Is That Government Best Which Regulates Least?

In a recent post, I questioned Henry David Thoreau’s aphorism, “That government is best which governs least.” The data, it seems, show something different. Countries with small governments, as measured by the share of expenditures and taxes in GDP, tend actually to be somewhat less free and prosperous than those with larger governments. The quality of government, as measured by things like rule of law, independent judges, and integrity of government officials turns out to matter much more than the size of government. I concluded that Thoreau’s aphorism should be revised to read, “That government is best which governs well.
In response, several readers questioned whether the size of government, as measured by spending, was the right measure of “governs least.” Excessive regulation, they pointed out, may do more damage than spending and taxes. Maybe what we should say is, “That government is best which regulates least.”
Niskanen Center’s Will Wilkinson puts it this way:

Whether a country’s market economy is free — open, competitive, and relatively unmolested by government — is more a question of regulation than a question of taxation and redistribution. . .
If we want to encourage freedom and prosperity, we should pay more attention to easing the grip of the regulatory state.

The point is a good one — worth putting to the same kind of statistical test used in the previous post. Here we go:

Data sources for prosperity: The Legatum Prosperity Index, a composite measure of but good health; access to food, clean water, shelter and education; safe communities; clean environment; and related indicators. The Social Progress Index, a similarly broad measure of human flourishing.
Data sources for freedom: The Human Freedom Index from the Cato Institute and the Personal Freedom Index from the same source, a subset of indicators that leaves out purely economic aspects of freedom like freedom of trade and sound money.
Data sources for regulation: The measure of regulatory freedom from the Cato data base, and the similar regulatory component of the Index of Economic Freedom from the Heritage Foundation. Both indicators are scaled in a way that assigns higher scores to countries with more “regulatory freedom,” that is, less regulation.
A first look at the data does show a positive association between regulatory freedom and prosperity. For example, data from 131 countries for the Heritage index of regulation and the Social Progress Index indicate that countries with higher regulation scores (less regulation) are in fact more prosperous. As measured by the statistic R², about 46 percent of differences in prosperity are statistically associated with differences in regulation. Similar findings are obtained by substituting the Cato measure of regulation or the Legatum measure of prosperity.
However, statistical association is not the same as causation. After all, we would find a similar positive relationship between the heights of all children in a grade school and their scores on a standardized math test. It would be wrong, though, to conclude that being tall makes people better at math. The apparent relationship would be a statistical illusion caused by the fact that sixth-graders are better at math than first-graders, and also happen to be taller. If we corrected for age, the correlation between height and math scores would disappear.
Much the same is true for the relationship between regulation and social prosperity. It turns out that most of the apparent statistical association between the two variables is a result of their level of development, as measured by per capita GDP. At any given level of development, whether high or low, countries with high scores for regulatory freedom do not score much better on noneconomic aspects of prosperity (population health, education, environmental quality, access to information, and so on) than do countries at similar levels of development but with low regulation scores. Similarly, once we control for differences in GDP per capita, regulation scores have little explanatory power for between-country differences in personal freedom.
However, it would be wrong to interpret these findings as proof that regulation does not matter. I could be, instead, that the Cato and Heritage indicators are just bad measures of those aspects of regulation that are important to prosperity and freedom.
A further comment by Wilkinson gives a clue as to why this might be the case:

Free markets require the presence of good regulations, which define and protect property rights and facilitate market processes through the consistent application of clear law, and an absence of bad regulation, which interferes with productive economic activity. A government can tax and spend very little — yet still stomp all over markets.


Wilkinson is exactly right. Bad regulation is a drag on freedom and prosperity but good regulation facilitates them. The problem with the Cato and Heritage indexes of regulation is that they indiscriminately jumble together regulations of all kinds, the good with the bad. The result is statistical mush that is incapable of explaining anything.
To distinguish the good from the bad, we need to look both at the aims of a regulation and the way it is implemented. Good regulations are those that have benign aims and are efficiently implemented. Bad regulations are those that have bad intentions, or good intentions that are badly implemented, or both.
Here are some guidelines, that can help distinguish good regulations from bad ones:
Retain regulations that support the basic rules of a market economy. Those include regulations that protect property rights, ensure that contracts are honored, and protect against common law harms like fraud, negligence, and nuisance. In principle, such rules can be enforced through civil litigation, but courts can be slow and costly. It may, for example, make more sense to send inspectors to ensure that nightclubs keep their fire exits unlocked than to wait for relatives of the deceased to sue a club’s owners for negligence after a fire occurs.
Replace regulations that have legitimate aims but are ineffective or have harmful unintended consequences. For example, in an effort to reduce CO2 emissions, CAFE standards set minimum gas mileage for new cars. Meeting the standards raises the price of cars, but better fuel economy lowers the cost per mile of driving. The unintended consequence is that people drive more, roads are more congested, and more accidents occur. A carbon tax would be a more efficient way to reduce emissions, since it would encourage people both to buy efficient cars and to drive them less.
Repeal regulations that are motivated primarily by the manipulation of public policy for private gain — what economists call rent seeking. Regulations that restrict competition or impose price controls rarely serve any purpose other than enriching special interests at the expense of the public. Restrictive occupational licensing provides many examples.
Following these “Three R’s” would do more to promote prosperity and freedom than mindlessly cutting regulations across the board. It is not really true that that government is best which regulates least. Rather, that government is best which regulates well.

Previously posted on Medium. For further information on methodology and data sources behind the statistical results, see “The Way Economic Freedom Indexes Measure Regulation is Deeply Flawed.”