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Be's avatar
Oct 10Edited

I am an economist and I regard that paper as rather weak evidence for the case that regulations reduce growth, for the same reason alluded to in the post: all the variation is over time in a single country.

From what I can tell, the paper was published because their time series analysis is integrated with a macroeconomic model such that they can parse out a relationship with total factor productivity, and because their results are in line with other papers that don’t rely solely on time series analysis. As always, one should draw inferences on the basis of the literature as a whole and update only weakly on individual papers. If the cited papers are using cross-country analysis this is better than time series analysis but has its own issues, and it makes some sense to see what happens if you try a pure time series approach, which the authors of this paper did. Ultimately it’s difficult for us to know much about a causal effect of total regulation because it is composed of many heterogeneous regulations and jurisdictions are large and few enough that we can’t really apply the sort of quasi-experimental methods that are the standard for estimating causal relationships.

The bull case for deregulation comes from looking at all the individual cases where overregulation is deeply harmful (housing, project permitting, drug development, nuclear, occupational licensing, etc.) and becoming redpilled to the apparent tendency of progressives and the federal bureaucracy to impose grievous costs for scant gains (though obviously some regulations are necessary). But it’s not enough to make some regulation that under ideal conditions results in some good thing and then pat yourself on the back for a job well done, there are usually assumptions that don’t hold, unmeasured costs, and unintended consequences.

(Edited for paragraph spacing)

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The Water Line's avatar

A technical point: it’s not really accurate to say regression analyses are regarded as good evidence. It heavily depends on why and how you conduct the analysis.

It’s like saying “using microscopes is considered good evidence.” Well… sometimes?? Depends what you’re looking at and what you’re concluding based on that. If you’re trying to find the weight of an elephant, using a microscope is the wrong tool. Regression analyses can also be the wrong tool in many circumstances.

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