When is the Standard Analysis of Common Property Extraction Under Free Access Correct? A Game-Theoretic Justification for Non-Game-Theoretic Analyses

Posted: 25 Aug 1999

See all articles by Robin Brooks

Robin Brooks

International Monetary Fund (IMF) - Financial Studies Division

Michael P. Murray

Bates College

Stephen W. Salant

University of Michigan; Resources for the Future

Jill C. Weise

Ernst & Young LLP

Abstract

Analyses of common property extraction under free access follow two distinct paths, traditional and game-theoretic, giving rise to two standard methodologies. One methodology avoids game-theoretic analysis by assuming that aggregate extraction in each period induces full rent dissipation. The second methodology solves for the Markov-perfect equilibrium of an n-player extraction game investigating aggregate behavior over time as n approaches infinity. We show by example that these coexisting "standard" methodologies can yield conflicting predictions. We then provide conditions, relatively easy to satisfy, sufficient for the two approaches to yield the same predictions.

JEL Classification: C79

Suggested Citation

Brooks, Robin and Murray, Michael P. and Salant, Stephen W. and Weise, Jill C., When is the Standard Analysis of Common Property Extraction Under Free Access Correct? A Game-Theoretic Justification for Non-Game-Theoretic Analyses. Available at SSRN: https://ssrn.com/abstract=169390

Robin Brooks

International Monetary Fund (IMF) - Financial Studies Division ( email )

700 19th Street N.W.
Washington, DC 20431
United States

Michael P. Murray

Bates College ( email )

Lewiston, ME 04240
United States
207-786-6085 (Phone)

Stephen W. Salant (Contact Author)

University of Michigan ( email )

611 Tappan Street
Ann Arbor, MI 48109-1220
United States
313-764-2370 (Phone)
313-764-2769 (Fax)

Resources for the Future ( email )

1616 P Street, NW
Washington, DC 20036
United States

Jill C. Weise

Ernst & Young LLP

1225 Connecticut Ave NW # 700
Washington, DC 20036
United States

Do you have negative results from your research you’d like to share?

Paper statistics

Abstract Views
729
PlumX Metrics