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

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  • Danial Asmat

Abstract

I study the effectiveness of collusion during an international cartel in DRAM, a type of semiconductor characterized by learning‐by‐doing and multiproduct competition. First, by exploiting time and firm‐level variation in cartel activity, I estimate that cartel participants cut output more on the oldest product generation than on newer generations. This is consistent with a hypothesis that higher learning rates in newer generations make defection from collusive equilibria more attractive. Second, I formulate a test for defection from collusive equilibria in learning‐by‐doing industries. Third, I formalize these results in a theoretical framework and discuss implications for antitrust policy in high technology markets.

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  • Danial Asmat, 2021. "Collusion Along the Learning Curve: Theory and Evidence From the Semiconductor Industry," Journal of Industrial Economics, Wiley Blackwell, vol. 69(1), pages 83-108, March.
    • Handle: RePEc:bla:jindec:v:69:y:2021:i:1:p:83-108
    DOI: 10.1111/joie.12235
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    Cited by:

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    2. Vasvári, Tamás & Hauck, Zsuzsanna & Longauer, Dóra, 2024. "Kiszervezési stratégiák és tanulási hatás a félvezetőiparban [Outsourcing strategies and the learning effect in the semiconductor industry]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(2), pages 176-200.

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