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Refinement of the partial adjustment model using continuous-time econometrics

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  • Arie ten Cate

Abstract

This paper presents some suggestions for the specification of dynamic models. These suggestions are based on the supposed continuous-time nature of most economic processes. In particular, the partial adjustment model -or Koyck lag model- is discussed. The refinement of this model is derived from the continuous-time econometric literature. We find three alternative formulas for this refinement, depending on the particular econometric literature which is used. Two of these formulas agree with an intuitive example. In passing, it is shown that that the continuous-time models of Sims and Bergstrom are closely related. Also the inverse of Bergstrom's approximate analog has been introduced, making use of engineering mathematics. Followed by Error-correction modelling in discrete and continuous time, Economics Letters 101 (2008), pp.140-141 [with Philip Hans Franses]

Suggested Citation

  • Arie ten Cate, 2004. "Refinement of the partial adjustment model using continuous-time econometrics," CPB Discussion Paper 41, CPB Netherlands Bureau for Economic Policy Analysis.
    • Handle: RePEc:cpb:discus:41
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    References listed on IDEAS

    as
    1. ten Cate, Arie, 1993. "The current period coefficient of polynomial lag distributions," Economic Modelling, Elsevier, vol. 10(4), pages 408-416, October.
    2. McCrorie, J. Roderick & Chambers, Marcus J., 2006. "Granger causality and the sampling of economic processes," Journal of Econometrics, Elsevier, vol. 132(2), pages 311-336, June.
    3. Arie ten Cate, 2002. "Continuous-time modelling in econometrics and engineering - juli 2002," CPB Memorandum 42, CPB Netherlands Bureau for Economic Policy Analysis.
    4. Sims, Christopher A, 1971. "Discrete Approximations to Continuous Time Distributed Lags in Econometrics," Econometrica, Econometric Society, vol. 39(3), pages 545-563, May.
    5. Bergstrom, A. R., 1988. "The History of Continuous-Time Econometric Models," Econometric Theory, Cambridge University Press, vol. 4(3), pages 365-383, December.
    6. Chambers, Marcus J., 1999. "Discrete time representation of stationary and non-stationary continuous time systems," Journal of Economic Dynamics and Control, Elsevier, vol. 23(4), pages 619-639, February.
    7. Teles, Paulo & Wei, William W. S., 2000. "The effects of temporal aggregation on tests of linearity of a time series," Computational Statistics & Data Analysis, Elsevier, vol. 34(1), pages 91-103, July.
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    Cited by:

    1. David E. Bloom & David Canning & Günther Fink, 2014. "Disease and Development Revisited," Journal of Political Economy, University of Chicago Press, vol. 122(6), pages 1355-1366.
    2. ten Cate, Arie & Franses, Philip Hans, 2008. "Error-correction modelling in discrete and continuous time," Economics Letters, Elsevier, vol. 101(2), pages 140-141, November.

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    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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