As most readers of this blog are likely aware, last month Transparency International (TI) released the 2017 edition of its important and influential Corruption Perceptions Index (CPI). As usual, the publication of the CPI triggered a fair bit of media coverage, much of it focused on how various countries ranked, and how individual country scores had changed from one year to the next (see, for example, here, here, here, and here).
There’s a lot to say about the most recent CPI—I may devote a post at some point to TI’s interesting decision to focus the press release accompanying the publication of the 2017 CPI less on the index itself than on the connection between (perceived) corruption and a lack of adequate freedom and protections for the media and civil society. But in this preliminary post, I want to take up an issue that regular GAB readers will know has been something of a fixation of mine in past years: the emphasis—in my view mostly misplaced—on how individual country CPI scores have changed from year to year.
In prior posts, I’ve raised a number of related but distinct concerns about the tendency of some commentators—and, more disturbingly, of some policymakers—to attach great significance to whether a country’s CPI score has gone up or down relative to previous years. For one thing, the sources used to construct the CPI for any given country may change from year to year—and adding or dropping an idiosyncratic source can have a substantial effect on the aggregate CPI score. For another, even when the underlying sources don’t change, we don’t know whether those sources are on the same implicit scale from year to year. And even if we put these problems to one side, a focus on changes in the final CPI score can sometimes obscure the statistical uncertainty associated with the estimated CPI—these scores can be noisy enough that changes in scores, even those that seem large, may not be statistically meaningful according to the conventional tests. Although TI always calculates statistical confidence intervals, in prior years these intervals have been buried in hard-to-find Excel spreadsheets, and the changes in CPI scores that TI highlights in its annual press releases haven’t always been statistically significant by TI’s own calculations. In an earlier post, I suggested that at the very least, TI should provide an easy-to-find, easy-to-read table assessing which changes in country scores are statistically significant at conventional levels, preferably over a 4-year period (as 1-year changes are both harder to detect if trends are gradual, and less interesting).
Apparently some folks within TI were thinking along similar lines, and I was pleased to see that in the 2017 CPI includes a reasonably prominent link to a spreadsheet showing those countries for which the 2017 CPI score showed a “statistically significant difference” from that country’s CPI score in each of five comparison years (2012, 2013, 2014, 2015, and 2016).
I’ve still got some criticisms and concerns, which—in the spirit of constructive engagement—I’ll turn to in just a moment. But before getting to that, let me pause to note my admiration for TI as an organization, and in this case its research department in particular, for constantly working to improve both the CPI itself and how it is presented and interpreted. It’s easy for folks like me to criticize—and I’ll continue to do so, in the interests of pushing for further improvements—but it’s much more challenging to absorb the raft of criticisms from so many quarters, sift through them, and invest the necessary time and resources to adapt and adjust from year to year. So, in case any folks at TI are reading this, let me first acknowledge and express my appreciation for how much work (often thankless) goes into the creation and continued improvement of this valuable tool.
Having said that, let me now proceed to raising some comments, questions, and concerns about TI’s claims about countries that appear to have experienced statistically meaningful changes in their CPI scores over the last five years. Continue reading