Behavioral economics finds that under predictable circumstances people sometimes fail to act rationally and in their own best self-interest. In these circumstances, public policies can nudge people towards better choices. For example, people can be nudged to save more, smoke less, lose weight, and buy more energy efficient vehicles and appliances. In addition to providing new insights about how to design public policies (see Chetty 2015), behavioral economics also has implications for how we conduct benefit-cost analysis (BCA). After all, BCA is built on the foundation of neoclassical welfare economics and rationality. This topic has been explored over the years in the Journal of Benefit-Cost Analysis, notably in a March 2016 Special Issue on [Ir]rationality, Happiness, and Benefit-Cost Analysis. 

In his new book, "Behavioral Economics for Cost-Benefit Analysis" (Cambridge University Press, 2017), David L. Weimer (University of Wisconsin – Madison) pulls together the insights of behavioral economics to provide “useful guidance for those actually doing BCA.” Because behavioral economics has wide-ranging implications for almost any policy, members of the Society for Benefit-Cost Analysis will very likely find Weimer’s book of interest. 

As those familiar with his textbooks on policy analysis and BCA know, Weimer writes clearly and effectively. In his new book he combines his commanding knowledge of the craft of BCA with insights from sources that range from economic theory to psychological and behavioral economic laboratory experiments. These insights raise many questions about how to conduct BCA, and Weimer provides his answers to many of the questions. He notes, however, that if his book leads other researchers to challenge his answers, it will also help the development and practice of BCA. 

The book’s intended audience of practitioners and academics will usually have had masters- or doctoral-level training in economics and BCA. However, Weimer relies on verbal explanations and only makes sparing use of equations and graphs. I plan to use the book as a supplementary reading for my upper-level undergraduate BCA course. The book is a useful source for benefit-cost analysts to learn about behavioral economics, and vice versa.

After an introductory chapter, Chapter 2 reviews neoclassical applied welfare economics and Chapter 3 reviews intellectual efforts to incorporate behavioral economics into welfare economics. Chapter 3 gave me a better understanding of Bernheim and Rangel’s behavioral welfare economic framework. (Although I have found the original theoretical papers challenging, Bernheim’s contribution to the JBCA Special Issue (Bernheim 2016) provides a useful and accessible overview.) Their framework analyzes individual welfare when choices reflect both neoclassical preferences and ancillary conditions that capture behavioral insights. Bernheim and Rangel’s work lays the foundation for a general approach to behavioral BCA, and I look forward to seeing well-developed practical applications. 

In the rest of the book Weimer relies heavily on the behavioral economics distinction between decision utility that describes how people make choices and the experienced utility that actually flows from those choices. For BCA, Weimer and others -- including my behavioral BCA of anti-smoking policies (Jin et al 2015) -- make the normative assumption that the allocation of resources should be valued in terms of people’s experienced utility.   

The book’s next four chapters provide the real meat of the book, and this brief book review can give just a taste. Chapter 4 discusses the compelling evidence that decision-making under uncertainty often departs from expected utility maximization, which leads many behavioral economists to favor prospect theory. Weimer works through the practical implications of prospect theory for BCA calculations of the expected surplus from a policy change under uncertainty, as well as the implications for the design of stated preference studies. Chapter 5 reviews the well-known large discrepancies between willingness to pay and willingness to accept. Weimer emphasizes that even in the neoclassical framework the value people place on reductions in goods that have few substitutes can lead to very large willingness to accept values. However, he does not dismiss explanations from behavioral economics, and once again provides an especially useful discussion of the implications for the design of stated preference studies. 

Chapter 6 reviews evidence from behavioral economic research that people are impatient in ways that are not captured by the standard exponential discounting of future benefits and costs. Experiments often find that people place extra weight on immediate rewards, which is known as present bias. For example, someone might choose one apple immediately rather than two apples tomorrow, but choose two apples in one year plus one day from now over one apple one year from now. Chapter 7 discusses the difficult and controversial question of how to conduct BCA of policies that affect addictive consumption. An idea that comes up in both chapters is that BCA should include people’s willingness to pay for policies that reduce the disutility of self-control in responding to immediate temptations. I also like Weimer’s suggestion that revealed and stated preference studies of people’s willingness to pay to overcome addiction are a promising way forward for BCA.

A key feature and contribution of Weimer’s book is a set of Practical Guidelines (PGLs) that distill the main lessons learned for the practice of BCA. Weimer embraces the case-by-case approach to incorporate behavioral economics into BCA. I hope and predict that Weimer’s list of PGLs will soon sit alongside references like Circular A-4 on regulatory impact analysis and become part of the standard guidance for the practice of BCA.

Of course, actually putting the PGLs into practice will be challenging. For example, PGL 3.2 gives the sensible advice that: “In assessing benefits, ignore departures from rationality that do not substantially affect observed behaviors.” The PGL advice echoes Circular A-4’s advice that a regulatory impact analysis should describe and attempt to quantify “significant” market failures. Both pieces of advice are good but, like a lot of good advice, they are hard to put into practice. Nobody optimizes perfectly and no markets function perfectly. When are individual optimization failures “substantial” or market failures “significant”?

The nature of the evidence base from behavioral economics poses additional challenges for putting PGL 3.2 and Weimer’s other PGLs into practice. Much of the evidence base about individual failures to optimize comes from psychological and behavioral economics laboratory experiments. Several potential threats to external validity mean that evidence of substantial departures from rationality in the laboratory might not extrapolate to a real-world policy problem.  Because they are such a convenient source of subjects, there is some truth to the joke that what we’ve mainly learned from experiments is about how college sophomores behave. Moreover, one of the most important insights from behavioral economics is how much context – such as the framing of a choice – can matter. Behavioral economic experiments might not be very closely aligned to the context of real-world BCAs. 

Another threat to the external validity of experimental evidence is that markets might produce rational results even when some individuals display substantial departures from rationality. Weimer discusses this in more detail. He points out, for example, that a small number of rational participants might be enough to dominate the market or to allow implicit learning by the less rational participants. Fortunately, field experiments are becoming more common in behavioral economics and will provide a more reliable evidence base about whether individual optimization failures are substantial in real-world contexts.

Neoclassical economics and behavioral economics have fans and foes. Opinions might vary, but I think Weimer’s thoughtful discussions and PGLs strike a nice balance. He is not too quick to abandon the neoclassical foundations of BCA, nor does he ignore the substantial body of behavioral economics research. His book might be described as taking an evidenced-based approach to improve the methodology and practice of BCA. Weimer’s book should make a real difference in how BCA is viewed and how it is practiced.

References
Chetty, Raj (2015). "Behavioral Economics and Public Policy: A Pragmatic Perspective." American Economic Review. 105 (5): 1 – 33.

Bernheim, B. Douglas (2016). "The Good, the Bad, and the Ugly: A Unified Approach to Behavioral Welfare Economics." Journal of Benefit-Cost Analysis. 7(1): 12-68. 

Jin, Lawrence, Don Kenkel, Feng Liu and Hua Wang (2015). "Retrospective and Prospective Benefit-Cost Analyses of U.S. Anti-Smoking Policies." Journal of Benefit-Cost Analysis. 6(1): 154-186.