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Firm's R & D Behavior Under Rational Expectations

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  • Lakshmi K Raut

Abstract

This paper formulates dynamic R&D investment decisions of private firms as an optimal stochastic control problem. It derives explicitly R&D investment decision rule and the cross equations parameter restrictions imposed by the rational expectations hypothesis, using the Riccati equations only and not requiring the use of Wiener-Kolmogorov prediction formula. Idenfitication and estimation of the structural parameters are essential for evaluating policies such as R&D subsidies, firm size, market concentration so that the evaluations of these policies stand against Lucas critique. We find conditions under which the structural parameters are identified; we then discuss econometric procedures for using aggregate time series data or panel data on firms to deal with unobserved technological knowledge, to estimate the structural parameters, and to test the model.

Suggested Citation

  • Lakshmi K Raut, 1997. "Firm's R & D Behavior Under Rational Expectations," Working Papers 199705, University of Hawaii at Manoa, Department of Economics.
  • Handle: RePEc:hai:wpaper:199705
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    References listed on IDEAS

    as
    1. Zvi Griliches, 1984. "R&D, Patents, and Productivity," NBER Books, National Bureau of Economic Research, Inc, number gril84-1.
    2. Hansen, Lars Peter & Sargent, Thomas J., 1980. "Formulating and estimating dynamic linear rational expectations models," Journal of Economic Dynamics and Control, Elsevier, vol. 2(1), pages 7-46, May.
    3. Rosenberg, Joel B, 1976. "Research and Market Share: A Reappraisal of the Schumpeter Hypothesis," Journal of Industrial Economics, Wiley Blackwell, vol. 25(2), pages 101-112, December.
    4. Jacques Mairesse & Mohamed Sassenou, 1991. "R&D Productivity: A Survey of Econometric Studies at the Firm Level," NBER Working Papers 3666, National Bureau of Economic Research, Inc.
    5. Nelson, Richard R & Winter, Sidney G, 1977. "Simulation of Schumpeterian Competition," American Economic Review, American Economic Association, vol. 67(1), pages 271-276, February.
    6. Ariel Pakes, 1984. "Patents, R&D, and the Stock Market Rate of Return: A Summary of Some Empirical Results," NBER Chapters, in: R&D, Patents, and Productivity, pages 253-260, National Bureau of Economic Research, Inc.
    7. Richard R. Nelson, 1959. "The Simple Economics of Basic Scientific Research," Journal of Political Economy, University of Chicago Press, vol. 67(3), pages 297-297.
    8. Raut, Lakshmi K., 1995. "R & D spillover and productivity growth: Evidence from Indian private firms," Journal of Development Economics, Elsevier, vol. 48(1), pages 1-23, October.
    9. Ariel Pakes & Zvi Griliches, 1980. "Patents and R and D at the Firm Level: A First Look," NBER Working Papers 0561, National Bureau of Economic Research, Inc.
    10. Richard Levin & Peter C. Reiss, 1984. "Tests of a Schumpeterian Model of R&D and Market Structure," NBER Chapters, in: R&D, Patents, and Productivity, pages 175-208, National Bureau of Economic Research, Inc.
    11. Ariel Pakes & Zvi Griliches, 1984. "Patents and R&D at the Firm Level: A First Look," NBER Chapters, in: R&D, Patents, and Productivity, pages 55-72, National Bureau of Economic Research, Inc.
    12. Lucas, Robert Jr, 1976. "Econometric policy evaluation: A critique," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 1(1), pages 19-46, January.
    13. L. K. Raut, 1988. "R & D Behaviour of Indian Firms: A Stochastic Control Model," Indian Economic Review, Department of Economics, Delhi School of Economics, vol. 23(2), pages 207-229, July.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    research and development; rational expectations; stochastic control;
    All these keywords.

    JEL classification:

    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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