Collusion Over the Business Cycle

RAND JOURNAL OF ECONOMICS, Vol. 28, No. 1

Posted: 24 Mar 1997

See all articles by Kyle Bagwell

Kyle Bagwell

Stanford University - Department of Economics; National Bureau of Economic Research (NBER)

Robert W. Staiger

Stanford University; University of Wisconsin - Madison - Department of Economics; National Bureau of Economic Research (NBER)

Multiple version iconThere are 2 versions of this paper

Abstract

We present a theory of collusive pricing for markets in which demand alternates stochastically between fast-growth (boom) and slow-growth (recession) phases. We show that 1) the most collusive prices are weakly procyclical (countercyclical) when demand growth rates are positively (negatively) correlated through time; and 2) the amplitude of the collusive pricing cycle is larger when the expected duration of boom phases decreases and when the expected duration of recession phases increases. We also offer a generalization of Rotemberg and Saloner's (1986) model, interpreting their findings in terms of transitory demand shocks that occur within broader business cycle phases.

JEL Classification: E31, E32

Suggested Citation

Bagwell, Kyle and Staiger, Robert W., Collusion Over the Business Cycle. RAND JOURNAL OF ECONOMICS, Vol. 28, No. 1, Available at SSRN: https://ssrn.com/abstract=3824

Kyle Bagwell (Contact Author)

Stanford University - Department of Economics ( email )

Landau Economics Building
579 Serra Mall
Stanford, CA 94305-6072
United States

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Robert W. Staiger

Stanford University ( email )

Stanford, CA 94305
United States

University of Wisconsin - Madison - Department of Economics ( email )

1180 Observatory Drive
Madison, WI 53706
United States
608-262-2265 (Phone)

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Abstract Views
664
PlumX Metrics