), the incidence of “real” corruption would be higher than revealed by the survey.

This wouldn’t matter if the degree of reticence or “guilt” is the same in all countries. But if “guilt” weren’t the same then survey estimates would be biased, and cross-country comparisons made meaningless. This new research paper explicitly models the degree of “guilt” and applies it to survey data for certain countries, and adjusts the survey estimates to arrive at what is essentially an absolute value for the incidence of corruption.

Malaysia, incidentally, is one of the countries they’ve applied the methodology to, and in fact commented on (excerpt, pg.15; the figure referred to is on pg.30):

Figure 5 illustrates the consequences of reticent behavior for estimates of the prevalence of corruption for the full set of 10 countries included in our analysis. The top panel compares naïve and reticence-adjusted estimates of guilt. Consider for example the comparison of Indonesia and Malaysia, which have similar naive estimates of the prevalence of corruption of 7% and 9% respectively. However, our estimates suggest that effective reticence is much more common in Malaysia (44%) than it is in Indonesia (21%). As a result, our reticence-adjusted estimates of corruption increase much more in Malaysia (to 15%) than they do in Indonesia (to 9%). Note also that the corruption ranking of six of the ten countries differs between the naïve and the estimated rates of guilt. Overall, our estimates from the GWP show that reticent behavior is likely to lead to substantial downward biases in estimates of corruption based on CQs, and moreover that the size of these biases can differ non-trivially across countries.

Two takeaways here:

1. The level of corruption is likely higher than captured by current surveys;
2. As against that, we’d need estimates on the rate of reticence across the globe to get a full picture of our ranking, as individual country bias will be substantially different.

One potential problem is that the paper presumes reticence as evidence of "guilt" (i.e. personal involvement in corruption), which might be problematical when applied to perception surveys such as Transparency International’s. Nevertheless, this is a promising start towards getting better measures of corruption than we currently have.

Technical Notes

Kraay, Aart & Peter Murrell, "Misunderestimating corruption", World Bank Policy Research working paper no. WPS 6488, May 2013