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

Loading next page...
 
/lp/springer_journal/common-sense-and-simplicity-in-empirical-industrial-organization-LDjWPtKyS1
Publisher
Springer Journals
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.

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off