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Estimation Of Differential-Difference Equation Systems With Unknown Lag Parameters

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  • Ercolani, Joanne S.
  • Chambers, Marcus J.

Abstract

This paper considers the estimation of the parameters of general systems of stochastic differential-difference equations in which the lag parameters themselves are treated as unknown and are not restricted to be integers and therefore form part of the parameter vector to be estimated. The asymptotic properties of an infeasible frequency domain maximum likelihood estimator are established in addition to those of a feasible version based on truncating an infinite series that arises in the computation of the spectral density function of the observed discrete time series. Precise conditions that the truncation parameter must satisfy for the asymptotic results to hold are provided.We are grateful to Gordon Kemp, Andrew Harvey, the Editor, and two anonymous referees for helpful comments on an earlier version of this paper. Any remaining errors are the sole responsibility of the authors. The first author thanks the Economic and Social Research Council for financial support under grant number R00429434216, and the second author thanks the Leverhulme Trust for financial support in the form of a Philip Leverhulme Prize.

Suggested Citation

  • Ercolani, Joanne S. & Chambers, Marcus J., 2006. "Estimation Of Differential-Difference Equation Systems With Unknown Lag Parameters," Econometric Theory, Cambridge University Press, vol. 22(3), pages 483-498, June.
    • Handle: RePEc:cup:etheor:v:22:y:2006:i:03:p:483-498_06
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    Cited by:

    1. Joanne S. Ercolani, 2010. "On the Asymptotic Properties of a Feasible Estimator of the Continuous Time Long Memory Parameter," Discussion Papers 10-09, Department of Economics, University of Birmingham.
    2. Joanne S. Ercolani, 2007. "Cyclical Trends in Continuous Time Models," Discussion Papers 07-13, Department of Economics, University of Birmingham.
    3. Joanne S. Ercolani, 2014. "Cyclical Activity and Gestation Lags in Investment," Manchester School, University of Manchester, vol. 82(5), pages 620-630, September.

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