In regulatory cost benefit analysis the discount rate translates future value to present terms.
The first three essays in this series on the Office of Management and Budget’s draft revisions to Circular A-4 on conducting regulatory impact analysis discussed broad themes related to context, distributional effects, and humility. In this one, I drill down on one important input in estimating regulatory impacts—the “discount rate” or “social rate of time preference.” Most regulations are designed to generate benefits and costs over time. The discount rate used to translate future impacts to present value terms can have a very large effect on whether regulation looks worthwhile.
Regulatory costs, such as investments in pollution control equipment or redesigning nutrition labels, often occur up front, while benefits may be projected to occur far into the future. OMB’s draft Circular A-4 directs agencies, as a first step, to “present the undiscounted annual time stream of benefits, costs, and transfers expected to result from a regulation, clearly identifying when they are expected to occur.” This is an important step that even the most sophisticated agencies do not always follow. Highly significant rules are sometimes accompanied by an analysis that simply presents a snapshot of benefits and costs at a future date. EPA’s recent air quality rule, for example, presents partial estimates of costs and benefits for the year 2032 and beyond. By 2032, capital costs have already been incurred and projected health benefits are at a high point. This snapshot is neither transparent nor informative.
Presenting the full streams of resource flows agencies expect their regulations to cause is thus a necessary first step in understanding impacts, but it is not sufficient. Due to the time value of money, a dollar a year from now is worth less than a dollar today. If you borrowed a dollar now, you would owe that dollar plus interest a year from now. The discount rate is simply the flip side of the interest rate: future benefits and costs must be discounted to estimate their present value. For government regulations, the discount rate reflects the opportunity cost of the resources that will no longer be available for other uses. In some cases, discount rates may also reflect the risks associated with the activity. (Note that regulatory impact analysis projections use “real,” inflation-adjusted dollars, so discount rates do not include expected inflation.)
The discount rate can also be thought of as a “hurdle rate”—a rate of return that government projects must earn in order to be considered worth pursuing. At one time, OMB’s guidance directed agencies to use a rate of 10% in conducting benefit-cost analysis. OMB guidance in 1992 established a standard rate of 7%; and the existing 2003 directive encourages agencies to use both 3% and 7%. OMB’s new draft guidelines provide a single lower default discount rate of just 1.7%. As the hurdle rate gets lower, many more regulations will appear attractive because projects that incur costs in the near term to achieve benefits in the future will look better than they would using higher discount rates.
The proposed new rate is not only dramatically lower than past practice but much lower than the rates experienced by those actually affected by regulation. For example, when the Department of Energy sets tighter standards for consumer appliances, a 1.7% discount rate will make consumer savings over time appear much bigger than consumers—who face borrowing costs much higher than that—will experience. (According to Business Insider, the average interest rate for personal loans today is 21%, or 18% after adjusting for inflation; those with lower income or poor credit ratings face higher rates.) Similarly, as EPA and Department of Transportation regulations push consumers into electric vehicles, the agencies will claim consumer fuel savings (as well as climate benefits) that appear much larger on paper than in consumers’ pocketbooks.
The draft revised Circular does offer agencies alternatives to using the 1.7% rate. It devotes seven pages to a discussion of sophisticated methods to account for uncertainty, risk, and the shadow price of capital. These have some theoretical support, but little widespread use in practice. They are also too complex for all but the most experienced agencies to apply on their most economically significant regulations; even commenters who support application of these methods say OMB would need to provide more guidance on how to account for these factors before agencies would be able to use them appropriately.
Given the complexity of accurately accounting for time preferences, agencies will likely fall back on the draft Circular’s default rate of 1.7% for all effects from the present through 30 years into the future. OMB justifies this rate by pointing out that it was derived using the same method that was used in 2003, updated with more recent data (the most recent 30-year yields on 10-year Treasury notes). This may not be the best method for several reasons, including that interest rates in recent years were subject to Federal Reserve policies that are unlikely to continue in the future. Experts who support the administration’s approach recognize that other reasonable assumptions would lead to quite different rates.
Given the uncertainty involved in selecting an appropriate rate and how important the discount rate is in estimating the value of a regulation, the Circular should not direct agencies to use a single number. OMB simply cannot have enough confidence in the underlying assumptions to rely on a single rate (and certainly not one as unjustifiably precise as 1.7%). Instead, the Circular should continue the practice of directing agencies to present estimates reflecting a range of plausible rates.
OMB’s proposed discount rate appears to be another example of a pervasive bias: the draft guidelines attempt to put a thumb on the scale in favor of this administration’s policy preferences, rather than presenting neutral guidance to inform decisions. If the final guidance directs agencies to use this low rate, agencies will find it much easier to justify new regulations that impose short-term costs in exchange for the promise of long-term benefits on “analytical” grounds rather than policy preferences.
