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Stochastic Technical Change and Procyclical TFP The Italian Agriculture Case

Author

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  • Roberto ESPOSTI

    (Universit… Politecnica delle Marche, Dipartimento di Economia)

Abstract

TFP comparisons across nations, sectors and time have been frequently used to represent the relative technological levels of the production systems. In this paper the use of the TFP as a proxy of the technological level in Italian agriculture is questioned. The cyclical behaviour seems to be the most important shortcoming of the TFP measure. It clearly reveals a short-run component due to shocks on the supply side. To separate these business cycle effects from real long-run technological change, we use a stochastic process for the generation of technical change induced by R&D and Extension expenditure and a Kalman filter procedure is applied. Doing this, it is possible to separate the short-run and long-run components of the traditional TFP measure. The empirical evidence clearly reveals that supply-side shocks enter the traditional measure of productivity therefore, it represents an erroneous indicator of technological progress. A better indicator can be obtained estimating the longrun component of productivity that seems to be close to a linear trend and significantly induced by R&D and Extension public expenditure.

Suggested Citation

  • Roberto ESPOSTI, 1998. "Stochastic Technical Change and Procyclical TFP The Italian Agriculture Case," Working Papers 108, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    • Handle: RePEc:anc:wpaper:108
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    File URL: http://docs.dises.univpm.it/web/quaderni/pdf/108.pdf
    File Function: First version, 1998
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    Citations

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    Cited by:

    1. Roberto ESPOSTI & Pierpaolo PIERANI, 2001. "Building the Knowledge Stock: Lags, Depreciation and Uncertainty in Agricultural R&D," Working Papers 145, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    2. Esposti, Roberto, 2008. "Why Should Regional Agricultural Productivity Growth Converge? Evidence from Italian Regions," 2008 International Congress, August 26-29, 2008, Ghent, Belgium 43955, European Association of Agricultural Economists.
    3. Matthew Andersen & Julian Alston & Philip Pardey, 2012. "Capital use intensity and productivity biases," Journal of Productivity Analysis, Springer, vol. 37(1), pages 59-71, February.

    More about this item

    Keywords

    Cost Function; Italian Agriculture; Latent Variable; Stochastic Technical Change;
    All these keywords.

    JEL classification:

    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General
    • Q16 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - R&D; Agricultural Technology; Biofuels; Agricultural Extension Services

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