Estimating continuous-time models on the basis of discrete data via an exact discrete analog

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    Abstract

    This paper offers a perspective on A.R. Bergstrom's contribution to continuous-time modeling, focusing on his preferred method of estimating the parameters of a structural continuous-time model using an exact discrete-time analog. Some inherent difficulties in this approach are discussed, which help to explain why, in spite of his prescience, the methods around his time were not universally adopted as he had hoped. Even so, it is argued that Bergstrom's contribution and legacy is secure and retains some relevance today for the analysis of macroeconomic and financial time series.

    Original languageEnglish
    Pages (from-to)1120-1137
    Number of pages18
    JournalEconometric Theory
    Volume25
    Issue number4
    DOIs
    Publication statusPublished - Aug 2009

    Keywords

    • GAUSSIAN ESTIMATION
    • DIFFERENTIAL-EQUATIONS
    • DYNAMIC-MODELS
    • TERM STRUCTURE
    • AUTOREGRESSIVE MODELS
    • TEMPORAL AGGREGATION
    • STOCHASTIC TRENDS
    • MARKOV-PROCESSES
    • FLOW DATA
    • ORDER

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