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Testing Dynamic Oligopolistic Interaction: Evidence from the Semiconductor Industry

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Author Info
Christine Zulehner

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Abstract

This paper analyzes the impact of a dynamic specification on the estimation of the conduct parameter in an oligopolistic market. Various empirical studies have shown that in the semiconductor industry, in particular in the Dynamic Random Access Memory (DRAM) market, one has to account for dynamic elements as learning-by-doing within firms and learning spillovers among them. Therefore this market seems to be appropriate to investigate whether firms behave strategically in a dynamic sense and how open-loop or closed-loop as equilibrium concepts alter the size of the estimated parameters. I apply a structural oligopolistic model of dynamic nonprice competition that incorporates learning-by-doing and spillovers. Theory shows that learning-by-doing and learning spillovers have important consequences for firm behavior. Whether firms in the DRAM industry take the strategic effects of learning-by-doing and learning spillovers actually into account when choosing their output strategies, is answered with empirical evidence. Using quarterly data from 1974-1996 at the firm level, I estimate demand and pricing relations for three different generations of DRAM chips. The empirical results show that the game theoretic specification has an important impact and that firms behave strategically. The assumption of an open-loop specification would underestimate the conduct parameter on average about 50%.

ZUSAMMENFASSUNG - (Testen dynamischer oligopolistischer Interaktion: Empirische Evidenz aus der Halbleiterindustrie)
In diesem Arbeitspapier wird der Einfluß einer dynamischen Spezifikation auf die Schätzung des Verhaltensparameters in einem oligopolistischen Marktes untersucht. Verschiedene empirische Studien haben gezeigt, daß die Halbleiterindustrie, im speziellen der Dynamic Random Access Memory (DRAM) Markt, von dynamischen Elementen wie Learning-by-doing in Unternehmen und Learning spillovers zwischen Unternehmen geprägt ist. Das wirft die Frage auf, ob sich Unternehmen in einem dynamischen Sinne strategisch verhalten und wie open-loop beziehungsweise closed-loop als Gleichgewichtskonzepte die Größe der geschätzten Parameter verändern. In diesem Papier wird ein strukturelles oligopolistisches Modell in einem dynamischen Kontext betrachtet, indem Unternehmen Mengen setzten und Learning-by-doing und Learning spillovers relevant sind. Die Theorie zeigt, daß Learning-by-doing und Learning spillovers wichtige Konsequenzen für das Verhalten von Unternehmen haben. Ob die Unternehmen in der DRAM Industrie tatsächlich die strategischen Effekte aus Learning-by-doing und Learning spillovers in Betracht ziehen, wird auf empirische Weise versucht zu beantworten. Unter der Verwendung vierteljährlicher firmenspezifischer Daten der Jahre 1974-1996 werden die Nachfrage- und die Angebotsgleichung für drei Generationen von DRAMs geschätzt. Die Schätzergebnisse zeigen, daß die spieltheoretische Spezifikation einen wichtigen Einfluß hat und daß sich Unternehmen strategisch in einem dynamischen Sinne verhalten. So unterschätzt die Annahme einer open-loop Gleichgewichtslösung den Verhaltensparameter im Durchschnitt um 50% unterschätzen.

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Publisher Info
Paper provided by Wissenschaftszentrum Berlin (WZB), Research Unit: Competition and Innovation (CIG) in its series CIG Working Papers with number FS IV 99-17.

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Length: 42 pages
Date of creation: Sep 1999
Date of revision:
Publication status: Published in the International Journal of Industrial Organization, Vol. 21(10), December 2003, pp. 1527-1556.
Handle: RePEc:wzb:wzebiv:fsiv99-17

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Related research
Keywords: Oligopoly; dynamic games; semiconductor industry;

Other versions of this item:

Find related papers by JEL classification:
L13 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Oligopoly and Other Imperfect Markets
L63 - Industrial Organization - - Industry Studies: Manufacturing - - - Microelectronics; Computers; Communications Equipment
C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games

Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. L. Lambertini & A. Mantovani, 2004. "Identifying Reaction Functions in Differential Oligopoly Games," Working Papers 518, Dipartimento Scienze Economiche, Universita' di Bologna. [Downloadable!]
    Other versions:
  2. Andrew Clarke, 2008. "Learning-by-Doing and Productivity Dynamics in Manufacturing Industries," Department of Economics - Working Papers Series 1032, The University of Melbourne. [Downloadable!]
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