In May I wrote about libertarian Will Wilkinson’s defense of the welfare state. I wrote:
Part of Wilkinson’s point, though, is to distinguish between the redistributive state and the regulatory state. It’s the latter, he argues, that more frequently impedes innovation.
My view is somewhat less pessimistic, and my bottom line in 2015 was:
Even the assumption that bureaucratic “red tape” holds back startups is less obvious than it sounds… What evidence we do have squarely challenges the intuition that it’s government that holds back startups.
But if Wilkinson is going to acknowledge the entrepreneurial benefits of the welfare state, liberals ought to at least consider the possibility that regulations do hamper innovation.
Putting entrepreneurship and innovation aside for a second, it seems clear that the net benefits of regulation vary considerably depending on which ones you’re talking about. The Clean Air Act seems to have had large positive effects. On the other hand, overzealous land use regulations that prohibit building have had large negative effects.
The same is likely true of regulation and entrepreneurship. Plenty of regulations probably aren’t a big impediment; some even help. But plenty of others probably do hold back innovation.
Generalizing about the economic effects of regulation was hard, it seemed to me, since there are cases of regulation that are obviously net positive and cases that are arguably net negative. Now, that’s true of other government interventions, too; there’s better and worse welfare state programs, for instance. Nonetheless, the aggregate evidence that the welfare state and redistribution have been net positive seems reasonably compelling.
But Wilkinson’s Niskaten colleague Ed Dolan has a nice post in which he does some rough-and-ready statistical analysis exploring the relationship between regulation indices and measures of prosperity and well-being. In the absence of clear aggregate evidence on the effects of regulation (that I know of) it is quite interesting:
When all is said and done, our search among the economic freedom data from Heritage and Fraser for evidence of the effects of the regulatory state has been frustrating. We are left with the following conclusions:
Simple correlations do find positive and statistically significant relationships between measures of regulation and commonly used measures of prosperity and personal freedom.
Half or more of the relationships implied by simple correlations turn out to come from the strong correlations of regulation, prosperity, and personal freedom indicators with GDP per capita. Controlling for income, wealthy countries with light regulation have only slightly better freedom and prosperity outcomes than wealthy countries with average regulation.
In multiple regressions that account for the interaction of regulation with other components of economic freedom, the statistical power of the Fraser and Heritage regulation indicators to explain cross-country variations in prosperity and personal freedom evaporates altogether.
Close examination reveals serious methodological problems in the way both the Fraser and Heritage regulation components are constructed. Neither makes adequate efforts to distinguish between helpful and harmful aspects of regulation. Both include some indicators that fit poorly with common notions of what the regulatory state really is and does, and both exclude important aspects of regulation (especially of international trade).
Dolan, who does worry about the negative effects of at least some regulation, sees this largely as exposing the flaws of the most common regulatory indices. And it reiterates my almost tautological starting point: there’s good regulation and bad. But it also suggests that, broadly, regulation is not on average and in general a huge factor holding back our economies.