Nuisance parameters, composite likelihoods and a panel of GARCH models.

We investigate the properties of the composite likelihood (CL) method for (T x NT) GARCH panels. The defining feature of a GARCH panel with time series length T is that, while nuisance parameters are allowed to vary across NT series, other parameters of interest are assumed to be common. CL pools...

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Main Authors: Pakel, C, Shephard, N, Sheppard, K
Format: Working paper
Language:English
Published: Department of Economics (University of Oxford) 2009
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author Pakel, C
Shephard, N
Sheppard, K
author_facet Pakel, C
Shephard, N
Sheppard, K
author_sort Pakel, C
collection OXFORD
description We investigate the properties of the composite likelihood (CL) method for (T x NT) GARCH panels. The defining feature of a GARCH panel with time series length T is that, while nuisance parameters are allowed to vary across NT series, other parameters of interest are assumed to be common. CL pools information across the panel instead of using information available in a single series only. Simulations and empirical analysis illustate that in reasonably large T CL performs well. However, due to the estimation error introduced through nuisance parameter estimation, CL is subject to the “incidental parameter” problem for small T.
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spelling oxford-uuid:4a2e3870-50d0-4375-9ea4-9e94c3b01e332022-03-26T15:36:06ZNuisance parameters, composite likelihoods and a panel of GARCH models.Working paperhttp://purl.org/coar/resource_type/c_8042uuid:4a2e3870-50d0-4375-9ea4-9e94c3b01e33EnglishDepartment of Economics - ePrintsDepartment of Economics (University of Oxford)2009Pakel, CShephard, NSheppard, KWe investigate the properties of the composite likelihood (CL) method for (T x NT) GARCH panels. The defining feature of a GARCH panel with time series length T is that, while nuisance parameters are allowed to vary across NT series, other parameters of interest are assumed to be common. CL pools information across the panel instead of using information available in a single series only. Simulations and empirical analysis illustate that in reasonably large T CL performs well. However, due to the estimation error introduced through nuisance parameter estimation, CL is subject to the “incidental parameter” problem for small T.
spellingShingle Pakel, C
Shephard, N
Sheppard, K
Nuisance parameters, composite likelihoods and a panel of GARCH models.
title Nuisance parameters, composite likelihoods and a panel of GARCH models.
title_full Nuisance parameters, composite likelihoods and a panel of GARCH models.
title_fullStr Nuisance parameters, composite likelihoods and a panel of GARCH models.
title_full_unstemmed Nuisance parameters, composite likelihoods and a panel of GARCH models.
title_short Nuisance parameters, composite likelihoods and a panel of GARCH models.
title_sort nuisance parameters composite likelihoods and a panel of garch models
work_keys_str_mv AT pakelc nuisanceparameterscompositelikelihoodsandapanelofgarchmodels
AT shephardn nuisanceparameterscompositelikelihoodsandapanelofgarchmodels
AT sheppardk nuisanceparameterscompositelikelihoodsandapanelofgarchmodels