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The Complexity of Production, Technological Volatility and Inter-Industry Differences in the Persistence of Profits Above the Norm

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  • Philip E. Auerswald
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    I present a model of industry dynamics resulting from competition between forward looking, heterogeneous firms that face three simultaneous challenges: learning in the process of production, competing against new entrants able to imitate best practice (albeit imperfectly), and enduring technological setbacks caused by volatility in the external environment. In the first part of the paper I propose a simple but (theoretically and empirically) well-grounded representation of the process of learning by a single plant firm that permits me to parameterize the complexity of production typical of an industry. I define the "complexity of production" as the extent to which a technical decision by one unit within the firm affects the productive efficiency of other units--that is, the magnitude of production "externalities" internal to the firm. Persistent intra-industry differences in firm profitability arise as the outcome of learning and imitation. Inter-industry differences in the persistence of above normal profits arise from production being more technologically complex in some industries than in others. In the second part of the paper I simulate industry evolution resulting from competition between forward looking firms that learn, imitate, and endure technological shocks. The framework is an extension of the Ericson and Pakes (1995) model of Markov-perfect industry dynamics; the implementation builds directly upon Pakes and McGuire (1995). I show that industry dynamics depend crucially on both complexity of production and on technological volatility.

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    Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 2001 with number 229.

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    Date of creation: 01 Apr 2001
    Handle: RePEc:sce:scecf1:229
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