Adjusting Corruption Perception Index Scores for National Wealth

My post two weeks ago discussed Transparency International’s newly-released 2017 Corruption Perceptions Index (CPI), focusing in particular on an old hobby-horse of mine: the hazards of trying to draw substantive conclusions from year-to-year changes in any individual country’s CPI score. Today I want to continue to discuss the 2017 CPI, with attention to a different issue: the relationship between a country’s wealth and its CPI score. It’s no secret that these variables are highly correlated. Indeed, per capita GDP remains the single strongest predictor of a country’s perceived corruption level, leading some critics to suggest that the CPI doesn’t really measure perceived corruption so much as it measures wealth—penalizing poor countries by portraying them as more corrupt, when in fact their corruption may be due more to their poverty than to deficiencies in their cultures, policies, and institutions.

This criticism isn’t entirely fair. Per capita income is a strong predictor of CPI scores, but they’re far from perfectly correlated. Furthermore, even if it’s true that worse (perceived) corruption is in large measure a product of worse economic conditions, that doesn’t mean there’s a problem with the CPI as such, any more than a measure of infant mortality is flawed because it is highly correlated with per capita income. (And of course because corruption may worsen economic outcomes, the correlation between wealth and CPI scores may be a partial reflection of corruption’s impact, though I doubt there are many who think that this relationship is so strong that the causal arrow runs predominantly from corruption to national wealth rather than from national wealth to perceived corruption.)

Yet the critics do have a point: When we look at the CPI results table, we see a lot of very rich countries clustered at the top, and a lot of very poor countries clustered at the bottom. That’s fine for some purposes, but we might also be interested in seeing which countries have notably higher or lower levels of perceived corruption than we would expect, given their per capita incomes. As a crude first cut at looking into this, I merged the 2017 CPI data table with data from the World Bank on 2016 purchasing-power-adjusted per capita GDP. After dropping the countries that appeared in one dataset but not the other, I had a 167 countries. I then ran a simple regression using CPI as the outcome variable and the natural log of per capita GDP as the sole explanatory variable. (I used the natural log partly to reduce the influence of extreme income outliers, and partly on the logic that the impact of GDP on perceived corruption likely declines at very high levels of income. But I admit it’s something of an arbitrary choice and I encourage others who are interested to play around with the data using alternative functional forms and specifications.)

This single variable, ln per capita GDP, explained about half of the total variance in the data (for stats nerds, the R2 value was about 0.51), meaning that while ln per capita GDP is a very powerful explanatory variable, there’s a lot of variation in the CPI that it doesn’t explain. The more interesting question, to my mind, concerns the countries that notably outperform or underperform the CPI score that one would predict given national wealth. To look into this, I simply ranked the 167 countries in my data by the size of the residuals from the simple regression described above. Here are some of the things that I found: Continue reading

Two Essential Volumes on Corruption

The study of corruption and what to do about it is no longer an academic or policy-studies backwater.  Matthew’s bibliography of corruption-related publications now lists over 6,000 books, articles, and reports and, as his regular updates show (thank you Matthew), the list continues to grow at the rate of some 50 plus per month.  That is the good news.  It is also of the course the bad news.  Few practitioners, and I suspect even academics, can claim to have absorbed the learning in the 6,000 current documents let alone keep up with the outpouring of new works.

For those who can’t , I recommend two recent books: Dan Hough’s Analysing Corruption and Alina Mungui-Pippidi and Michael Johnston’s Transitions to Good Governance: Creating Virtuous Circles of Anti-Corruption.  Both do an excellent job of synthesizing and extending recent scholarship on corruption issues, and both do so in a sophisticated but accessible manner.  Both have the added virtue of being available in reasonably priced paperback editions. Continue reading

Coordination by Legislation: Is Regional Anticorruption Legislation in the East African Community a Good Idea?

This past September, at a meeting of the East African Association of Anti-Corruption Authorities, Daniel Fred Kidega, the Speaker of the East African Legislative Assembly (EALA) announced that the regional legislature planned to consider a series of anticorruption and whistleblower bills (also reported here). (The EALA is the legislative body of the East African Community, a treaty organization to which Burundi, Kenya, Rwanda, Tanzania, and Uganda are members.) According to the Speaker’s remarks, “[t]he Laws passed by EALA supercede those of the Partner States on matters within the purview of the Community.”

Details on the legislation are scant, and movement on this proposal does not seem imminent. (Drafts of the proposed legislation are not available on the EALA website, nor could I find them through other sources. And at the mid-October EALA session, anticorruption does not appear to have been on the agenda.) Furthermore, the EAC Treaty does not provide the EALA all of the legislative power the Speaker’s statements suggest, because, according to Article 63 of the EAC Treaty, acts of the EALA only become effective law for member states if each of the five Heads of State “assents” to the measure. Nonetheless, given the interest in East Africa and elsewhere in greater international cooperation on anticorruption efforts, it’s worth reflecting on whether regional anticorruption legislation such as that proposed by Speaker Kidega is a good idea.

I tend to think not. While regional coordination, particularly through conventions, can be an effective way to strengthen anticorruption efforts (as Rick previously discussed in a comment on this post), it is not a good idea in every circumstance (as Matthew noted in a recent post in the context of proposals for a ASEAN Integrity Community). Although the EAC might be able to perform a helpful goal-setting and coordinating role (something akin to an UNCAC or African Union Convention on Preventing and Combating Corruption), the proposal for the EALA to enact more binding regional anticorruption legislation involves more risks than benefits.

Continue reading

The 2014 CPI Data Demonstrates Why, Even Post-2012, CPI Scores Cannot Be Compared Over Time

A little while back, I expressed some skepticism about whether Transparency International’s Corruption Perceptions Index (CPI) scores can be compared across time, even after TI changed its methodology in 2012 and claimed that its new scores would now be comparable across years.  More recently, I criticized TI’s 2014 CPI for burying the information on the margins of error associated with the CPI values, and for wrongly asserting that changes in the CPI score between 2013 and 2014 for certain countries (most notably China) were substantively meaningful.  (In fact, not only does the change in China’s score between 2013 and 2014 seem not to be statistically significant, but the change was due almost entirely to the dropping of a source in which China did abnormally well in 2013, and an abnormally large movement in a single other source.) I decided to follow up on this by taking a closer look at the other ten countries that TI singled out as having experienced significant CPI changes (in either direction) between 2013 and 2014.

Upon closer examination, I’m even more certain that CPI scores cannot be compared over time. I’m also more confident in my judgment that TI has been unforgivably sloppy — and downright misleading — in how it, and its representatives, have portrayed the substantive significance of these CPI changes. It turns out that the problem I found with the China calculations was not unusual. For almost all of the eleven countries TI identified as big movers, the CPI changes were driven by (1) the addition or elimination of sources from year to year for particular countries, and/or (2) abnormally large (indeed, implausibly large) movements in a single source. Until TI fixes its methodology, the safest thing to do is to ignore year-to-year changes in the CPI. And for the sake of preserving its own integrity and credibility, TI should either (A) persuasively explain why I am wrong in my analysis of the data (in which case I will gladly concede error), or (B) issue some sort of retraction or correction to its earlier press releases, and either drop the claim that post-2012 CPI scores can be compared across time or fix its methodology going forward.

Allow me to elaborate my analysis of the data: Continue reading