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«Abstract From bidding data, we estimate the underlying value distribution for Forest Service timber. We nd that bidder values decrease $2=mbf ...»

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Because non-cooperative game theory has replaced the structure-performance paradigm as the dominant framework shaping competition policy, it seems appropriate to abandon the old structural metrics in favor of computational ones as a framework for evaluating competition policy Froeb and Werden 15 ; Crooke, Froeb, Tschantz, and Werden 10 . Economists at the Federal Trade Commission and U.S. Department of Justice have already begun to do this in merger cases involving di erentiated-products mergers Werden 31 . The computational approach may be extended to auction markets to address antitrust concerns, like those of Baker 3 who is worried that hospital mergers will reduce competition for Health Maintenance Organization contracts. Computational tools like the ones developed in this paper could replace structural merger analysis in second-price auction markets. Other tools could be used in rst-price auction markets Bajari 2 ; Dalkir, Logan, Masson 11 ; Tschantz, Crooke and Froeb 27 . Perhaps the biggest bene t of such a change would be an expanded role for e ciencies which have no explicit role under a structural standard Werden and Froeb 33 . Even if good data are unavailable, rules-of-thumb implied by the merger model in 5.2 and a compensating marginal-cost reduction could be used to evaluate the e ciency claims of merging parties. Although we would urge the agencies to adopt a total-welfare standard, an explicit consumer-welfare standard is a step in the right direction, and we would second Jerry Hausman's call for merger safe harbors" de ned in terms of computed post merger prices Passell 25 .

The computational tools presented in the paper could also be used in price- xing cases to compute damages or as a tool to guide enforcement resource-allocation decisions. For example, one of the surprising results of the paper is the small size of the computed price e ects of mergers that include the two most favorably-situated bidders. To get signi cant price e ects, like the 23 percent e ect estimated by Froeb, Koyak, and Werden 13, bidding coalitions would have to include nearly all auction participants.

This is similar to the nding in Bresnahan and Reiss 8 that the bene ts of additional competition are exhausted after only a few rms.

Finally, the computational approach is well suited to analyzing the e ects of bidding preferences. We nd it surprising that bidding preferences could have such large e ects in spectrum auctions Ayres and Cramton 1 , but such small e ects in timber auctions. More work to reconcile or understand these contradictory results would help guide policy.

References 1 Ayres, Ian, and Peter Cramton De cit Reduction Through Diversity:

How A rmative Action at the FCC Increased Auction Competition," Stanford Law Review 48 1981, 761-815.

2 Bajari, Patrick, A Structural Econometric Model of the First Price Sealed Bid Auction: With Applications to Procurement of Highway Improvements," manuscript, University of Minnesota, 1996.

3 Baker, Jonathan B., Unilateral Competitive E ects Theories in Merger Analysis," Antitrust 112 Spring 1987, 21-26.

4 Baldwin, Laura H., Robert Marshall, and Jean-Francois Richard, Bidder Collusion at Forest Service Timber Sales," Journal of Political Economy 1054 August 1997, 657-99.

5 Ben-Akiva, Moshe and Steven Lerman, Discrete Choice Analysis:

Theory and Application to Travel Demand Cambridge, Massachusetts: MIT Press, 1985.

6 Brannman, Lance, Hauling Distances in Forest Service Timber Sales:

Economic E ciency in Oral and Sealed Bidding," Journal of Forestry Research February 1991, 1830.

7 Brannman, Lance, Potential Competition and Possible Collusion in Forest Service Timber Auctions," Economic Inquiry 34 1996, 730Bresnahan, Timothy, and Peter Reiss, Entry and Competition in Concentrated Markets," Journal of Political Economy 99 1991, 977-1009.

9 Crooke, Philip, Luke Froeb, Steven Tschantz, Maximum Likelihood Estimation with Mathematica, Mathematica in Education and Research forthcoming.

10 Crooke, Philip, Luke Froeb, Steven Tschantz, and Gregory Werden, E ects of Assumed Demand Form on Simulated Post-Merger Equilibria," Review of Industrial Organization forthcoming.

11 Dalkir, Serdar, John Logan, and Robert Masson, Mergers in Noncooperative Auction Markets: The E ects of Mergers on Prices and E ciency," International Journal of Industrial Organization forthcoming.

12 David, Herbert A., Order Statistics, Second Edition New York: Wiley, 1981.

13 Froeb, Luke, and Robert Koyak, and Gregory J. Werden, What is the E ect of Bid Rigging on Price?," Economics Letters 42 1993, 419-423.

14 Froeb, Luke, and R. Preston McAfee, Deterring Bid Rigging in Forest Service Timber Auctions," U.S. Department of Justice Working Paper, 88-5, 1988.

15 Froeb, Luke and Gregory J. Werden, Simulating the E ects of Mergers among Noncooperative Oligopolists," in Hal Varian, ed., Computational Economics and Finance: Modeling and Analysis with Mathematica New York: Springer-Verlag Telos, 1996.

16 Froeb, Luke, Steven Tschantz, and Philip Crooke, Mergers Among Asymmetric Bidders: A Logit Second-Price Auction Model," working paper, Owen Graduate School of Management Vanderbilt University, working paper, 1997.

17 Hansen, Robert G., Sealed-Bid Versus Open Auctions: The Evidence," Economic Inquiry 24 1986, 125-142.

18 Hausman, Jerry, and D. McFadden, Speci cation Tests for the Multinomial Logit Model," Econometrica 52 April-June 1984, 1219-40.

19 Johnson, Ronald, Competitive Bidding for Federally Owned Timber," Ph.D. Dissertation, University of Washington, 1977.

20 Johnson, Ronald, Oral Auction versus Sealed Bids: An Empirical Investigation," Natural Resources Journal April 1979, 315-35.

21 McAfee, R. Preston and John McMillan, Incentives in Government Contracting: Report the Ontario Economic Council," April, 1985.

22 Mead, Walter J. Competition and Oligopsony in the Douglas- r Lumber Industry," Los Angeles: University of California Bureau of Business and Economic Research, 1966.

23 Paarsch, Harry J., Deciding between the common and private value paradigms in empirical models of auctions," Journal of Econometrics 51 1992, 191-215.

24 Paarsch, Harry J., Deriving an estimate of the optimal reserve price:

An application to British Columbian timber sales," Journal of Econometrics 78 1997, 169-193.

25 Passell, Peter, Economic Scene: FTC Looks at E ect of Mergers on Consumers," New York Times March 20, 1997, Business Section, page 1.

26 Schniepp, M., The Economic Consequences of the Set-Aside Program

in the Douglas-Fir Regions of the Paci c Northwest," in Forestlands:

Public and Private, eds. R. Deacon and M.B. Johnson, Cambridge, Massachusetts: Ballinger, 1984.

27 Tschantz, Steven, Philip Crooke, and Luke Froeb, Mergers in Sealed vs. Oral Asymmetric Auctions," working paper Owen Graduate School of Management Vanderbilt University, 1997.

28 Train, Kenneth, Qualitative Choice Analysis Cambridge, Massachusetts: The MIT Press, 1986.

29 U.S. Department of Justice and Federal Trade Commission, Horizontal Merger Guidelines, 4 Trade Reg. Rep. CCH P13104.

30 Vickrey, W, Counterspeculation, Auctions, and Competitive Sealed Tenders," Journal of Finance 16 1961, 8-37.

31 Werden, Gregory J., Simulating the E ects of Mergers in Di erentiated Products Industries," Antitrust 112 Spring 1997, 27-31.

32 Werden, Gregory J., and Froeb, Luke M., The E ects of Mergers in Di erentiated Products Industries: Logit Demand and Merger Policy," Journal of Law, Economics, and Organization 10 Oct. 1994, 407-26.

33 Werden, Gregory J., and Froeb, Luke M., Simulation as an alternative to Structural Merger Policy in Di erentiated Products Industries," in Malcolm Coate and Andrew Kleit, eds., The Economics of the Antitrust Process New York: Kluwer, 1996.

34 Willig, Robert, Merger Analysis, Industrial Organization Theory, and Merger Guidelines," Brookings Papers on Economic Activity, Microeconomics 1992, 281-332.

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