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Bribery, corruption and evolution of pro-social institutions (2)

By News Express on 30/10/2017

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The “Bribery Game” was the usual institutional punishment in public goods game, with the punishing leader, but with one additional choice: players could not only keep money for themselves or contribute to the public pool; they could also contribute to the leader. And the leader could not only punish or not punished, they could instead accept that contribution. What happened? On average, we saw contributions fall by 25 per cent compared to the game without bribery as an option. More than double what the pound has fallen against the USD since Brexit (~12 per cent. Fine, bribery is costly. The World Bank estimates $1 trillion is paid in bribes alone; in Kenya, eight out of 10 interactions with public officials involves a bribe and, as pointed out in the paper, most of humanity – 6 billion people – live in nations with high levels of corruption. The model also reveals that unlike the typical institutional punishment, public goods game, where stronger institutions mean that more cooperation can be sustained, when bribery is an option, stronger institutions mean more bribery. A small bribe multiplied by the number of players will make you a lot richer than your share of the public good.

So can it be fixed? The usual answer is transparency. There are also some interesting approaches, like tying a leader’s salary to the country’s GDP: the Singaporean model. So what happened when these strategies are introduced? Well, when the public goods multiplier was high (economic potential – the potential to make money using legitimate means – was high) or the institution had power to punish, then contributions went up. Not to levels without bribery as an option, but higher. But in poor contexts with weak punishing institutions, transparency had no effect or backfired. As did the Singaporean model. Why?

Consider what transparency does. It tells us what people are doing. But as psychological and cultural evolutionary research reveals, this solves a common knowledge problem and reveals the descriptive norm: what people are doing. For it to have any hope of changing behaviour, we need a prescriptive or proscriptive norm against corruption. Without this, transparency just reinforces that everyone is accepting bribes and you have to be a fool not to. People who have lived in corrupt countries would have felt this frustration first hand. There’s a sense that it’s not about bad apples: the society is broken in ways that are sometimes difficult to articulate. But societal norms are not arbitrary. They are adapted to the local environment and influenced by historical contexts. In the experiment, the parameters created the environment. If there really is no easy way to legitimately make money and the state doesn’t have the power to punish free-riders, then bribery really is the right option. So, even among Canadians – admittedly some of the nicest people in the world – in these in-game parameters, corruption was difficult to eradicate. When the country is poor and the state has no power, transparency doesn’t tell you not to pay a bribe, it solves a different problem: it tells you the price of the bribe. Not “should I pay”, but “how much”?

There were some other nuances to the experiment that deserve follow up. If we had played the game in Cameroon – instead of Canada – we suspect baseline bribery would have been higher. Indeed, people with direct exposure to corruption norms encouraged more corruption in the game controlling for ethnic background. And those with an ethnic background that included more corrupt countries, but without direct exposure, were actually better cooperators than the third generation+ Canadians. These results may reveal some of the effects of migration and historical path dependence. Of course, great caution is required in applying these results to the messiness of the real world. A further investigation into these cultural patterns is hoped to be carried out in future work.

 The experiment also reveals that corruption may be quite high in developed countries, but its costs aren’t as easily felt. Leaders in richer nations like the United States may accept “bribes” in the form of lobbying or campaign funding; and these may indeed be costly for the efficiency of the economy; but it may be the difference between a city building 25 or 20 schools. In a poor country, similar corruption may be the difference between a city building three or one school. Five is more than three, but three is three times more than one. In a rich nation, the cost of corruption may be larger in absolute value, but in a poorer nation, it may be larger in relative value, and felt more acutely.

The take-home is that cooperation and corruption are two sides of the same coin; different scales of cooperation competing. This approach gives us a powerful theoretical and empirical tool-kit for developing a framework for understanding corruption: why some states succeed and others fail, why some oscillate; and the triggers that may lead to failed states succeeding and successful states failing.

Our cultural evolutionary biases lead us to look for whom to learn from and, perhaps, whom to avoid. They lead us to blame individuals for corruption. But just as atrocities are the acts of many humans cooperating towards an evil end, corruption is a feature of a society not individuals.

Indeed, corruption is arguably easier to understand than my fearless acceptance of my anonymous barista’s coffee. Our tendency to favour those who share copies of our genes – a tendency all animals share – lead to both love of family and nepotism. Putting our buddies before others is as ancient as our species, but it creates inefficiencies in a meritocracy. Innovations are often the result of applying well-established approaches in one area to the problems of another. We hope the science of cooperation and cultural evolution will give us new tools in combating corruption.

Putting aside what it means for something to be natural for our species, suffice to say these are recent inventions in our evolutionary history, by no means culturally universal, and not shared by our closest cousins. Genes that identify and favour copies of themselves will spread, helping those who help you! The United Nations Human Development Index ranks the United States 10th in the world. Liberia is 177th.

Temporal discounting: the degree to which we value the future less than the present. Our tendency to value the present over the future is one reason we don’t yet have Moon or Mars colonies, but the degree to which we do this varies from society to society.

Written laws can serve a signalling and coordination function, rather than having to interpret norms from the environment. When previously contentious norms are sufficiently well established, you may do well to codify them in law (legislating before they are established might mean more punishment: consider the history of prohibition in the United States).

Singapore’s leaders are the highest paid in the world, but the nation also has one of the lowest corruption rates in the world: lower than the Netherlands, Canada, Germany, UK, Australia and United States. Note, there are some conceptual issues that make interpretation of the Singaporean treatment ambiguous.

•Lawrence Nwaodu is a small business expert and enterprise consultant, trained in the United Kingdom and the Netherlands, with an MBA in Entrepreneurship from The Management School, University of Liverpool, United Kingdom, and MSc in Finance and Financial Management Services from Rotterdam School of Management, Erasmus University Netherlands. Mr. Nwaodu is the Lead Consultant at IDEAS Exchange Consulting, Lagos. He can be reached via nwaodu.lawrence@hotmail.co.uk (07066375847).

Source News Express

Posted 30/10/2017 7:25:09 PM

 

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