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Identification through heteroskedasticity: a likelihood-based approach

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  • Emanuele BACCHIOCCHI

Abstract

In this paper we show how the analysis of identification of simultaneous equations systems 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 FullInformation Maximum Likelihood (FIML) algorithm is discussed and the small sample performances of estimators and tests on the parameters are studied through Monte Carlo simulations. Finally, this methodology is used to investigate the relationships between sovereign bond yields for some highly indebted EU countries.

Suggested Citation

  • Emanuele BACCHIOCCHI, 2011. "Identification through heteroskedasticity: a likelihood-based approach," Departmental Working Papers 2011-19, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    • Handle: RePEc:mil:wpdepa:2011-19
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    References listed on IDEAS

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    Keywords

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    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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