My paper with the excellent Nathan Goldschlag, Is regulation to blame for the decline in American entrepreneurship? has finally been published. Our paper tests the plausible theory that regulation reduces dynamism as it builds up over time. Michael Mandel explains:
…it’s possible for every individual regulation to pass a cost-benefit test, while
the total accumulation of regulation creates a heavy burden on Americans. The number of
regulations matter, even if individually all are worthwhile.
I call this the ‘pebble in the stream’ effect. Thrown one pebble in the stream, nothing happens.
Throw two pebbles in the stream, nothing happens. Throw one hundred pebbles in the stream,
and you have dammed up the stream. Which pebble did the damage? It’s not any single pebble,
it’s the accumulation.
This is also the theory of regulation and declining dynamism that Mancur Olson puts forward in his classic, The Rise and Decline of Nations. We find, however, that declining dynamism cannot be explained by growing federal regulation. The reason turns out to be simple: the decline in dynamism is widespread across many different industries and, in particular, it is widespread across heavily and lightly regulated industries. Our finding does not imply that regulation is necessarily good–regulations could fail a cost-benefit test and yet not have much of an effect on dynamism–nor does it imply that no regulation could explain declining dynamism only that we should probably look elsewhere for an explanation of declining dynamism than the cumulative growth of federal regulation. See the paper for some suggestions.
Frankly, it’s difficult to publish a paper that fails to reject the null hypothesis. A positive or negative effect is a natural stopping point–ok, they got it, let’s move on–but a zero-effect always leads to complaints that you didn’t run the regression in such and such a way or you could have done such and such a test. The asymmetry in paper evaluation leads to the file drawer problem where published results tend to reject the null even when a random sample of all results would find that the null is supported. We know the file drawer problem is serious because it predicts that studies with small sample sizes should have larger effect sizes–an effect that has often been found.
I can’t complain too much, however, because our paper was published in Economic Policy, a highly-ranked journal, and is the Editor’s Choice paper for that issue. The referees certainly made the paper better.
One of the things we did in the paper to counter the claim that our methods or data were defective was to look for entirely independent tests of the regulation hypothesis. If regulation is the main cause of declining U.S. dynamism, for example, then we ought to find that declining dynamism is associated with declining industry size. But when we look at dynamism, as measured by excess job reallocation rates, and industry employment what we see is that dynamism is declining in both shrinking and growing industries (see above). The paper has many additional tests.
The data and tools in our paper have other applications. Our methods, for example, can be used to distinguish between special-interest and general-interest regulation and could be used to test many other theories in political economy.