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Stability Analysis Using Kalman Filtering, Scoring, EM, and an Adaptive EM method

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Economic Structural Change

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Summary

This chapter gives a detailed description of the implementation of ML estimation using scoring and EM for the hyperparameters of a particular econometric state-space. Kaiman filtering enters these methods in an essential way. The EM method can be turned into an on-line (adaptive) estimation method, which can be conveniently used for speeding up the ML estimation procedure. We apply these techniques to a random walk parameter model of a standard (Goldfeld type) West German money-demand function testing its stability via testing the variances of the random walk for zero. We compare these results to a descriptive stability analysis that uses so-called flexible least squares—a nonstochastic variant of Kaiman filtering.

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Authors
  1. Wolfgang Schneider
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Editor information

Editors and Affiliations

  1. Institut für Statistik, Wirtschaftsuniversität Wien, Augasse 2, A-1090, Wien, Austria

    Peter Hackl

  2. Stockholm School of Economics, Box 6501, S-113 83, Stockholm, Switzerland

    Anders Holger Westlund

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© 1991 Springer-Verlag Berlin Heidelberg

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Schneider, W. (1991). Stability Analysis Using Kalman Filtering, Scoring, EM, and an Adaptive EM method. In: Hackl, P., Westlund, A.H. (eds) Economic Structural Change. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-06824-3_14

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  • DOI: https://doi.org/10.1007/978-3-662-06824-3_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-06826-7

  • Online ISBN: 978-3-662-06824-3

  • eBook Packages: Springer Book Archive

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