Raymond Fisman and Edward Miguel, Economic Gangsters: Corruption, Violence, and the Poverty of Nations

I started off thinking that maybe this book’s title should be Gather Ye Data Where Ye May. It starts with a couple neat chapters where the authors try to measure various hidden variables — how much one company’s fortunes depend on connections to a dictator, say, or how much gets smuggled into a particular country. You can get a reasonable measure of smuggling by counting exports from one country and imports into another. The authorities only tax you on the way in, not on the way out, so you have every incentive to lie on the import forms and tell the truth about your exports. If 10,000 BMWs leave Hong Kong destined for China, and only 9,000 arrive in China having been shipped from Hong Kong, you can guess that about 1,000 BMWs were smuggled out of Hong Kong into China. Perhaps they were creatively relabeled ‘Hyundai,’ thereby carrying a much smaller tariff burden.
The authors dig a bit deeper into the numbers and point out a loophole that nations ought to fill if they want to modernize their system of duties: give similar products similar tariffs. One example here is amusing: a “boring/milling machine — numerically controlled” used to get a 10% tariff on its way into China, whereas a “boring/milling machine — other” got a 20% tariff. People have every incentive to claim that their boring/milling machine — other is actually a boring/milling machine — numerically controlled. The closer the products are in appearance, the easier it is for importers to pass off the one as the other and evade the higher tariff. (The authors give us a thought experiment, wherein chickens and turkeys come in for different tariffs. I only wish this were real. It would make me smile.)
Next the authors ask: is there any way to measure how corrupt a nation is? They find a smirk-worthy means of measurement: look at how often diplomats pay their parking tickets. Diplomats, you’ll remember from the Lethal Weapon movies, can wave diplomatic immunity around anything and magically get off scot-free. This includes parking violations. So find some place where a large number of diplomats congregate and see whether they pay their tickets even though they don’t have to. As it happens, the UN fits the bill: New York City keeps detailed records about which ambassadors received citations, which nations they represent, how much they were fined, and whether they paid the bill. From this, Fisman and Miguel get a rough measure of corruption, which they can try to connect to other measures like the World Bank’s.
Don’t think for a moment that I take this particularly seriously, by the way. The “parking metric” is a rough measure, at best, of what you’d do if you knew no one was looking. What’s vexing, then, is that the authors seem to take it quite seriously indeed. 40% further on in the book, we see Fisman and Miguel writing about Africa’s history of extractive industries feeding nothing back to their people, “To the extent that stealing parking spots in New York City really is correlated with stealing government funds, Chad is in for trouble.” This example just doesn’t do much at all of the heavy lifting that they expect it to. The authors seem surprised that other researchers could have accomplished much without parking data: “Even without hearing of the wanton parking habits of Chad’s diplomats, donor organizations were fully aware of the endemic corruption in Chad’s government …”.
So maybe, goes the implication, nations remain poor because their people are fundamentally corrupt. Or maybe not: the next chapter considers the possibility that domestic instability — civil wars, particularly — result from drought. That is: the rain stops falling, and the only available work is in a gang. Not a terribly controversial idea. The authors’ approach is novel: send in the peacekeepers when drought makes war look likely. Get a rapid-response team to stop wars before they start. There are unexpected curiosities here: during droughts, there’s more witch-burning, and the witches tend to be old women. The authors speculate that this might be the survival instinct disguised as superstition: old women consume more resources, so they have to be the first to go. The policy response they propose here is old-age pensions: turn the women into village assets, rather than liabilities.
We might label the connection among all of these “discovering the economic gangster in all of us”: under what circumstances would we become corrupt or join a militia or burn a “witch”? How bad would the world around us have to get? And how do we use this knowledge of human self-interest to prevent disaster? Economic Gangsters is a slight introduction to these questions, and didn’t really feel solid enough to justify the time. I suspect there’s a better book on the same topic out there.





