Columbia University

To integrate behavioral insights into the foundations of standard macroeconomic models by re-examining the role of the Euler equation

  • Amount $490,298
  • City New York, NY
  • Investigator Emi Nakamura
  • Year 2017
  • Program Research
  • Sub-program Economic Institutions, Behavior, & Performance

How do people decide between consuming more today and saving more for the future? Mainstream macroeconomists have one answer: the Euler Equation. Simply put, it says that an optimizing agent will consume today up to the point where adding one more unit now would provide the same utility that could be expected if consuming that extra unit were deferred until tomorrow instead. In principle, the attitude expressed by the Euler Equation seems reasonable enough. Surely if you knew that having a second dessert right now, for example, would not be as enjoyable as having that dessert tomorrow, you would do well to wait. Yet as a practical matter, such calculations are difficult or impossible for individuals to make. And we all know from experience that hardly anyone ever tries. Real people rely on heuristics at best, and are sometimes not only inconsistent but also self-defeating. The Euler Equation also has theoretical implications that limit its applicability to the real world. For instance, to a population governed by the Euler Equation, the timing of consumption does not depend on when income arrives. So Euler populations will not alter their behavior in response income events like tax cuts. But clearly people in the real world do so alter their behavior. This grant funds the research of Emi Nakamura and Jon Steinsson of Columbia University to test alternatives to the Euler Equation against a uniquely comprehensive dataset of the consumer behavior of the residents of Iceland, which has Iceland has usefully kept records of nearly every financial transaction in the country. The goal is to devise a replacement for the Euler Equation and to create new macroeconomic models that are both less naпve and more useful in predicting consumer behavior in the real world.

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