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Incorporating Price-Induced Innovation in a Symmetric Generalised McFadden Cost Function with Several Outputs

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  • Ludo Peeters
  • Yves Surry
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    Abstract

    This paper proposes a multiple-output Symmetric Generalised McFadden (SGM) cost function, incorporating both exogenous and endogenous technological change. Whilst exogenous technological change is captured by the usual time trend, endogenous or price-induced technological change is cast within a partial-adjustment framework involving lagged input prices. The study points to various dimensions or components of technological change, and allows to disentangle “pure” factor substitution, given the state of the technology, from factor substitution due to price-induced changes in technology. Under the conditions of non-jointness in input quantities, the model further allows to identify technological change biases for each output separately. An empirical application is presented in which the proposed model is applied to time-series data on the feed manufacturing industry in Belgium. To improve on the econometrics, the SGM cost function also incorporates linear splines. Copyright Kluwer Academic Publishers 2000

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    Bibliographic Info

    Article provided by Springer in its journal Journal of Productivity Analysis.

    Volume (Year): 14 (2000)
    Issue (Month): 1 (July)
    Pages: 53-70

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    Handle: RePEc:kap:jproda:v:14:y:2000:i:1:p:53-70

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    Web page: http://www.springerlink.com/link.asp?id=100296

    Related research

    Keywords: Cost function; multiple outputs; non-jointness; price-induced innovation; partial adjustment; linear splines;

    References

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    1. Fulginiti, Lilyan E., 1994. "Price-Conditional Technology," Staff General Research Papers 881, Iowa State University, Department of Economics.
    2. Ulrich Kohli, 1994. "Canadian Imports and Exports by Origin and Destination: A Semi-flexible Approach," Canadian Journal of Economics, Canadian Economics Association, vol. 27(3), pages 580-603, August.
    3. Kohli, Ulrich, 1993. "A Symmetric Normalized Quadratic GNP Function and the U.S. Demand for Imports and Supply of Exports," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 34(1), pages 243-55, February.
    4. Stevenson, Rodney, 1980. "Measuring Technological Bias," American Economic Review, American Economic Association, vol. 70(1), pages 162-73, March.
    5. Diewert, W E & Wales, T J, 1992. "Quadratic Spline Models for Producer's Supply and Demand Functions," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 33(3), pages 705-22, August.
    6. Krinsky, Itzhak & Robb, A Leslie, 1986. "On Approximating the Statistical Properties of Elasticities," The Review of Economics and Statistics, MIT Press, vol. 68(4), pages 715-19, November.
    7. Diewert, Walter E & Wales, Terence J, 1987. "Flexible Functional Forms and Global Curvature Conditions," Econometrica, Econometric Society, vol. 55(1), pages 43-68, January.
    8. Kohli, Ulrich R, 1981. "Nonjointness and Factor Intensity in U.S. Production," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 22(1), pages 3-18, February.
    9. Peeters, Ludo & Surry, Yves, 1993. "Estimating feed utilisation matrices using a cost function approach," Agricultural Economics: The Journal of the International Association of Agricultural Economists, International Association of Agricultural Economists, vol. 9(2), August.
    10. Fernando S. Machado, 1995. "Testing The Induced Innovation Hypothesis Using Cointegration Analysis," Journal of Agricultural Economics, Wiley Blackwell, vol. 46(3), pages 349-360.
    11. Hayami, Yujiro & Ruttan, Vernon W., 1969. "Factor Prices And Technical Change In Agricultural Development: The United States And Japan, 1880-1960," Staff Papers 14172, University of Minnesota, Department of Applied Economics.
    12. Peeters, Ludo, 1995. "Measuring Biases of Technical Change: The Case of Cereals Displacement in Livestock Ration Formulation in Belgium," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 22(2), pages 137-56.
    13. Peeters, Ludo & Surry, Yves, 1993. "Estimating feed utilisation matrices using a cost function approach," Agricultural Economics, Blackwell, vol. 9(2), pages 109-126, August.
    14. Diewert, W. E. & Wales, T. J., 1988. "A normalized quadratic semiflexible functional form," Journal of Econometrics, Elsevier, vol. 37(3), pages 327-342, March.
    15. Lasserre, Pierre & Ouellette, Pierre, 1991. "The measurement of productivity and scarcity rents : The case of asbestos in Canada," Journal of Econometrics, Elsevier, vol. 48(3), pages 287-312, June.
    16. Rask, Kevin, 1995. "The Structure of Technology in Brazilian Sugarcane Production, 1975-87: An Application of a Modified Symmetric Generalized McFadden Cost Function," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(3), pages 221-32, July-Sept.
    17. Livernois, John R & Ryan, David L, 1989. "Testing for Non-jointness in Oil and Gas Exploration: A Variable Profit Function Approach," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 30(2), pages 479-504, May.
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    Cited by:
    1. Esposti, Roberto & Pierani, Pierpaolo, 2005. "Price-Induced Technological Change in Italian Agriculture: An SGM Restricted Cost Function Approach (1951-91)," 2005 International Congress, August 23-27, 2005, Copenhagen, Denmark 24662, European Association of Agricultural Economists.
    2. Roberto Esposti & Pierpaolo Pierani, 2008. "Price-induced technical progress in Italian agriculture," Review of Agricultural and Environmental Studies - Revue d'Etudes en Agriculture et Environnement, INRA Department of Economics, vol. 89(4), pages 5-28.
    3. Casasnovas, Valero L. & Aldanondo, Ana Maria, 2011. "Influence of Animal Feeding on Milk Supply in Navarre," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114316, European Association of Agricultural Economists.
    4. Kamel Louhichi & Florence Jacquet & Jean-Pierre Butault, 2012. "Estimating input allocation from heterogeneous data sources: a comparison of alternative estimation approaches," Working Papers 169237, Institut National de la Recherche Agronomique, France.
    5. Kenneth Stewart, 2009. "Non-jointness and scope economies in the multiproduct symmetric generalized McFadden cost function," Journal of Productivity Analysis, Springer, vol. 32(3), pages 161-171, December.
    6. Wieck, Christine & Heckelei, Thomas, 2004. "Development Of Marginal Cost Distributions In Dairy Production Regions Of The Eu," 2004 Annual meeting, August 1-4, Denver, CO 19943, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    7. Pierani, Pierpaolo & Rizzi, Pier Luigi, 2003. "Technology and efficiency in a panel of Italian dairy farms: an SGM restricted cost function approach," Agricultural Economics, Blackwell, vol. 29(2), pages 195-209, October.

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