Andrew W. Lo
Massachusetts Institute of Technology (MIT) - Sloan School of Management; Massachusetts Institute of Technology (MIT) - Computer Science and Artificial Intelligence Laboratory (CSAIL); National Bureau of Economic Research (NBER)

Abstract

This is a pre-conference essay prepared for 'What Post-Crisis Changes Does the Economics Discipline Need?', a conference organized by Diane Coyle and Enlightenment Economics, the Bank of England, and the U.K. Government Economic Service on 7 February 2012. In this essay, I trace the origins of 'theory envy' to Paul Samuelson and the mathematization of economics over the past half century, and consider its implications for how economics should be taught. Although this research program has produced many genuine breakthroughs in economics, any virtue can become a vice when taken to an extreme, and the recent financial crisis has given us an opportunity to reinvent our field. One innovation is to teach economics not from an axiomatic and technique-oriented perspective, but by posing challenges that can only be addressed through economic logic. Instead of starting microeconomics with the consumer’s problem of maximizing utility subject to a budget constraint, begin by challenging students to predict the impact of a gasoline tax on the price of gasoline, or asking them to explain why diamonds are so much more expensive than water, despite the fact that the latter is critical for survival unlike the former. Instead of starting macroeconomics with national income accounts, begin with the question of how to measure and manage the wealth of nations, or why inflation can be so disruptive to economic growth. Without the proper institutional, political, and historical context in which to interpret economic models, constrained optimization methods and fixed-point existence proofs have much less meaning and are more likely to give rise to theory envy. However, when students understand the “why” of their course of study, even the most complex mathematical tools can be mastered and are almost always applied more meaningfully.