“Pollution for Promotion,” R. Jia (2012)

Ruixue Jia is on the job market from IIES in Stockholm, and she has the good fortune to have a job market topic which is very much au courant. In China, government promotions often depend both on the inherent quality of the politician and on how connected you are to current leaders; indeed, a separate paper by Jia finds that promotion probability in China depends only on the interaction of economic growth and personal connections rather than either factor by itself. Assume that a mayor can choose how much costly effort to exert. The mayor chooses how much dirty and clean technology – complements in production – to use, with the total amount of technology available an increasing function of the mayor’s effort. The mayor may personally dislike dirty technology. For any given bundle of technology, the observed economic output is higher the higher the mayor’s inherent quality (which he does not know). The central government, when deciding on promotions, only observes economic output.

Since mayors with good connections have a higher probability of being promoted for any level of output in their city, the marginal return to effort and the marginal return to dirty technology are increasing in the connectedness of the mayor. For any given distaste for pollution among the mayor, a more connected mayor will mechanically want to substitute clean for dirty technology since higher output is more valuable to him for career concerns while the marginal cost of distaste for pollution has not changed. Further, by a Le Chatelier argument, higher marginal returns to output increase the optimal effort choice, which allows a higher budget to purchase technology, dirty tech included. To the extent that the government cares about limiting the (unobserved) use of dirty tech, this is “almost” the standard multitasking concern: the folly of rewarding A and hoping for B. Although in this case, empirically there is no evidence that the central government cares about promoting local politicians who are good for the environment!

How much do local leaders increase pollution (and simultaneously speed up economic growth!) in exchange for a shot at a better job? The theory above gives us some help. We see that the same politician will substitute in dirty technology if, in some year, his old friends get on the committee that assigns promotions (the Politburo Standing Committee, or PSC, in China’s case). This allows us to see the effect of the Chinese incentive system on pollution even if we know nothing about the quality of each individual politician or whether highly-connected politicians get plum jobs in low pollution regions, since every effect we find is at the within-politician level. Using a diff-in-diff, Jia finds that in the year after a politician’s old friend makes the PSC, sulfur dioxide goes up 25%, a measure of river pollution goes up by a similar amount, industrial GDP rises by 15%, and non-industrial GDP does not change. So it appears that China’s governance institution does incentivize governors, although whether those incentives are good or bad for welfare depends on how you trade off pollution and growth in your utility function.

Good stuff. A quick aside, since what I like about Jia’s work is that she makes an attempt to more than simply find a clever strategy for getting internal validity. Many other recent job market stars – Dave Donaldson and Melissa Dell, for instance – have been equally good when it comes to caring about more than just nice identification. But such care is rare indeed! It has been three decades since we, supposedly, “took the ‘con’ out of Econometrics”. And yet an unbearable number of papers are still floating around which quite nicely identify a relationship of interest in a particular dataset, then go on to give only the vaguest and most unsatisfying remarks concerning external validity. That’s a much worse con than bad identification! Identification, by definition, can only hold ceteris paribus. Even perfect identification of some marginal effect tells me absolutely nothing about the magnitude of that effect when I go to a different time, or a different country, or a more general scenario. The only way – the only way! – to generalize an internally valid result, and the only way to explain why that result is the way it is, is to use theory. A good paper puts the theoretical explanation and the specific empirical case examined in context with other empirical papers on the same general topic, rather than stopping after the identification is cleanly done. And a good empirical paper needs to explain, and needs to generalize, because we care about unemployment (not unemployment in border counties of New Jersey in the 1990s) and we care about the effect of military training on labor supply (not the effect of the Vietnam War on labor supply in the few years following), etc. If we really want the credibility revolution in empirical economics to continue, let’s spend less seminar and referee time worrying only about internal validity, and more time shutting down the BS that is often passed off as “explanation”.

November 2012 working paper. Jia also has an interesting paper about the legacy of China’s treaty ports, as well as a nice paper (a la Nunn and Qian) on the importance of the potato in world history (really! I may be a biased Dorchester-born Mick, but still, the potato has been fabulously important).

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