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Behavioral and Experimental Economics 18

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I magine you run the Centers for Disease Control and Prevention (CDC) located in Atlanta, Georgia. Your job is to keep America safe. Suddenly, an unusual disease breaks out in Florida. Your best scientists estimate that 600 Americans were exposed to the disease and will die if no government action is taken. You are given a choice between two programs to address this crisis.

Did you choose Response A for Program 1 and Response C for Program 2? You should have, because both responses are the same; they are only described differently. In either case, 200 people live and 400 people die with certainty. Similarly, Responses B and D are the same, but worded differently. With each response, there is a one-third chance to save everyone and a two-thirds chance to save no one.

In a famous study, economic researchers asked people what response they would pick.1 With Program 1, 72% of the people chose Response A: Better to save 200 lives for certain with this option than gamble on saving more lives and risk saving no one with Response B. But when offered Program 2, 78% of the same people picked Response D. Their reasoning? How can you pick a response (C) in which 400 people die for sure when you can take a chance to save everyone? Remember that Responses A and C are the same: Response A saves 200 lives for certain (and thus 400 people die for certain), and in Response C, 400 people die for certain (and 200 people live for certain). By manipulating how these alternatives were framed, Amos Tversky and Daniel Kahneman (now a Nobel laureate) were able to alter the choices dramatically.

This outcome should not happen in a standard economic model. When we have thought about utility functions, costs, risks, and the like in the previous 17 chapters, decision making was never affected by how the choices were described. You prefer one bundle of goods to a second bundle or you don’t. Likewise, the cost of a particular level of output is calculated in the same manner for all levels. An economic model cannot explain why framing the problem in terms of lives saved versus lives lost should matter. Nor can it easily explain why companies price things in 99-cent increments or why a consumer buys only one Nike shirt priced at $25, but buys three of them if the shirt is marked down by 50% from $50. In building economic models, economists always assume that the economic actors behave rationally and would therefore realize that in the disease example 200 lives are saved with Responses A and C, and that in both cases the price of the Nike shirt is $25.

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In recent years, economists have increasingly come to accept that, as great a job as standard economic models do in explaining the ways of the world, they sometimes fail badly when human psychology plays a role in people’s decision making.

The nature of these models’ failures matters. If people and firms sometimes make mistakes and act differently from the perfectly rational, self-interested agents that underlie the analysis in our previous chapters and if those mistakes are random (i.e., they do not occur with any predictable pattern), then the standard economic models may be fine. But if the mistakes are systematic, that is, if people repeatedly act differently from the model in predictable ways, then the flaws are much more serious. It is claims of systematic departure from rational economic decision making that motivate the rising prominence of behavioral economics, the branch of economics that incorporates insights from human psychology into models of economic behavior.

Like the field of behavioral economics itself, this chapter is a bit different from the conventional microeconomics we’ve presented thus far. Instead of laying out specific models and showing you how to solve and apply them, this chapter examines some of the ways that economists and psychologists have expanded traditional economic models in an effort to better explain real-world behaviors. The first half of the chapter presents an overview of some of the common psychological biases and mistakes people make that have emerged from behavioral economics research and why these biases and mistakes pose a problem for traditional models. In addition, we learn how fully rational, self-interested market participants can take advantage of such biases in a well-functioning market. These biases include the susceptibility to framing (the bias we saw in our disease example), overconfidence, being overly oriented to the present, an inability to ignore sunk costs, and other economic taboos.

In the second half of the chapter, we discuss the new ways economists have begun to test these behavioral economic models using actual experiments rather than traditional statistical methods like econometrics. We conclude the chapter and the book with a discussion of what behavioral economics means for the future of microeconomics.