Estimation and Tests

  • Christian Gouriéroux
Part of the Springer Series in Statistics book series (SSS)


The usual estimation and test procedures may be applied without difficulties to ARCH models. We begin by recalling the basic idea and general properties of the pseudo maximum likelihood method [hereafter referred to as PML]. In the particular case of ARCH models, the asymptotic precisions of the estimators have a closed form representation. We then compare the PML estimators to some two step least squares estimators and show that the latter ones, although intuitive and easy to implement, are usually much less precise. Finally, we discuss the construction of forecast intervals and the tests of the homoscedasticity hypothesis.


Conditional Variance Arch Model Forecast Interval Asymptotic Relative Efficiency Heteroscedastic Error 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media New York 1997

Authors and Affiliations

  • Christian Gouriéroux
    • 1
  1. 1.Centre de Recherche en Economie et StatistiqueLaboratoire de Finance-AssuranceMalakoff CedexFrance

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