Collusion Along the Learning Curve: Theory and Evidence from the Semiconductor Industry

40 Pages Posted: 24 Oct 2019

See all articles by Danial Asmat

Danial Asmat

U.S. Department of Justice, Antitrust Division

Date Written: July 31, 2019

Abstract

This paper studies the effectiveness of collusion in the DRAM cartel. Like other high technology products, DRAM is characterized by learning-by-doing and multi-product competition. I hypothesize that collusion is more difficult to sustain on a new generation, where learning is high, than an old generation, where learning is low. A higher learning rate makes defection from a collusive equilibrium more attractive by reducing future cost. Empirical analysis exploits variation between cartelization and competition to estimate the change in firms' output decisions on each generation. Consistent with the hypothesis, cartel participants are estimated to cut output more on the oldest generation than newer generations. Output decisions on the newest generation also show evidence consistent with defection from collusive equilibria. Lastly, the paper presents a theoretical framework to analyze collusive equilibria with learning-by-doing and multi-product competition. The model motivates various pieces of evidence that competition authorities can compile to guide antitrust investigations in high technology markets.

Keywords: learning by doing, cartel, price fixing, high technology

JEL Classification: D43, L13, L41, L63

Suggested Citation

Asmat, Danial, Collusion Along the Learning Curve: Theory and Evidence from the Semiconductor Industry (July 31, 2019). Available at SSRN: https://ssrn.com/abstract=3470229 or http://dx.doi.org/10.2139/ssrn.3470229

Danial Asmat (Contact Author)

U.S. Department of Justice, Antitrust Division ( email )

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Room 9418
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202-598-8762 (Phone)

HOME PAGE: http://sites.google.com/site/danialasmat/

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