Guest Post: Refining Corruption Surveys To Identify New Opportunities for Social Change

GAB is delighted to welcome back Dieter Zinnbauer, Programme Manager at Transparency International, who contributes the following guest post:

Household corruption surveys, such as Transparency International’s Global Corruption Barometer (GCB) are primarily, and very importantly, focused on tracking the scale and scope of citizens’ personal bribery experience and their general perceptions about corruption levels in different institutions. More recently, the GCB has branched out into questions about what kind of action against corruption people do or do not take, and why. The hope is that better understanding what motivates people to take action against corruption will help groups like TI develop more effective advocacy and mobilization strategies.

In addition to these direct questions about why people say they do or don’t take action against corruption, household surveys have the potential to help advocacy groups in their efforts to mobilize citizens in another way as well: by identifying inconsistencies or discrepancies between what people’s experience of corruption and their perceptions of corruption. The existence of these gaps is not in itself surprising, but learning more about them might help advocates craft strategies for changing both behavior and beliefs. Consider the following examples: Continue reading

Another Way To Improve the Accuracy of Corruption Surveys: The Crosswise Model

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

Using the Unmatched Count Technique (UCT) to Elicit More Accurate Answers on Corruption Experience Surveys

With apologies to those readers who couldn’t care less about methodological issues associated with corruption experience surveys, I’m going to continue the train of thought I began in my last two posts (here and here) with further musings on that theme—in particular what survey researchers refer to as the “social desirability bias” problem (the reluctance of survey respondents to truthfully answer questions about sensitive behaviors like corruption). Last week’s post emphasized the seriousness of this concern and voiced some skepticism about whether one of the most common techniques for addressing it (so-called “indirect questioning,” in which respondents are asked not about their own behavior but about the behavior of people “like them” or “in their line of business”) actually works as well as is commonly assumed.

We professors, especially those of us who like to write blog posts, often get a bad rap for criticizing everything in sight but never offering any constructive solutions. The point is well-taken, and while I can’t promise to lay off the criticism, in today’s post I want to try to be at least a little bit constructive by calling attention to a promising alternative approach to mitigating the social desirability bias problem in corruption experience surveys: the unmatched count technique (UCT), sometimes alternatively called the “item count” or “list” method. This approach has been deployed occasionally by a few academic researchers working on corruption, but it hasn’t seemed to have been picked up by the major organizations that field large-scale corruption experience surveys, such as Transparency International’s Global Corruption Barometer (GCB), the World Bank’s Enterprise Surveys (WBES), or the various regional surveys (like AmericasBarometer or Afrobarometer). So it seemed worthwhile to try to draw more attention to the UCT. It’s by no means a perfect solution, and I’ll say a little bit more about costs and drawbacks near the end of the post. But the UCT is nonetheless worth serious consideration, both by other researchers designing their own surveys for individual research projects, and by more established organizations that regularly field surveys on corruption experience.

The way a UCT question works is roughly as follows: Continue reading

Can Indirect Questioning Induce Honest Responses on Bribery Experience Surveys?

As I noted in my last post, bribery experience surveys – of both firms and citizens – are increasingly popular as a tool not only for testing hypotheses about corruption’s causes and effects, but for measuring the effectiveness of anticorruption policies, for example in the context of assessing progress toward the Sustainable Development Goals’ anticorruption targets. Bribery experience surveys are thought to have a number of advantages over perception-based indicators, greater objectivity chief among them.

I certainly agree that bribery experience surveys are extremely useful and have contributed a great deal to our understanding of corruption’s causes and effects. They’re not perfect, but no indicator is; different measures have different strengths and weaknesses, and we just need to use caution when interpreting any given set of empirical results. In that spirit, though, I do think the anticorruption community should subject these experience surveys to a bit more critical scrutiny, comparable to the extensive exploration in the literature of the myriad shortcomings of corruption perception indicators. In last week’s post, I focused on the question of the correct denominator to use when calculating bribery victimization rates – all citizens, or all citizens who have had (a certain level of) contact with the bureaucracy? Today I want to focus on a different issue: What can we do about the fact that survey respondents might be reluctant to answer corruption questions truthfully?

The observation that survey respondents might be reluctant to truthfully answer questions about their personal bribery experience is neither new nor surprising. Survey respondents confronted with sensitive questions often have a tendency to give the answer that they think they “should” give (or that they think the interviewer wants to hear); social scientists call this tendency “social desirability bias.” There’s quite robust evidence that social desirability bias affects surveys on sensitive topics, including corruption; even more troubling, the available evidence suggests that social desirability bias on corruption surveys is neither constant nor randomly distributed, but rather varies across countries and regions. This means that apparent variations in bribery experience rates might actually reflect variations in willingness to truthfully answer questions about bribery experience, rather than (or in addition to) variations in actual bribery experience (see here, here, and here).

So, what can we do about this problem? Existing surveys use a range of techniques. Here I want to focus on one of the most popular: the “indirect questioning” approach. The idea is that instead of asking a respondent, “How much money does your firm have to spend each year on informal payments to government officials?”, you instead ask, “How much money does a typical firm in your line of business have to spend each year on informal payments to government officials?” (It’s perhaps worth noting that the indirect questioning method seems more ubiquitous in firm/manager surveys; many of the most prominent household surveys, such as the International Crime Victims Survey and the Global Corruption Barometer, ask directly about the household’s experience rather than asking about “households like yours.”) The hope is that asking the question indirectly will reduce social desirability bias, because the respondent doesn’t have to admit that he or she (or his or her firm) engaged in illegal activity.

Is that hope justified? I don’t doubt that indirect questioning helps to some extent. But I confess that I’m skeptical, on both theoretical and empirical grounds, that indirect questioning is the silver bullet solution for social desirability bias that some researchers seem to suggest that it is. Continue reading

Watch Your Language: Not “Everyone” Is Corrupt–Anywhere.

I’ve noticed something about the way many people (including me) sometimes describe the severity of the corruption problem in many parts of the world: When calling attention to the problem of widespread, systemic corruption, it’s not uncommon to hear people say—usually in casual conversation, occasionally in more formal presentations—that in this or that country, or this or that government or department, “everyone” is corrupt, or “everybody” takes bribes, or similar. I’m sure I’ve used this or similar language myself, without even thinking about it. And I understand that when most people say things like “everyone in [X] is corrupt,” they don’t mean that literally. Yet I find myself increasingly bothered by statements like this, for several reasons: Continue reading

Measurement Brings Action: The Need for a Global Sexual Corruption Index

Sexual corruption is a scourge, to varying degrees, in almost every country–from immigration officials demanding sex for green cards, to U.N. soldiers using their power to force themselves on refugees or the local population they are supposed to be protecting, to police officers who demand sex in exchange for not arresting someone. The International Association of Women Judges has been trying to bring attention to this “sextortion” problem, with some limited success: Transparency International (TI) describes sextortion as a form of corruption, and last September’s International Anti-Corruption Conference devoted a high-profile session to discussing this issue.

Yet despite this increasing recognition that this sort of sexual corruption is indeed corruption–the abuse of public power for private gain–the major international indexes used to measure corruption, such as TI’s corruption perception index (CPI) (and the underlying studies used to generate the CPI), focus overwhelmingly on material corruption–principally monetary bribery and embezzlement–not the abuse of public power to extort sexual favors from victims. This is a problem: As we have seen over and over again (both in the corruption context, and in other contexts such as the Millennium Development Goals (MDGs)), for better or worse, national-level country ratings drive action. Right now, a country that wishes to improve its global standing on corruption currently has little incentive to tackle sexual corruption. And there is no separate, easy-to-understand metric that calls attention to how well (or poorly) countries are doing, relative to one another, in addressing that problem.

It is time for that to change. It is time to create a Global Sexual Corruption Index. Continue reading

Guest Post: A New Additional Indicator for Measuring Progress Toward SDG 16

GAB is delighted to welcome back Dieter Zinnbauer, Programme Manager at Transparency International, who contributes the following guest post:

A very interesting discussion has evolved on this blog (see here, here, here, and here), and in the wider world (for example, see here), on about the indicators that should be used to measure progress toward the Sustainable Development Goals (SDGs) goals for improving governance and reducing corruption (Goal 16). There are already some very good suggestions on the table, including the use of Transparency International’s Global Corruption Barometer (GCB) to measure progress toward Target 16.5, on reducing corruption and bribery in all their forms. (TI has used the GCB since 2005 to compile one of the largest data troves on the detailed experience with corruption of households and individuals around the world. Using a GCB-type indicator for the bribery dimension of SDG 16.5 is supported by a wide variety of stakeholders, including the World Bank, UNDP, and Save the Children.)

Yet most of the indicators proposed so far, including the GCB, speak to very specific aspects of corruption (such as bribery) and don’t quite do justice to Goal 16’s broad ambitions and its emphasis on public accountability. So to spice up this stew a bit, let me suggest another possible indicator, one that complement to some of the ideas that are already on the table. My proposed indicator of progress toward SDG 16 is as follows:

What percentage of national-level parliamentarians (and perhaps top level members of the executive) have made assets, income, and interest disclosures (AIIDs) in a format that is publicly accessible online at sufficient level of detail, in timely manner, and in a machine-readable data format.

Using AIID as an additional SDG 16 indicator might at first seem to be a step backwards, since such an indicator measures “outputs” rather than “outcomes.” But let me try to convince you that in fact AIID would be an extremely useful complementary indicator for progress toward SDG 16: Continue reading