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Statistics

Index-a-thon

Since we bashed Transparency International’s Corruption Perception Index, it just wouldn’t be right if we ignored the brand new Human Development Report which is, it just so happens, chalk full of indices. Fortunately, it’s not all bashing this time.  (We have a love-hate relationship with statistics.)

Just which indices are we talking about here? The alphabet soup of HDR acronyms includes the well-known Human Development Index (HDI) and, this year, adds several others such as an Inequality-adjusted HDI and a Gender Inequality Index as well as a new Multidimensional Poverty Index.  The idea behind these measures is to look at aspects of poverty like education and health that can’t be seen through the lens of traditional income growth statistics.

Bear with us for a quick breakdown (or just skip ahead for some bashing):

The HDI includes three dimensions—health, education, and income—measured from life expectancy, school enrollment rates, literacy, and GDP per capita.  The new MPI expands upon this concept even further by combining health and education indicators like child mortality, nutrition, years of schooling, and child enrollment with standard of living measures such as access to electricity, drinking water, sanitation, flooring, cooking fuel and basic assets like a radio or bicycle.  The goal in all of this is of course to look at holistic deprivations, not just income poverty—recognizing that “people’s lives cannot be measured simply in terms of money or income.”

As we mentioned before, throwing a bunch of different ingredients together with arbitrary weights of importance can be a recipe for a completely muddled version of reality.  Because weighting (or giving importance to indicators) is pretty arbitrary, UNDP weighs everything equally and also has a website where anyone can build their own development index to assign their own weights to whichever indicators they want.

UNDP has also responded to past criticisms by providing disaggregations of the indicators.  For example, income can be the sole driver behind a country’s HDI improvement (which, by the way, is exactly the case for China this year).  Since this obviously doesn’t paint an accurate picture of what is happening, the report lists countries’ HDI improvements accompanied by gains from non-income HDI.  This emphasizes the point that indices are often misrepresentations of reality if taken at face value—but at least UNDP is trying to get that message out there, too.

The MPI is another story altogether.  It has come under more fire because it aggregates  even more poverty indicators.  The pros? MPI can add more nuance to the MDGs by showing overlap between different dimensions—that is, it can figure out in how many ways an individual is poor.  This is important for comparing inequality among regions and even within countries.  The cons? For starters, it compares “apples and oranges” while implicitly putting value equivalencies on human lives.  And the need for homogeneous data means the indicators were drawn from less rich data sets.  Looking at it this way means it amounts to no more than an intellectual exercise since the most useful part of the data, as is the case with the China example above, comes from when it’s broken down, not mashed together.

Kudos to UNDP for highlighting the complexities of poverty but, as always with statistics, proceed with caution.  Or, in other words: “Math may be the language of the Devil, but statistics proves that reality really is what you make it.” (Stephen Colbert)


Heritage Foundation loves being awesome

The Heritage Foundation is adorable.

A recent article published in their foreign aid section lambasts the UN’s “statist” approach to development, arguing that it merely entrenches corruption.

I argued last week that Transparency International’s Corruption Perceptions Index (CPI) looks a lot like the Heritage Foundation’s bullshit Index of Economic Freedom. Thankfully, the defenders of liberty are here to prove that two indices which essentially measure the same thing will show a correlation.

Really, I love these guys.


Not so transparent: measuring corruption

Cartoon courtesy of University of Colorado
Transparency International (TI) just released their 2010 Corruption Perceptions Index. For those of you unfamiliar with CPI, its an attempt to measure and rank  corruption in each country based on “expert opinions” from 10 “independent sources”. I think you can see where we’re going with this.

First, let’s see what TI says corruption is.
Transparency International (TI) defines corruption as the abuse of entrusted power for private gain. This definition encompasses corrupt practices in both the public and private sectors.”

This definition, sufficiently broad gives TI the flexibility it needs to examine something as abstract as corruption. However, such a broad view should include a broad, diverse group of sources. But that isn’t the case with TI. TI’s sources are all pretty much on the same side of the political spectrum. Lets see if you can find the similarities:

1) Bertelsman Foundation
2) Freedom House
3) African Development Bank
4) Asian Development Bank
5) World Bank CPIA
6) Economist Intelligence Unit
7) Global Insight
8) IMD International- Switzerland
9) Political and Economic Risk Consultancy
10) World Economic Forum

Oh wait, looks like they forgot to include ANY  nationally-based sources for data. But maybe these guys are the only ones with sufficient data?  Well, not entirely….since a half of these sources gather all of their data by surveying (mostly expatriate) businessmen (IMD, WEF, PERC, IMD and GI).So the ‘perception’ of corruption would appear to be the perception of the ease of doing business.

Other sources that don’t just survey expats still focus on business data for their perception of corruption. Freedom House (already of dubious neutrality), considers an “excessive state presence” in economic affairs as a proxy for corruption. Likewise, the World Bank CPIA and EIU conception of corruption still focuses entirely on the role of state in business. Bertelsman Foundation has likewise come under some criticism for compromising its declared neutrality through neoliberal advocacy (article is in German). This might explain why CPI ranks Singapore as less corrupt than Sweden. Or how South Africa ranks higher than Rwanda, which has nearly draconian anti-corruption laws.

The end result is that TI’s CPI ends up looking a lot like Heritage Foundation’s Index of Economic Freedom, something which few development practitioners or academics take seriously. Can business leaders provide insight into the workings of a state’s commercial, industrial or tax policy? Absolutely. But, given that corruption is also a private-sector phenomenon, should business leaders be given the sole power to judge the integrity of a state? Hell no.

In terms of the actual methodology, TI has been courteous enough to explain that their indicators shouldn’t be used to measure trends, since the sources used for each country change every year.  As a result, you get a snap-shot, not a big-picture analysis.  Even the World Bank, one of CPI’s sources has lambasted the aggregation of dubiously compatible indicators:

“There is a strong desire to quantify the entire concept of corruption into a single index, so that it may be compared across countries and over time. Unfortunately,corruption is such a complex phenomenon that attempts to compress it into a single number lead to results that are imprecise (at best) and misleading (at worst). This is not to say that corruption should not be studied. On the contrary, there is a great need for good measures of governance and corruption.

Organizations such as Transparency International say that corruption indices likethe CPI are a “wake-up call to political leaders and to the public at large to confront theabundant corruption that pervades so many countries.”33 The truth is that governmentsand citizens are fully aware of the corruption which pervades their country. The problem is that the people are powerless to stop corruption.”

booyakasha.