Common Sense and Simplicity in Empirical Industrial Organization

Common Sense and Simplicity in Empirical Industrial Organization This paper is a revised version of a keynote address delivered at the inauguralInternational Industrial Organization Conference in Boston, April 2003. I arguethat new econometric tools have facilitated the estimation of models with realistictheoretical underpinnings, and because of this, have made empirical I.O. muchmore useful. The tools solve computational problems thereby allowing us to makethe relationship between the economic model and the estimating equations transparent.This, in turn, enables us to utilize the available data more effectively. It also facilitatesrobustness analysis and clarifies the assumptions needed to analyze the causes of pastevents and/or make predictions of the likely impacts of future policy or environmentalchanges. The paper provides examples illustrating the value of simulation for theestimation of demand systems and of semiparametrics for the estimation of entry models. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Review of Industrial Organization Springer Journals

Common Sense and Simplicity in Empirical Industrial Organization

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Publisher
Kluwer Academic Publishers
Copyright
Copyright © 2003 by Kluwer Academic Publishers
Subject
Economics; Industrial Organization; Microeconomics
ISSN
0889-938X
eISSN
1573-7160
D.O.I.
10.1023/B:REIO.0000031365.05276.c1
Publisher site
See Article on Publisher Site

Abstract

This paper is a revised version of a keynote address delivered at the inauguralInternational Industrial Organization Conference in Boston, April 2003. I arguethat new econometric tools have facilitated the estimation of models with realistictheoretical underpinnings, and because of this, have made empirical I.O. muchmore useful. The tools solve computational problems thereby allowing us to makethe relationship between the economic model and the estimating equations transparent.This, in turn, enables us to utilize the available data more effectively. It also facilitatesrobustness analysis and clarifies the assumptions needed to analyze the causes of pastevents and/or make predictions of the likely impacts of future policy or environmentalchanges. The paper provides examples illustrating the value of simulation for theestimation of demand systems and of semiparametrics for the estimation of entry models.

Journal

Review of Industrial OrganizationSpringer Journals

Published: Oct 4, 2004

References

  • Incomplete Simultaneous Discrete Response Model with Multiple Equilibria
    Tamer, E.

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