Every now and then, economists come up with ideas that are too radical and cool not to try. Kaushik Basu asking India to legalize paying bribes is one:
The paper puts forward a small but novel idea of how we can cut down the incidence of bribery. There are different kinds of bribes and what this paper is concerned […] harassment bribes [which] is widespread in India and it plays a large role in breeding inefficiency and has a corrosive effect on civil society. The central message of this paper is that we should declare the act of giving a bribe in all such cases as legitimate activity. In other words the giver of a harassment bribe should have full immunity from any punitive action by the state.
The Theory and Experiment
In the spirit of Basu’s best writing, the idea behind this proposal is game theoretic in nature. India is famous for its corrupt political culture. Of course, foreigners sense this from the carefully coordinated heists like the 2G Scam. But most bribery isn’t that sexy, nor is it coordinated. It’s the undignified bribes a commoner must pay to the police officer, or water man. The gift to expedite regulatory approval. (In my case the bribe to bring our American-born Dachshund, Lego, into India without the murder of a quarantine India requires). Basu’s argument is as follows:
- In a “harassment” situation, the bribe giver is humiliated and is eager to bring the taker to justice.
- Under today’s punitive laws he, too, is a criminal and hence must keep quiet. The taker knows this to be the case and hence does not fear punishment – especially as this information is restricted to the two involved parties.
- If the government were to a) legalize the act of giving a bribe and b) incentivize citizens to report illicit activity the dominant strategy for the citizen would be to report the bribe regardless.
Here’s what the payoff matrix might look like with symmetric liability:
|Citizen/Corrupt Official||Accept||Don’t Accept|
|Give and Report||(-5, -5)||(0, 0)|
|Give and Don’t Report||(5, 10)||(0, 0)|
In reality, (Give and Report, Don’t Accept) might be a Pareto-efficient situation, but (Give and report), in this matrix, is not subgame perfect. This means a given citizen cannot credibly threaten to report, and the official knows this. Basu’s insight was noting that it’s not difficult for the government to make (Given and Report) a credible threat. This would force officials to accept transactions without a bribe because they will be penalized if no transactions are processed. (The bribe is just a way of extracting surplus from the citizen)
|Citizen/Corrupt Official||Accept||Don’t Accept|
|Give and Report||(15, -5)||(0, -2)|
|Give and Don’t Report||(5, 10)||(0, -2)|
|Don’t Give||(10, 0)||(0, -2)|
It can be seen that (Don’t Give, Accept) becomes a subgame-perfect Nash equilibrium. (Note, I omitted the Don’t Give option in the first game because it is strictly dominated by the given matrix and hence may be iteratively removed).
The beauty of Basu’s theory is that it’s vindicated not only by matrices, but also empirics. Klaus Abbink, Lata Gangadharan, Utteeyo Dasgupta, and Tarun Jain conducted an experiment in Hyderabad that verifies this theory. The sample (students in major universities around the city) was fairly representative of India’s middle-class as a whole. 55% reported having paid a bribe, and over 60% declared some familiarity with India’s labyrinthine corruptions laws. Participants had the chance of real earnings to the tune of almost $10, ensuring that they took the experiment seriously. For the average Indian student, this is definitely not a trivial sum of money: we should be confident that they played selfishly.
The experiment played a citizen against a corrupt official, as I noted above, with the same moves. Unlike my simpler matrix, they assume a 40% chance of successful prosecution if the bribe is reported, but a 5% chance if it is not, perhaps through a third agent. Citizens and officials are made aware of the potential gains from reporting and taking bribes, but also the risk of fines from a prosecution.
Three games are played. A control where both agents are at risk of prosecution, Basu’s proposal where only the official may be punished. Abbink et al. also consider a third option where the angry official threatens to take revenge on the citizen if he reports the bribe. The results are striking:
We found strong evidence that Basu’s proposal works. Twenty five percent of citizens reported bribe demands in the symmetric case, which increased to 59% in the asymmetric case. In the case of officials, while 38% asked for bribes in the symmetric treatment, this fell to 24% with asymmetric liability as officials feared the impact of greater reporting by citizens. Interestingly, the moral “refusal to pay” did not change significantly as we switched between the two versions (17 versus 19%), suggesting that the law is not a strong guide to moral behaviour.
We find that the impact of asymmetric punishment is reduced considerably when retaliation enters the formulation. Only 42% of citizens report bribe demands and 37% of officials demand bribes, which is close to bribe demands with symmetric liability.
So Basu is correct, unless the official has the capacity to threaten citizens (perhaps with prolonged water shortage, delay, etc.)
While the results of this experiment is a victory for behavioral economics and “out of the box” thinking, one sobering thought caught my eye:
Retaliation takes costly effort, but does not offer the official any explicit rewards. Thus, in our formulation, retaliation is never an optimal strategy and instead hangs as a threat that can be used by a vengeful official.
This is to say that revenge by the official is not a credible threat. Because it’s a costly process to antagonize a citizen, both parties are the worse off. In a world with symmetric information and rational actors, there should be no discernible effect in adding the option of retaliation. To the extent this sample is representative of middle-class, urban India – the game is settled outside of a subgame perfect equilibrium.
This is not to say the government shouldn’t experiment with Basu’s proposal. The idea that fairly petty officials (drunk police officers, etc.) have any long-term rationality is unlikely. Indeed, the only benefit from the non-credible threat of retaliation comes from possible deterrence and I suppose it’s unlikely many such agents have studied the Cold War.
This study decisively rebukes P. Sainath’s scathing critique of Basu’s idea:
The Chief Economic Adviser dresses up these arguments for middle classes forced to make payoffs. For instance when a person allotted subsidised government land “goes to get her paperwork done … she is asked to pay a hefty bribe.” Yet, his law will in no way curb bribery where scarcity exists. For instance putting a child into school where seats are hard to get. Or even getting that flat or the land he speaks of, allotted. Raising the stakes Dr. Basu’s way could mean the victims face heavier demands. After all, the bribe taker needs to be compensated for the higher risk he now runs. And there is no focus at all on government failures that lead to scarcity. Nor on priorities that gift the corporate sector over $103 billion in write-offs in just this budget. Nor on spending policies that cut food subsidies and punish the poor.
If anything it suggests that behavioral game theory can soundly inform empirical study. A country like India, where the center is starved of national mandate, can only rely on the small “nudges” to fix its most damning problems. Basu offers a cheap, brilliant, and neat idea that seems to be defended by experimental study. It is time for the government to pilot similar projects at an increasing scale. Perhaps in cooperation with various municipal governments, the Centre can offer avenues for reporting petty bribes. This also gives India a great chance to work with endeavors such as Janaagraha’s I Paid a Bribe, to catalog the little bribes that dot urban India.
The marriage of technology, behavior, and design (TBD conferences anyone?) might offer India an escape from wasting institutions.