Deriving the exact discrete analog of a continuous time system

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    Abstract

    The exact discrete model satisfied by equispaced data generated by a linear stochastic differential equations system is derived by a method that does not imply restrictions on observed discrete data per se. The method involves integrating the solution of the continuous time model in state space form and a nonstandard change in the order of three types of integration, facilitating the representation of the exact discrete model as an asymptotically time-invariant vector autoregressive moving average model. The method applying to the state space form is general and is illustrated using the prototypical higher order model for mixed stock and flow data discussed by Bergstrom (1986, Econometric Theory 2, 350-373).

    Original languageEnglish
    Pages (from-to)998-1015
    Number of pages18
    JournalEconometric Theory
    Volume16
    Issue number6
    Publication statusPublished - Dec 2000

    Keywords

    • GAUSSIAN ESTIMATION
    • STOCHASTIC TRENDS
    • DYNAMIC-MODELS

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