One of the curious things about coming to law school was discovering the very high regard that “economics” is held in, at least in some areas like torts and contracts, where “law and economics” has become the primary theoretical construct. In essence, this school of thought holds either that the law has developed in such a way as to promote efficient economic outcomes, or that it should promote efficient economic outcomes. There is now an empirical branch of law and economics, but historically the law and economics approach was largely theoretical. For example, in United States v. Carroll Towing Co., 159 F.2d 169 (2d Cir. 1947), Judge Learned Hand wrote that the whether behavior is negligent should be determined by multiplying the probably of an accident by the cost of the accident and comparing that to the cost of taking precautions. Twenty-five years later, Richard Posner argued that this rule would lead to the optimal level of accident prevention, because it doesn’t make economic sense to pay more for accident prevention than the corresponding reduction in the expected costs of accidents; at that point, the firm would be better off just paying damages to accident victims. (There, now you don’t need to take first-year torts – just apply that principle everywhere.)
The Hand-Posner principle has filtered into the world of public policy and regulation as the argument that the benefits of regulation must exceed their costs. This argument is ascribed to Cass Sunstein, who “cruised through Tuesday’s Senate confirmation hearing” to be the “regulatory czar” in the new administration, which sounds much more powerful than “Administrator of the Office of Information and Regulatory Affairs” in the Office of Management and Budget. Sunstein is a widely respected law professor who specializes in just about everything (constitutional law, administrative law, regulation, and now behavioral economics – he co-authored Nudge – with a brief foray into the death penalty on the side).In principle, he would be able to review new regulations being defined throughout the executive branch. So the cost-benefit model of regulation – already favored by the previous administration – may become more firmly entrenched in the federal government.
While this makes perfect sense in principle, I’m skeptical of how it works in practice. The basic problem is that it’s difficult if not impossible to measure either the probability of an accident or the expected costs of the accident, especially since there is a wide range of potential accidents and a wide range of potential outcomes (among other things, the same injury to different people will have a different compensable value, since damages are based in part on wage loss).
Take seat belts, for example. This should be an easy case: it couldn’t have been that hard, back in the 1960s, to estimate the number of lives and injuries that would be saved by installing seat belts and making their usage mandatory. It shouldn’t be that hard to estimate some of the expenses that would be saved – police and firefighters, vehicle damage, medical expenses, etc. But what about death or long-term disability? Or just simply having recurring back pain for the rest of your life? What is that worth? It is true that our legal system has ways of valuing these things, but they are outgrowths of common law (whenever you hear the term “common law,” think of 16th-century English judges deciding cases about horses and cows, and you won’t be too far off) and they produce results that are at worst perverse – if you’re going to run over someone in a car accident, hit the old person on Social Security, not the young hedge fund manager – and at best incomplete. For the most part, if it can’t be bought and sold in a market (like cars, or labor), it has no value.
This can be a particular problem when it comes to regulations that affect health or the environment. It affects any chronic health condition that simply makes people feel worse, since it’s difficult to quantify the cost of your feeling crummy. (I know there are economists who work on this kind of valuation; they include my wife, which is why I know how difficult this is.) Then imagine trying to do the cost-benefit analysis on reducing emissions of greenhouse gases. It’s easy to estimate the cost of technology to reduce smokestack emissions. But what’s the cost of not doing so? How do you estimate the total cost of the ice caps melting, sea levels rising, violent storms becoming more frequent, huge swaths of agricultural land turning to desert, and so on? How do you estimate the benefits of new shipping lanes opening up? And how do you estimate the likelihood of any of this happening?
Finally, to return to our favorite application, imagine that the government had considered the idea of systemic risk regulation five years ago. It would have cost money; it would have created new disclosure requirements for banks and possibly hedge funds; it would have required countercyclical measures in a boom that would dampen economic growth. Those are the costs of regulation. And how would anyone have estimated the benefits? No one would have estimated the scenario we face today – trillions of dollars of asset writedowns, 3.3% contraction in the U.S. economy and counting, even more severe damage elsewhere in the world economy. And as a result, the regulation would have died.
To be honest, I’m a bit conflicted about this whole issue. I think that conceptually this is the right way to think about government policy, and in many areas we could certainly use more of it. But it’s a mistake to think that all policies can be boiled down to cost-benefit calculations when one side of the equation is difficult or impossible to measure accurately, and the last thing we need today is more economics-based overconfidence. Sunstein did say that the approach shouldn’t put regulation “in an arithmetic straitjacket,” so we’ll have to see what he actually does.
Originally published at the Baseline Scenario and reproduced here with the author’s permission.