More on CPI Changes Over Time (or Not)

OK, in my post from a few weeks back, I asserted that year-to-year changes in a country’s Corruption Perceptions Index (CPI) score are not meaningful, even after the thoughtful and welcome changes that Transparency International made to its methodology in 2012. My concern was — and remains — that the underlying data sources that TI uses to create the index are themselves not likely to be comparable across years, which means that the CPI inherits the problem. But for purposes of this post, I’m going to completely disregard my own warning in that earlier post, and take a look at whether there have been fact been any notable changes in individual countries’ perceived corruption between 2012 and 2013.  Based on a very quick scan of the data, the answer appears to be (mostly) no.

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Post-2012 CPI Scores Can’t Be Compared Across Time, Either

In post last week, I emphasized what lots of others have already tried (without much apparent success) to point out: Prior to 2012, Transparency International’s Corruption Perception Index (CPI) scores are not comparable over time.  The fact that a country’s score from one year to the next goes up or down might reflect an actual change in perceived corruption, but might be due to a whole host of other factors (changing aggregation methodology, changing scope of country coverage, change in perceived corruption of other countries, etc.), such that simple year-to-year comparisons are unreliable.  In making this point, I was not criticizing TI itself, which has been quite clear that the pre-2012 CPI scores cannot be compared across years.

But what about 2012 and after?  In 2012, TI announced, with much fanfare, that starting with the 2012 CPI and henceforth, scores across years would be comparable, due to changes in methodology (described here).

Is this right?  If it were, it would be a huge benefit both to scholars and policy reformers who want to evaluate changes over time–and the impact of various interventions.  Alas, after reading through TI’s discussion of the revised methodology, I regret to say the answer is probably no.

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Pre-2012 CPI Scores CANNOT Be Compared Across Time–So Please Stop Doing It!

OK, I know (as Rick pointed out in a recent post) that a lot — maybe too much — of the content on this blog has focused on measurement issues, so I apologize for yet another post on that topic, but this has really been bugging me:

Transparency International has been publishing its well-known and widely-used Corruption Perceptions Index (CPI) since 1995.  The index has its pros and cons, several of which have been discussed on this blog (see here, here, here, here, and here).  But putting other debates about the CPI’s validity and utility to the side, one thing should be perfectly clear: At least prior to 2012 (when TI changed its method and scoring system for the CPI), a country’s CPI scores CANNOT be compared across years.  The fact that Country X scores, say, a 4.4 in 2002, and scores a 4.9 in 2005, does NOT mean that (perceived) corruption has declined in country X.  Maybe it did, but it might have stayed the same, or gotten worse.  At most, the pre-2012 CPI provides information about country’s ranking relative to other countries, within a single year, with respect to corruption perceptions.

TI itself could not be more explicit about this, stating bluntly “CPI scores before 2012 are not comparable over time.”  Yet I keep coming across sources — news articles, presentations by leading international organizations, academic papers — that use year-to-year CPI comparisons to make claims about how corruption in a particular country or region is improving or worsening, or about whether a particular policy intervention is working or not.  YOU CAN’T DO THIS!  PLEASE STOP!!

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Multiple Errors in Quantitative Data Analysis, from Site Specializing in Quantitative Data Analysis

Like many people out there, I’m both a huge fan of Nate Silver–and the rigorous quantitative approach to election forecasting that he popularized–and at the same time quite disappointed in his FiveThirtyEight website, where the posts (especially those not by Silver himself) often seem to be slapdash efforts by people who have a smattering of statistical knowledge but don’t really know much about the topics they’re writing about. A depressing recent example, germane to this blog, is a post from last week entitled “It Only Seems Like Politics Is More Corrupt.” I normally wouldn’t bother to comment on something so slight here (especially because the post appears to have been written by an intern, and I generally try to avoid beating up on people who are just starting out), but many of the errors in analysis are both sufficiently elementary, and sufficiently common in discussions of corruption trends in other contexts (and by people with much more experience and therefore less of an excuse), that it’s worth taking a moment to explain what’s wrong.

A quick summary: The author cites recent U.S. Gallup poll data showing that the percentage of Americans who believe that “corruption is widespread” throughout the government in the United States has increased from about 60% in 2006 to a little over 75% in 2013. However, the author argues, the data doesn’t support the idea that corruption in the U.S. has actually worsened. To support that claim, she points to two other data sources:

  1. U.S. Department of Justice statistics from 1992-2012 show that the number of cases prosecuted by the DOJ’s Public Integrity Section (as well as the number of convictions and number of cases awaiting trial) appears to have declined, or at least hasn’t increased.
  2. The U.S. score on the Transparency International Corruption Perception Index (CPI) hasn’t changed very much between 1995 and 2013 (although there’s concededly a slight downward trend).

Do these two data sources disprove the idea that corruption in the U.S. has worsened over the last eight years, or more generally that the U.S. public’s perception of corruption is inaccurate?  In a word, no. There are so many elementary conceptual and statistical errors in this analysis, it’s difficult to know where to begin, but let me take a shot at cataloguing the most egregious problems: Continue reading

Does Bribery Pay? For Whom? And How Much?

Anticorruption advocates—including those in the private sector who have taken the fight against corruption seriously—insist that bribery is bad for business. That’s likely true in the aggregate, and perhaps it’s true for some individual firms. But it’s probably not true for all firms—otherwise, why would so many of them pay bribes? But it’s hard to know how much firms benefit from bribery. Likewise, while would be useful to know more about the factors that affect the size and probability of bribery, figuring this out is a challenge because of the secrecy of corrupt transactions.

In a recent working paper, Yan Leung Cheung, P. Raghavendra Rau, and Aris Stouraitis try to get at these questions by looking at enforcement data for anti-bribery laws–both laws that apply domestically and those (like the U.S. FCPA and the UK Bribery Act) that prohibit foreign bribery. In particular, the study examines a subset of reported cases where (1) a bribe was (allegedly) paid for a particular, identifiable public contract, announced on a specific date, (2) there is stock and financial data for the firm, available on a day-to-day basis, and (3) the enforcement data contains information on the size of the bribe paid to secure the contract. Armed with that information, the authors reason that we can use the abnormal increase in firm market capitalization that coincides with the announcement of the contract as a measure of the gross benefit of the bribe to the firm (the authors assume that bribe-paying firms would not have gotten the contract without paying the bribe). We can then subtract the size of the bribe from that gross benefit to get the net benefit of bribery for the firm. On top of that, the authors reason that we can learn something about how the total gains from the bribe transaction are allocated between the firm and the corrupt public official by dividing the size of the bribe payment by the sum of the bribe payment plus the gross benefit of the bribe. The higher this ratio, the more the benefits of bribery go to the public official; the lower this ratio, the more the benefits of bribery accrue to the bribe-paying firm.

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Corruption Measurement: A Primer

In an early post Matthew predicted that the measurement of corruption was likely to be a major topic of discussion on this blog.  So far his prediction has proved correct.  Ten of the sixty plus posts that have appeared since this blog was launched in mid-February have been devoted in whole or part to measurement issues:  Are perception measures accurate?  Useful whether accurate or not?  What’s the source of the $1 trillion bribe estimate?  Shouldn’t someone develop sub-national corruption perception measures?   And so forth.

This eleventh post steps back from the policy issues examined in earlier ones to address a much more straightforward question:  What are the different ways corruption can be measured? Continue reading

The Source of the $1 Trillion in Annual Bribes Figure

In my last post, I discussed my unsuccessful attempts to track down the source for the widely-cited “$1 trillion in annual bribe payments” figure (other than a 2004 World Bank press release, which referenced an unpublished study without further citation).  Several readers were kind enough to direct me to the best published source on the $1 trillion figure: the appendix in a chapter by Daniel Kaufmann in the World Economic Forum’s 2005-2006 Global Competitiveness Report.  The chapter addresses most—though perhaps not all—of my concerns.

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Where Does the “$1 Trillion in Annual Bribes” Number Come From?

Given the generally accepted view that bribery is widespread around the world, it probably doesn’t make sense to get too hung up over the specific numbers. That said, I’ve seen the figure of (approximately) $1 trillion in annual bribe payments thrown around quite a bit, and I was curious where that number came from.  It seems to me it would be very difficult for even the most intrepid researcher to come up with a plausible ballpark estimate of the total dollar amount of annual bribe transactions. After poking around a bit on the web and in some of the relevant literature, I’m coming up empty. Here’s what I can tell so far: Continue reading

Objective Validation of Subjective Corruption Perceptions?

As discussed on this blog and elsewhere, one of the big concerns about the most popular cross-country datasets on corruption (the Transparency International Corruption Perceptions Index (CPI), the World Bank Institute’s Worldwide Governance Indicators (WGI), etc.) is that they are based (largely or entirely) on perceptions of corruption. As Rick noted in a recent post, and as the critical literature has pointed out ad nauseam, perceptions, while perhaps important in their own right, are not necessarily based in reality. Indeed, some recent research (including, but certainly not limited to, nice papers by Claudio Weber Abramo, by Mireille Razafindrakoto and Francois Rouband, and by Richard Rose and William Mishler) indicates that national corruption perceptions are only weakly correlated with survey results asking about individuals’ personal experience with bribery. This raises serious questions about whether the perception-based indicators are useful either for general assessment or for testing hypotheses about the causes or consequences of corruption.

But might there be more objective measures that could be used to assess whether the corruption perceptions indices are picking up something real? Off the top of my head, I can think of four quite clever recent papers that demonstrate a strong correlation between a subjective corruption perception index and some more objective measure of dishonest behavior. I’m sure there are more, but let me note the four examples that I can think of, and then say a bit on what this might mean for the use of perception-based indicators in empirical corruption research.

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Can Foreign Anti-Bribery Enforcement Statistics Help Us Measure Corruption Levels Objectively?

We’ve spent a fair amount of time, in the early days of this blog, talking about the challenges of measuring corruption cross-nationally. The well-known perception measures are useful to a point, but suffer from well-known drawbacks, chief among them concerns about how accurately perceptions capture reality. A recent working paper by Laarni Escresa and Lucio Picci, “A New Cross-National Measure of Corruption,” tries to get around these difficulties. Using data on enforcement of foreign anti-bribery laws like the U.S. Foreign Corrupt Practices Act (FCPA), Escresa and Picci they derive a new index, which they call the Public Administration Corruption Index (PACI), to make more objective cross-country comparisons in corruption levels. The paper is really clever and creative—but in the end I think it doesn’t work. Let me first say what I think is so cool about the idea, and then explain what I think are the biggest flaws. Continue reading