Economics at your fingertips  

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

Danial Asmat
Additional contact information
Danial Asmat: Antitrust Division, U.S. Department of Justice

No 201604, EAG Discussions Papers from Department of Justice, Antitrust Division

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 multiproduct 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 multiproduct competition. The model motivates various pieces of evidence that competition authorities can compile to guide antitrust investigations in high technology markets.

JEL-codes: D43 L13 L41 L63 (search for similar items in EconPapers)
Pages: 40 pages
Date: 2016-08, Revised 2019-07
New Economics Papers: this item is included in nep-com and nep-ind
References: Add references at CitEc

Downloads: (external link) ... miconductor-industry (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Access Statistics for this paper

More papers in EAG Discussions Papers from Department of Justice, Antitrust Division Department of Justice Antitrust Division 450 Fifth Street NW Washington, DC 20530. Contact information at EDIRC.
Bibliographic data for series maintained by Tung Vu ().

Page updated 2024-07-22
Handle: RePEc:doj:eagpap:201604