Sunday, July 10, 2011

Challenges of causal inference in complex systems

From Felix Salmon:

“Spend less money, create more jobs” is the kind of world one normally finds only in Woody Allen movies, and it’s a profoundly unserious stance for any politician to take. Spending cuts, whether they’re implemented by the public sector or the private sector, are never going to create jobs. And there’s simply no magical ju-jitsu whereby government spending cuts get reversed and amplified, becoming larger private-sector spending increases.


I think that one of the difficulties in macroeconomics is that you have complex systems that are not subject to experimentation. So you are forced to try and use observational studies and analogies with microeconomics to try and determine the causal effects of policies. Even instruments are questionable as they also rely on unverifiable, strong assumptions.

The inability to have a consensus on the counter-factual is pernicious and causes no end of trouble. Consider the tax increases passed at the beginning of the Clinton administration. Are they responsible for the late-1990's boom, unrelated to it, or did they act to slow it down (making the current economy smaller than it could have been)? How would you know this?

Cross country comparisons are possible but you have both confounding factors and effect measure modification. Changing the tax rate in Sweden might have different consequences than in the United States due to both different cultures (confounding) and to differences in current tax rates (effect modification). So, by picking different analogies and different models for the observational data, we can end up with some really strange claims being made about how economies work.

It is not an area with easy solutions. But I think to agree with Felix that the model he is critiquing is making heroic assumptions about the influence of tax levels on economic growth.

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