The New Corruption Perceptions Index Identifies Countries with Statistically Significant Changes in Perceived Corruption–Should We Credit the Results?

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

Fighting Environmental Corruption in the Mekong River Basin: More Firepower Needed

The forests, wildlife, plants, and vegetation of the Mekong River Basin are under sustained assault.  Not from some virulent new fungus or mutant virus.  No, the attacker is a man-made pathogen: the inability of the region’s governments to curb the rampant corruption eating away at the legal structure that protects the basin’s ecosystem.  Officials of basin governments are being paid to condone logging in conservation zones, to issue export permits for protected flora and fauna, and to otherwise flaunt laws meant to prevent an environmental catastrophe.  No other ecosystem is under such deadly assault, and unless the trend is arrested, the World Wildlife Fund predicts that within 20 years the region, twice the size of California and rivaled only by the Amazon for biological diversity, could lose more than a third of its remaining forests along with the exotic plants and wildlife that inhabit them.

The six governments of the region – Cambodia, China, Lao PDR, Myanmar, Thailand, and Vietnam – have declared war on environmental corruption and have begun counterattacking.  Environmental protection laws are being tweaked, and investigators and prosecutors trained to detect and prosecute environmental crime.  But important though these steps are, in the face of impending ecological disaster more firepower is needed.  Here are four ways to step up the fight: Continue reading

Can’t See the Forest Because of the (Missing) Trees: How Satellite Imagery Can Help Fight Illegal Logging

Illegal logging is one of the gravest threats to the environment, and to the people (and countries) that depend on forest resources. Global Witness’s 2013 Annual Review describes industrial logging as a force that “drives land grabs, promotes corruption, contributes to climate change, fuels conflict and human rights abuses, and threatens over one billion people who rely on forests for their livelihoods and well-being.” The problem has been documented with surprising depth. Prominent examples include investigative work done by Global Witness (including two short films, Inside Malaysia’s Shadow State, which shows undercover interviews with members of then-Chief Minister of Sarawak Taib Mahmud’s family and legal team advising a “foreign investor” how to use bribery and fraud to illegally clear land for a palm oil plantation, and Rubber Barons, which documents land grabbing by a Vietnamese rubber firm), as well as other groups like the Environmental Investigation Agency, which recently recounted how army officials protect Chinese loggers’ passage into Myanmar, despite new laws entirely banning foreign exports of logs. In the popular media, NPR’s All Things Considered and The New Yorker looked at illegal logging in Russia and allegations of its yield being sold by major U.S. retailers, while The Economist called out HSBC’s involvement with dirty loggers. The issue is not confined to developing economies—a World Bank paper enumerated the breadth and variety of possible illegal acts surrounding the logging industry and its products worldwide, noting that practically all involve corruption. The problem, then, appears well-known and reported but remains widespread, possibly getting worse.

Illegal logging remains persistent largely because of pervasive corruption. A number of proposals have already laid out systems to address forestry corruption. Possibilities include land tenure arrangements that give management to local or indigenous groups, certification schemes for wood products, and a variety of monitoring and transparency mechanisms. A 2009 World Bank report provided a “comprehensive framework” involving five principal parts, each with a number of sub-components. Scholars, NGOs, and international organizations have noted the need for technology to increase monitoring capabilities. Technological developments may offer the key to progress in the fight against illegal logging—allowing circumvention of (or greater pressure on) the corrupt government officials who ignore, or sometimes participate in or profit from, the unlawful destruction of forests.

A previous post discussed one such technology, isotope provenancing, used to identify the origin of wood. This technology, however, has its limits. (For example, it does not help when forests are razed not to harvest the timber, but to clear the land for other uses, such as palm oil and rubber plantations.) Other new technologies can help show how corruption in the logging industry happens, working forward from the site of the problem instead of tracing back from imported products. One of the most promising tools—satellite imaging—is in fact already available, and could be very effective if deployed more appropriately and aggressively.

Continue reading