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Continuous Time Modelling Based on an Exact Discrete Time Representation

In: Continuous Time Modeling in the Behavioral and Related Sciences

Author

Listed:
  • Marcus J. Chambers

    (University of Essex, Department of Economics)

  • J. Roderick McCrorie

    (University of St. Andrews, School of Economics and Finance)

  • Michael A. Thornton

    (University of York, Department of Economics and Related Studies)

Abstract

This chapter provides a survey of methods of continuous time modelling based on an exact discrete time representation. It begins by highlighting the techniques involved with the derivation of an exact discrete time representation of an underlying continuous time model, providing specific details for a second-order linear system of stochastic differential equations. Issues of parameter identification, Granger causality, nonstationarity and mixed frequency data are addressed, all being important considerations in applications in economics and other disciplines. Although the focus is on Gaussian estimation of the exact discrete time model, alternative time domain (state space) and frequency domain approaches are also discussed. Computational issues are explored, and two new empirical applications are included along with a discussion of applications in the field of macroeconometric modelling.

Suggested Citation

  • Marcus J. Chambers & J. Roderick McCrorie & Michael A. Thornton, 2018. "Continuous Time Modelling Based on an Exact Discrete Time Representation," Springer Books, in: Kees van Montfort & Johan H. L. Oud & Manuel C. Voelkle (ed.), Continuous Time Modeling in the Behavioral and Related Sciences, chapter 0, pages 317-357, Springer.
    • Handle: RePEc:spr:sprchp:978-3-319-77219-6_14
    DOI: 10.1007/978-3-319-77219-6_14
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