Impact of corruption on American Recovery and Reinvestment Act

One generally gets to read such papers for emerging/developing economies. It is interesting to read them in developed country context.

Anders Sundell of University of Gothenburg in this paper says US states which are more corrupt ended up being more efficient in stimulus spending and creating more jobs:

In this paper, I attempt to gauge the effects of corruption on the stimulus package, by comparing projects awarded grants in the 50 US states, using a two-level modeling strategy. First, for each state, the cost of a project is modelled as a function of the number of people employed in the project, which yields a job cost coefficient. The assumption is that a lower coefficient implies more efficient spending. Second, the job cost coefficient is modelled as a function of corruption in the state, controlling for other state-level factors. The empirical analysis shows that the job cost coefficient is higher in states where more public officials have been convicted for corruption, implying that corruption impairs the possible effect of the stimulus package.


The paper has some interesting discussion on corruption and its impact on economy:

To discuss the effects of corruption on economic efficiency, it is first necessary to define what corruption is. While there are plenty of definitions, a widely used one is that corruption is the misuse of public office for private gain (Rose-Ackerman, 2008). Public officials may be both politicians and bureaucrats.

For long, the effects of corruption on economic efficiency and growth were understudied, and several scholars argued that corruption possibly could have beneficial effects. For instance, Leff (1964) argued that corruption could stimulate economic growth by increasing competition among bureaucrats in the government bureaucracy and thereby increasing governmental efficiency. It could also work as a “hedge” against bad governmental policies, by allowing entrepreneurs to implement their favored policies, aided by corrupted bureaucrats. Moreover, corruption could also reduce uncertainty, in that entrepreneurs need not fear governmental intervention as much when the bureaucracy is corrupted. Bribes could also act as “speed money”, and reduce government inefficiency (Mauro, 1995).

Needless to say, an underlying tendency in this strand of research is low trust in government. Governmental policies are seen as intervening in an efficient market and bureacratic rigidity and inefficiency is seen as impeding growth. Empirical studies  demonstrating the negative effects of corruption on economic growth and performance now abound (Evans & Rauch, 1999; Mauro, 1995; Mo, 2001), and this is reflected in policy shifts among policymakers, for instance the World Bank (Holmberg,  Rothstein, & Nasiritousi, 2009). 

Superb stuff especially on how corruption could stimulate economic growth. This looks so fitting for India which manages to grow 9% despite corruption in all corners and walks of life. Though, corruption leads to different kind of competition amidst bureaucrats here. Each one wants to capture more of the available pie. In India’s case the idea that corruption acts as a hedge against inept policies seems more likely. Need to look at these papers closely.

He suggests two mechanisms by which corruption could undermine ARRA:

  • Direct – corruption leads to market prices being higher or the corrupt official could siphon off funds by inflating costs
  • Indirect – the overall corrupt climate makes anything to do difficult.

The paper however looks at job creation in states and maps it with corrupt states and finds those states which are more corrupt are more inefficient (high costs and lower jobs created)

Interestingly, there are different measures of corruption and states ranking is different with least corrupt showing most corrupt in other analysis. But overall, it does not change the findings. If you plot coefficient of jobs with corruption you see a steep curve showing more corrupt the state, higher the inefficiency.

Interesting paper.

It will be interesting to model this study on India’s flagship scheme – NREGA. Do we see similar kind of results with more corrupt states showing  less effectiveness of NREGA? I would guess so. Though in India’s case it will be very difficult to rank states based on corruption. They all look the same with some marginal differences. Till now, this was not the case but with so many scams being exposed in different states, one is not sure how they are different.

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