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Least Squares Estimation of Linear and Nonlinear ARMAX Models under Data Heterogeneity

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  • Herman J. Bierens

Abstract

In this paper we consider the asymptotic properties of least squares estimators of the parameters of linear and nonlinear ARMAX models under data heterogeneity, where we allow the X-variables to be stochastic time series themselves, possibly depending on lagged dependent variables. These results are obtained by a further elaboration of the results in Bierens [1984, 1987].

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  • Herman J. Bierens, 1991. "Least Squares Estimation of Linear and Nonlinear ARMAX Models under Data Heterogeneity," Annals of Economics and Statistics, GENES, issue 20-21, pages 143-169.
    • Handle: RePEc:adr:anecst:y:1991:i:20-21:p:143-169
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    File URL: http://www.jstor.org/stable/20075810
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    Cited by:

    1. de Jong, Robert M., 1996. "The Bierens test under data dependence," Journal of Econometrics, Elsevier, vol. 72(1-2), pages 1-32.
    2. Jonathan B. Hill, 2013. "Consistent GMM Residuals-Based Tests of Functional Form," Econometric Reviews, Taylor & Francis Journals, vol. 32(3), pages 361-383, November.
    3. Hill Jonathan B., 2013. "Stochastically weighted average conditional moment tests of functional form," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(2), pages 121-139, April.
    4. Broersma, L., 1992. "Profits and employment in the United States 1970-1991," Serie Research Memoranda 0039, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.

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