This is the third in a series of four blogs featuring key excerpts from the writings of our founder and past president, Richard Zerbe. His insights shaped the foundation of our association and remain relevant to today’s challenges. We hope these selections offer valuable perspectives to all members.

That moral sentiment whose consideration is the most prominent is the Benefit-Cost Analysis (BCA) treatment of distributional matters.

There are four possibilities:

1. Ignore distributional effects.
2. Consider them separately from non-distributional goods.
3. Develop a set of weights to account for distributional goods.
4. Treat them as other goods for which there is a Willingness to Pay (WTP).
5. Separate utility weighting from equity rating.

Ackland and Greenberg suggest separating utility rating from equity rating and incorporating utility rating into BCA and thus into Net Present Value (NPV), but not including equity rating.  Utility rating would account for declining marginal utilities of income. Equity rating would in their view involve a judgement about the morality of equity. The incorporation of utility rating into BCA seems wholly consistent with the foundations of BCA in so far as reasonably reliable estimates of declining marginal utility can be made.  Acland and Greenberg (2023) suggest that equity effects should not be included in BCA, as to do so would rely on judgements not properly a part of BCA. Yet equity rating is also consistent with BCA to the extent that Willingness to Accept (WTA) or Willingness to Accept (WTA) compensation estimates to achieve a moral position can be made.  Thus, to treat moral sentiments, including distributional effects, as other goods is theoretically correct and consistent with BCA but in many or even most cases impractical due to data limitations or costs. Although such estimates could be achieved through survey data. The usual expression of these is in existence values. Even twenty years ago according to Dana (2004, p. 369), more than 2000 contingent valuation (CV) studies have been completed, a significant number of which have been directed toward determining existence values. Existence values are defined by the federal appellate court in the Ohio decision as “the dollar amount an individual is willing to pay although he or she does not plan to use the resource, either at present or in the future.” (State of Ohio v. United States Department of Interior, 880 F.2d 432 (D.C. Cir. 1989)). This case defines contingent valuation as including assessment of option and existence values (and cites 51 Fed.Reg. at 27,692, 27,721 for the definition of existence value). The basis for existence value is a concern for others, including future users, or for the intrinsic value of the thing or the being itself, or for the type of thing or being. Clearly existence values have at least in part a moral component. The Ohio court, at 464, went on: “Option and existence values may represent ‘passive’ use values but they nonetheless reflect utility derived by humans from a resource and thus, prima facie, ought to be included in a damage assessment.” For example, the federal wetlands program and the federal endangered species program are justified only by including existence values (Farber, 1992, p. 64, Dana, 2004, p. 353). In so far as this is possible equity ratings could also be included in BCA.  Otherwise, they should be treated separately but not ignored, for to ignore them is to fail to provide useful information to the decision-maker.

The counterargument to using either utility or equity weights is that distributional changes are best made through the tax system. Such an approach has been suggested, for example by Steve Shavell in an AER article. I have long been in agreement with Acland and Greenberg that the tax system and BCA inhabit different worlds and provide no reason why BCA should avoid distributional considerations.

Current interest appears to be in developing weights for distributional effects.  Such weights are normally an inverse function of income or wealth such that  W = Y^α, where Y is income or wealth, and α is a variable.  For example, for average income α might equal 1, and for lower incomes α might be > 1, or for above average incomes α would be negative. A straightforward example is that W = Y^-1 in which the weight is just the inverse of income of the population.  Using such weights is acceptable in a foundation for BCA, as long as the weights themselves are grounded in WTP or WTA measures from public opinion.