Rolling Back Regulatory Complexity

November 24, 2014 • Cato Online Forum
By Megan McArdle

If there were one simple thing that we could do to promote economic growth, and I knew what it was, I wouldn’t be writing this essay; I’d be touring the world’s luxury resorts in a chariot pulled by lions. Alas, we are unlucky to discover an easy route to growth, because growth itself is never simple: it is the products of millions and billions of people making individual decisions that add up to a collective choice to do things a little bit better. If there were easy rules that could consistently make this process go more smoothly… well, communism would have worked spectacularly well, and most of the authors in this series would be toiling anonymously in the bowels of some gleaming government ministry.

But the failure of central planning doesn’t mean that policy doesn’t matter; it does, and we could do better. It’s just that the changes we need are many, not few, and not always easy to describe in one succinct sentence. So here’s a suggestion that will not fix everything, but could fix some of the barriers to “doing things a little better”: we need a regulatory budget.

Before you protest that we already do cost‐​benefit analysis, let me be clear that this is not what I’m talking about. The American government indeed already performs cost‐​benefit analysis on new regulations, which attempts to price government rules the way bankers price securities: so many dollars in the plus column for a single life saved, so much in the minus column for the costs to a factory owner. One could make many quarrels with the methods used for this analysis, but I am not going to, because whatever the method’s faults, it’s better than the alternative method of ignoring costs entirely. CBA’s main failure isn’t that it calculates costs wrong; it’s the fact that it misses one of the biggest and most pervasive costs of our current regulatory state: the cost of complexity.

A few years back, I had a conversation with a very smart, very progressive analyst who had left the Public Intellectual Industrial Complex in order to go into business for himself. A few years later, he retreated back into the fold, and the reason he gave for this was deeply disturbing: he found it impossible to know whether he was in compliance with the law.

I won’t dive into details, but suffice it to say that this man was not running a toxic waste disposal business; he was running a tech startup. But even this business, that ought to be lightly regulated, was surrounded by red tape. He hired experts, of course, but he had no way to check their decision; if the payroll company tacked an extra $100 on his weekly bill, he had to trust that they were collecting money that was really owed, rather than boosting the office Christmas party fund.

This sort of uncertainty haunts innovators at every level, from a guy inventing a toy, to a company trying to build a self‐​driving car. Regulators rarely calculate the individual uncertainties that their laws create, and more importantly, they never calculate the collective effect of adding on more regulations, at multiple levels of government, every year.

The key thing to understand about regulatory complexity is that it doesn’t just add up: it multiplies. Every new regulation potentially interacts with many old regulations, and as the number grows larger, the consequences of those interactions grow harder to predict. Eventually the law passes the potential of a single person, or even a team of experts, to fully understand it.

To see what I mean, imagine a brand new system that is just passing laws and regulations for the first time. In the early days, each new rule potentially intersects with a handful of other laws. Let’s call each of these intersections a “complexity point”: a spot where two laws may conflict, create unclear lines of authority, or interact in unanticipated ways to create negative unintended consequences.

As time goes on, however, the number of potential intersection grows. An early law had a handful of complexity points; a later law may have a few million. Over time, too, many of these complexity points get litigated, creating case law that itself offers more complexity points.

What this means is that the complexity cost of new rules grows over time. At our advanced age, any new regulation is very expensive indeed, complexity‐​wise. This deters some potential entrants, but it also changes the shape of the competitive landscape. Large corporations that can afford vast reserve armies of paid experts, overseen by a battalion of in‐​house regulatory and legal specialists, have a massive competitive advantage over smaller upstarts that have to roll the dice and hope their attorneys guessed right.

Most of the Cato Institute’s readers won’t find it hard to believe that excessive regulation is undesirable. But the important point is that this problem afflicts even the best regulations. It applies to a rule requiring cops to wear video cameras, as well as to a rule requiring African hair braiders to pass an expensive licensing exam. Framing the problem as “bad regulations” misses the real problem with the system: even good regulations are now so expensive, in complexity points, that they are probably not worth passing.

To attack this problem we need to stop thinking about regulations individually and start thinking in terms of a budget. Instead of analyzing whether the calculations in a regulatory ledger sum to a positive or a negative number, we need to set a level of complexity that we’re willing to live with, and then decide which positive sum regulations we’re willing to discard in order to stay within that budget.

Creating a framework to do this in a sophisticated way would obviously be a massive task. But there are crude rules which might well serve, like capping the number of laws and regulations, allowing a new one to be implemented only if an older one is repealed. The most important shift, however, may be cognitive: we need to start talking about this as a large and pressing problem to be solved, before we get lost in the forest, counting the trees.

The opinions expressed here are solely those of the author and do not necessarily reflect the views of the Cato Institute. This essay was prepared as part of a special Cato online forum on reviving economic growth.

About the Author
Megan McArdle