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The Learning Curve and Pricing in the Chemical Processing Industries

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  • Marvin B. Lieberman
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    Abstract

    Data on 37 chemical products are used to test a number of hypotheses about the learning curve and industrial price behavior. The results document a strong and consistent learning effect. Learning is found to be a function of cumulated industry output and cumulated investment rather than calendar time. Standard economies of scale appear significant but small in magnitude relative to the learning effect. Variations in the slope of the learning curve are linked to differences in R&D expenditures and capital intensity. Market concentration is found to be a strong influence on price flexibility and the timing of learning-related price changes.

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    Bibliographic Info

    Article provided by The RAND Corporation in its journal RAND Journal of Economics.

    Volume (Year): 15 (1984)
    Issue (Month): 2 (Summer)
    Pages: 213-228

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    Handle: RePEc:rje:randje:v:15:y:1984:i:summer:p:213-228

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    Cited by:
    1. Blazek, David & Sickles, Robin C., 2010. "The impact of knowledge accumulation and geographical spillovers on productivity and efficiency: The case of U. S. shipbuilding during WWII," Economic Modelling, Elsevier, vol. 27(6), pages 1484-1497, November.
    2. Alwyn Young, 1991. "Invention and Bounded Learning by Doing," NBER Working Papers 3712, National Bureau of Economic Research, Inc.
    3. Lee Branstetter, 1996. "Are Knowledge Spillovers International or Intranational in Scope? Microeconometric Evidence from the Japan and the United States," NBER Working Papers 5800, National Bureau of Economic Research, Inc.
    4. Tracy R. Lewis & Huseyin Yildirim, 2002. "Managing Dynamic Competition," American Economic Review, American Economic Association, vol. 92(4), pages 779-797, September.
    5. Majd, Saman. & Pindyck, Robert S., 1987. "The learning curve and optimal production under uncertainty," Working papers 1948-87., Massachusetts Institute of Technology (MIT), Sloan School of Management.
    6. Harashima, Taiji, 2009. "A Theory of Total Factor Productivity and the Convergence Hypothesis: Workers’ Innovations as an Essential Element," MPRA Paper 15508, University Library of Munich, Germany.
    7. Méjean, A. & Hope, C., 2010. "Supplying Synthetic Crude Oil from Canadian Oil Sands: A Comparative Study of the Costs and CO2 Emissions of Mining and In-Situ Recovery," Cambridge Working Papers in Economics 1014, Faculty of Economics, University of Cambridge.
    8. Festel, Gunter & Würmseher, Martin & Rammer, Christian & Boles, Eckhard & Bellof, Martin, 2013. "Modelling production cost scenarios for biofuels and fossil fuels in Europe," ZEW Discussion Papers 13-075, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.
    9. Harashima, Taiji, 2011. "A Model of Total Factor Productivity Built on Hayek’s View of Knowledge: What Really Went Wrong with Socialist Planned Economies?," MPRA Paper 29107, University Library of Munich, Germany.
    10. Harashima, Taiji, 2012. "A Theory of Intelligence and Total Factor Productivity: Value Added Reflects the Fruits of Fluid Intelligence," MPRA Paper 43151, University Library of Munich, Germany.
    11. Oliver Falck & Simon Wiederhold, 2013. "Nachfrageorientierte Innovationspolitik: Bestandsaufnahme und ökonomische Bewertung," ifo Beiträge zur Wirtschaftsforschung, Ifo Institute for Economic Research at the University of Munich, number 51.
    12. Mulotte, L., 2013. "Do experience effects vary across governance modes? Evidence from new product introduction in the global aerospace industry, 1948–2000 (Online first)," Open Access publications from Tilburg University urn:nbn:nl:ui:12-5905829, Tilburg University.

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