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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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    1. Favero, Carlo A. & Giavazzi, Francesco, 2002. "Is the international propagation of financial shocks non-linear?: Evidence from the ERM," Journal of International Economics, Elsevier, vol. 57(1), pages 231-246, June.
    2. Roberto Rigobon & Brian Sack, 2003. "Measuring The Reaction of Monetary Policy to the Stock Market," The Quarterly Journal of Economics, Oxford University Press, vol. 118(2), pages 639-669.
    3. Andrew C. Harvey, 1990. "The Econometric Analysis of Time Series, 2nd Edition," MIT Press Books, The MIT Press, edition 2, volume 1, number 026208189x, December.
    4. Caporale, Guglielmo Maria & Cipollini, Andrea & Demetriades, Panicos O., 2005. "Monetary policy and the exchange rate during the Asian crisis: identification through heteroscedasticity," Journal of International Money and Finance, Elsevier, vol. 24(1), pages 39-53, February.
    5. Rigobon, Roberto, 2002. "The curse of non-investment grade countries," Journal of Development Economics, Elsevier, vol. 69(2), pages 423-449, December.
    6. Sentana, Enrique & Fiorentini, Gabriele, 2001. "Identification, estimation and testing of conditionally heteroskedastic factor models," Journal of Econometrics, Elsevier, vol. 102(2), pages 143-164, June.
    7. Rothenberg, Thomas J, 1971. "Identification in Parametric Models," Econometrica, Econometric Society, vol. 39(3), pages 577-591, May.
    8. Normandin, Michel & Phaneuf, Louis, 2004. "Monetary policy shocks:: Testing identification conditions under time-varying conditional volatility," Journal of Monetary Economics, Elsevier, vol. 51(6), pages 1217-1243, September.
    9. Roberto Rigobon, 2003. "Identification Through Heteroskedasticity," The Review of Economics and Statistics, MIT Press, vol. 85(4), pages 777-792, November.
    10. King, Mervyn & Sentana, Enrique & Wadhwani, Sushil, 1994. "Volatility and Links between National Stock Markets," Econometrica, Econometric Society, vol. 62(4), pages 901-933, July.
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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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