8.5.16

LOGARITHMS.

If you torture the data long enough, Nature confesses.  But the implements of torture are part of the contested territory in academic research, particularly academic research when somebody wants policy implications.  Thus a recent tussle between John "Grumpy Economist" Cochrane and Brad "Grasping Reality" DeLong over the correlation between Ease of Doing Business (yeah, that's an index number, all the usual cautions apply) and Per Capita Output.  Greg Mankiw is collateral damage.

Here's the methodological point.
My graph is an illustration of a conclusion reached by hundreds, if not more, papers in the academic literature. It is not The Evidence, or even particularly novel evidence. Were it so, standard errors, specification search, endogeneity, much better measures of institutions, etc. would be appropriate, as many suggest. My graph is just a quick graphical illustration of the conclusions of much growth economics, including much work by Jones, Acemoglu, Barro, Klenow, and many many others. Institutions matter to economic growth; bad governments have amazing power to ruin economies.  As always in writing, I should have made that clearer; but I thought this literature was familiar to the average economist-blogger.
The political economy point is of greater import.
Did North Korea or East Germany first get poor and then get bad institutions? Did the UK and US first get rich, and then develop our rule-of-law and property rights traditions? Is reverse causality at all a plausible explanation for the correlation? Just about every historical episode you can think of goes the other way.
True, but fussing over specification and sign and significance is the essence of Getting Publishable Results.

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