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Identification through heteroskedasticity in a likelihood-based approach: some theoretical results

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  • Emanuele BACCHIOCCHI

Abstract

In this paper we show how the analysis of identification of simultaneous systems of equations with different volatility regimes can be addressed in a conventional likelihood-based setup, generalizing previous works in different directions. We discuss general conditions for identification and one of the results shows that an adequate number of different levels of heteroskedasticity is sufficient to identify the parameters of the structural form without the inclusion of any kind of restriction. A Full Information Maximum Likelihood (FIML) algorithm is discussed.

Suggested Citation

  • Emanuele BACCHIOCCHI, 2010. "Identification through heteroskedasticity in a likelihood-based approach: some theoretical results," Departmental Working Papers 2010-38, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    • Handle: RePEc:mil:wpdepa:2010-38
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    References listed on IDEAS

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    More about this item

    Keywords

    Simultaneous equations model; heteroskedasticity; identification; FIML;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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