Make Benefit-Cost Analysis Meaningful

Abstract

In 1947, economist Tjalling Koopmans wrote a review of the book Measuring Business Cycles, written by his fellow economists Arthur Burns and Wesley Mitchell. The title of Koopmans’s review, Measurement Without Theory, referenced the fact that Burns and Mitchell had collected and summarized impressive amounts of macroeconomic data and described in detail the business cycle fluctuations they observed, but they had not drawn sufficiently on economic theory to explain the observed regularities in their data. By omitting theory that might otherwise give their data context and meaning, Burns and Mitchell’s contribution was cast into doubt. In more recent years, there is another area where theory has taken a backseat to empirical measurement: namely, the theory behind benefit-cost analysis (BCA). BCA intends to predict how regulations and other public policies impact society for better or worse. Conspicuously missing from BCA, however, is the necessary theory connecting whatever BCA is measuring to the well-being of actual people. Debates over the relative merits of theory versus empirical measurement are not new to academic inquiry. In the late 19th century, for example, a debate took place in the German-speaking world over the importance of theory as it pertains to economics. On one side of the Methodenstreit, as the debate came to be known, was the so-called German historical school, led by Gustav Schmoller. Schmoller cautioned against fundamental laws in economics, arguing that historical context and culture are always changing and that outcomes will vary by time and by place. Theory can be developed, he accepted, but careful measurement comes first. Only after extensive data collection and analysis can hard conclusions be drawn, or so members of the historical school believed. A group of economists in Austria, led by Carl Menger, viewed matters differently. They saw an important role for theorizing in the social sciences, believing that a scholar can construct an idealized model economy and, through careful reasoning, arrive at certain fundamental truths about its workings. Insights can then be extended to the messy and complicated world around us, with its nearly unlimited and imperfect data that can often be contradictory and misleading. Furthermore, any analysis of data involves theory—theory is impossible to escape—because understanding what data represent is critical to their interpretation. If we fast forward to today, we see similar debates playing out in economics. When measuring the effects of the minimum wage, some commentators act almost as if measurement is all that matters, as if “Econ 101” supply and demand theory, which would otherwise indicate that artificially high wages mean fewer jobs, can be cast aside. When an empirical study finds no employment effects, they conclude that those who reason based on the theory of supply and demand must be ideologues. But are they? Or are our data and measurement techniques too imperfect to detect the law of downward sloping demand in a fast-paced world? These kind of issues are also at play in BCA. Open up a textbook and it will likely tell you that the welfare measure underlying BCA is economic efficiency, which relates to maximizing a broad conception of society’s overall wealth. But BCA, at least as it is produced in the government and in countless academic studies, is not measuring efficiency. This is true for at least two reasons: First, BCA does not properly account for the opportunity cost of capital, detailing how capital would be employed with and without a government policy change. Second, BCA applies weights to consumption based on when the consumption occurs in time. With respect to the opportunity cost of capital, economists have understood, since the early 1960s, that the proper way to account for the opportunity cost of capital in analysis is by using a shadow price, which is a factor by which all capital benefits and costs are converted to equivalent units of consumption. Sometimes this conversion device is called a marginal cost of funds factor. Whatever the name used, without such a conversion, comparing one dollar of capital to one dollar of consumption is comparing apples to oranges. The government tries to address this issue by using a discount rate, but its approach is almost always inappropriate. Units of consumption and units of capital are all discounted at the same rate, as if they are growing over time at the same rate. But consumption benefits dissipate quickly, while the returns to capital can increase with time as some are reinvested. Treating these different benefits as if they are the same gives too much weight to consumption—capital increases social wealth by more. Through discounting, the analyst also applies a set of weights to consumption streams based on who receives them and when. If John receives a consumption benefit worth one dollar today, this benefit receives more weight than if Sally receives an equivalent benefit next year. But is Sally’s consumption really so different from John’s? Even if it is, a government analyst is ill-equipped to distinguish how this experience varies across people. From the standpoint of economic efficiency, a dollar’s worth of consumption should always receive the same weight (adjusting for inflation, of course). Equal weighting along these lines is standard within a time period but for some reason it becomes controversial across time. Analysts must be careful not to attribute characteristics of individuals—like time preference, diminishing marginal utility, or risk aversion—to society as a whole, an error known as a fallacy of composition. Ironically, Koopmans himself, through his influential work on time preference, likely contributed to this tendency of analysts to blur individual and social characteristics. BCA has been a fundamental part of the regulatory process in the U.S. federal government since the early 1980s. Executive Order 12,866, which governs the U.S. regulatory analysis and review process has just enjoyed its 25th anniversary. The government’s benefit-cost watchdog, the Office of Information and Regulatory Affairs, has existed for nearly 40 years. And yet, after all these years, what exactly is BCA measuring? If not efficiency, then what? Without a clear welfare measure, BCA is like a rudderless boat adrift at sea. It can be a useful tool, but to be truly useful in practice, first BCA has to measure something meaningful in theory