Sunday, April 1, 2012

The Nexus Of Corruption And Higher Income Part III

[I’ve been working on this for over a week now, hope you enjoy it. Since this is a very long post, I’ve split it into three parts. This is Part III]

Continued from Part II


The idea that corruption has a dampening effect on income levels and/or growth is intuitively appealing, yet the data doesn’t appear to support any causal relationship of any kind. In fact, the conclusion appears to be that the relationship is technically spurious – corruption affects neither the level or growth of income, nor does income affect the level or rate of corruption (or should I say, the perception of corruption).

Here’s some of the reasons why I think the results came out the way they do:

  1. Accuracy of the dataset – The CPI scores are composites of surveys of business people on their experience with corruption in their respective countries. Taking the CPI scores as given means accepting that the CPI number accurately reflects actual corruption. That may not be true for a number of reasons, such as differences between opinion and actuality, or instances of corruption that might not impinge on the business community (NFC is a good example, since it allegedly involves CBT, rather than bribery). I also suspect the CPI score says more about the level of trust in public institutions as much as actual experience of corruption.
  2. Lags in the data – Because the CPI score is a reflection of business community perception of corruption rather than its incidence, there might be a lag structure to the data. For example, if a corruption case is exposed today, it might raise the perception of corruption now (a lower CPI score) even though the actual corruption might have occurred years before. That suggests increasing transparency might have a short term perverse effect on the CPI score, before returning perception returns to its “true” level.
  3. Variance in the dataset – While TI puts in considerable effort at arriving at a definitive CPI score (and kudos to them for trying), the variance of the scores in the individual surveys can be pretty wide – as much as 1 point or more. That means the data can be a bit “fuzzy”, especially for those countries with lower scores – the variance is noticeably smaller for countries with high CPI scores. In which case OLS regression analysis (which works towards minimising errors) might not be capturing the true relationship, simply because the distribution of the actual level of corruption might be too wide.
  4. Non-linear relationship between corruption and income – There’s the possibility that corruption only affects national income and growth at certain ranges of corruption. That may be true especially at the bottom of the income scale, as the relative costs of corruption on society might be larger. Past a certain income level, the costs of corruption might rapid diminish. Applying the same analysis to subsets of the data might reveal a causal relationship. I’d tend to discount this explanation though, as looking at the individual country scatterplots tends to show a relatively stable value of the CPI against higher and higher income levels.
  5. The fallacy of composition – Corruption is often seen to be a dead loss to the economy, but that’s only true at the level of the individual economic agent. It largely isn’t true for the economy as a whole. Money spent on bribery for instance transfers wealth and income from the briber to the bribed – one loses and one gains. But from the perspective of GDP, the difference in terms of growth and spending will only be seen in terms of the differences in marginal consumption and saving between the two parties. If the bribed spends as much as the briber, then total expenditure within the economy doesn’t change. Only if the briber has a smaller propensity to consume will income levels and growth be negatively affected (incidentally, that suggests that venal corruption should be more tolerated than large scale corruption), or if the expenditure takes place elsewhere, e.g. buying condos in Australia instead of in Malaysia. What this means is that the impact of corruption should primarily be seen through rising income and wealth inequality (the distribution of income), and/or through capital flight,  but not in GDP or GDP growth.

Any or all of the factors above could be in play, or just as likely, that the analysis I’ve done is correct and there’s some other factor driving both variables – income inequality for instance, or the integrity of social and political institutions, for example.

But the bottom line here is that the available evidence that I’ve been able to come up with just doesn’t support a causal link between income and corruption, or vice versa.

I’ll conclude with the actual data for Malaysia; it’s illustrative of problem (CPI score against GDP per capita; red line is the estimated regression):


Malaysia shows a negative relationship between the CPI score and GDP per capita – so if you believe that there is a causal relationship, the way to increase our income level is to increase the perceived level of corruption. That obviously can’t be right. A more plausible explanation? The CPI score is actually pretty stable from 1995 to 2008 – I wonder what happened then (*cough*).

Moving on (CPI score against GDP per capita growth; red line is estimated regression):


Here the estimated relationship is slightly positive (higher CPI leads to higher growth), but the sample coefficient is statistically indistinguishable from zero; in other words, there’s no detectable relationship.

The most appealing explanation I can come up with for the data is that increased transparency post-2008 and the proliferation of online news channels and social media activism, has seen evidence of past corruption increasingly surfacing and that’s been reflected in a higher perceived level of corruption (lower CPI score).

It isn’t that corruption is increasing, it’s that we’re more aware of it and increasingly intolerant of it. Which is a good thing, and signals in a way our increasing development as a society. But I don’t expect that reducing corruption will, on its own, help Malaysia become a high income nation.

Technical Notes:

  1. Corruption data is from Transparency International’s Corruption Perception Index, from 1995 to 2011
  2. GDP per capita data is taken from the IMF World Economic Outlook database (September 2011) – series code PPPPC.


  1. True indeed, by right, the economic crisis should not happen in Europe as their CPI index is higher...bu right the London yoith could notmhave rioted because the English queue when they board up the bus.

    There is just too many variables to correlate GDP growth with a gamutbof factors..for all I know, we can even correlate the cleanliness ofmour public toilets with economic growth but

    i do work with statistics but in the manufacturing sector using minitab..seems there is no correlation of CPI with GDP growth primarily because CPI is not measurable but a perception and we know we have citizens who put doen the perception of our country...getting a positive perception on corruption in Malaysia would be impossible IMO.

  2. Hi Hishamh,

    First of all, thanks for the awesome study. It has really given us a lot of insight on corruption and economic growth.

    I think you may have said this, but not exactly in these words. Also, it wasn't exactly clear from your 2nd part. May I know how you had defined GDP growth or GDP per capita growth. If my assumption is correct, and that you had used year-on-year growth, then I think it would not be too surprising to encounter almost no correlation. My take on this is that, from year to year, I would think that any number of factors would affect GDP growth (global economic conditions, commodity prices, bad weather, etc). Corruption would be a pretty insignificant factor for short-run growth. Perhaps you may have tried this, but I think there should be a much stronger link between corruption and long-term growth. It's hard to say how long term is long term though. Plus, I think you may have been handicapped by the short CPI data.

    Also, another small issue that I am not entirely sure is that, perhaps, developed countries (which I assume tend to be less corrupt), will tend to have smaller growth rates, courtesy of the fact that their GDP is already at a high base. So, if your data does not go far back enough to reflect the transformation from a low income economy to a high income economy, it will create sort of a distortion in the sense "low corruption may be correlated with low growth".

    I am not trying to poke holes into your study here. I really think that it has definitely given us a lot of things to think about. Really appreciate it.

  3. @anon

    Yes, I think that the perception of corruption might not be a good indicator of corruption itslef.



    Re: Growth is calculated on a y-o-y basis. But consider this, for long term growth to be higher (i.e. systematic negative correlation against the CPI), you'd also have to see systematically higher short term growth as well. However you define it, long term growth is still a function of short term growth. You can't have low short term growth and higher long term growth.

    On your second point, if that were true, you should find a weak negative relationship between income and corruption - in fact, that's what I was expecting to find. But the interesting thing is that I found no relationship at all - GDP per capita growth is a constant across the CPI measure, which suggests that GDP growth on a per capita basis doesn't really change going from low income to high income either (only the variance seems to change). That in turn suggests that's there's no such thing as a poverty trap, or a middle income trap.

  4. Kudos on a very revealing & insightful analysis. Now I have to go away and ponder on this for a while :)

  5. Salam,

    I wonder whether or not a GDP per capita is actually an excellent tools to measure whether or not corruption has seeped into a nation economic system...

    Don't get me wrong, I always thought that CPI score is not an accurate statistical data before. Then again, suppose a nation riddled with corruption. By qualitative logic, this nation would still have a significant growth albeit this growth is shifted towards a certain individuals or entity... This growth is undoubtedly may be reflected into the nation GDP. Assuming illicit flows through corruption negligible.

    Shouldn't a better tools for data representation uses a wealth distribution measures instead of GDP Per Capita...

    Then again is there such a tools to better capture wealth distribution...??

    Anyway, great post and nice presentation...kudos

  6. Hishamh,

    I agree that long-term growth is indeed a function of short-term growth. But what I was trying to say is that, the CPI this year may not necessarily impact the economic growth this year. There is going to be a lot of noise if you look at that alone. For example, Indonesia. The CPI has been improving consistently over the last 10 years, but there is no significant change in the growth rate. But if you were to look at how Indonesia had performed in the previous 10 years (1990-1999) compared with 2000-2009, there is a significant change in the average growth rate, and I think part of this can be attributed to less corruption. Perhaps you can use the moving average of the economic growth in the 10 years ahead.

    On the second point, yes, there could be some negative relationship between corruption and GDP per capita growth. Because not all developed countries have high CPI. Only some. Also, there is a possibility that corruption has yet to "eat into" economic growth. It may take several years before the vested interests become entrenched and start siphoning income away from the economy. How about accounting for the level of income by including income-level dummies like high income, middle income and low income (based on World Bank definitions), to control for that? Just some thoughts. Thanks for the prompt reply.

  7. @akubas86

    Actually I thought of that - see point 5 in the discussion above. The problem with using income/wealth inequality is that there's a lot of other things going on with that as well, like tax structures and whether there's a social safety net. Also, income inequality data is really patchy except for in some advanced economies, and wealth inequality measures very nearly don't exist at all.


    On the first point, I've looked at the data, and Indonesia's growth rate has actually fallen not risen in the last ten years compared to the previous ten (which included the 1997-98 crisis). Remember we're looking at per capita GDP, not GDP itself. Using a moving average might not be useful, because it'll mute any changes in the data - you're actually less likely to find any statistical relationship. There's also the problem of reducing the degrees of freedom.

    Interesting sidenote: if you look at Japan's "lost decade", per capita growth isn't that bad, even if headline growth has tanked. It's actually pretty close to other advanced economies like the US and Germany.

    On the second point, I thought of that and its on my to-do list. I didn't incorporate that before because the whole dataset was already getting pretty complicated.

  8. My apologies. I had forgotten that you were looking at GDP per capita. On that note though, I just had another thought. Would there be a difference if you had used local currency vs USD? I mean, if we talk about Indonesia, per capita GDP in Rupiah is most certainly to surge due to the currency depreciation. I hate to give the impression that I am just sitting here criticizing the study and letting you do all the work. Haha... sorry about that.

    I looked at the data for Indonesia (using IMF), but it doesn't have constant prices for per capita GDP in USD, while the World Bank data, though it gives real per capita GDP in USD, it assumes a fixed exchange rate throughout the data (constant 2000 USD). Which means that the growth rates in USD and Rupiah are exactly the same. So, no help there. Next, I tried to compute the "implicit exchange rate" by dividing the per capita GDP in Rupiah with the per capita GDP in USD (using IMF data). Using this exchange rate, I reconstructed the "real GDP per capita in USD". If you look at it in USD, I think it becomes more obvious that per capita GDP in Indonesia has done poorly in the 1990s. Maybe I am doing something obviously wrong here. If so, I apologize in advance.

    On the Japan note, I think that's probably a worse sign. Since the headline tanked, it means that the population is shrinking.

  9. Shihong,

    Indonesia was far more badly affected by the 1997-98 financial crisis than Malaysia was. If you take away those two years, I think you'll find that average growth in the 1990s was still higher than in the following decade. Using your methodology, the drop in real GDP per capita in USD terms was over 75% in 1998 alone. I'm not sure if that would be a fair comparison.

    On Japan, you're absolutely right - it's the impact of demographic change. That's the reason why I've focused on the per capita GDP, rather than overall GDP.