The likelihood function of a conditionally heteroskedastic factor model with heywood cases PDF Download

Author: Enrique Sentana
Publisher:
ISBN:
Category :
Languages : es
Pages : 17

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Author: Enrique Sentana
Publisher:
ISBN: 9788477933366
Category :
Languages : en
Pages : 20

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Author: Catherine Doz
Publisher:
ISBN:
Category : Business enterprises
Languages : en
Pages : 0

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Author: Renault, Éric
Publisher: Montréal : CIRANO
ISBN:
Category :
Languages : en
Pages : 55

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Author: Enrique Sentana
Publisher:
ISBN:
Category :
Languages : es
Pages : 38

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Author: Maddalena Cavicchioli
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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In this work, we give simple matrix formulae for maximum likelihood estimates of parameters in a broad class of vector autoregressions subject to Markovian changes in regime. This allows us to determine explicitly the asymptotic variance-covariance matrix of the estimators, giving a concrete possibility for the use of the classical testing procedures. In the context of multivariate autoregressive conditional heteroskedastic models with changes in regime, we provide formulae for the analytic derivatives of the log likelihood. Then we prove the consistency of some maximum likelihood estimators and give some formulae for the asymptotic variance of the different estimators.

Author:
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ISBN:
Category : Econometrics
Languages : fr
Pages : 604

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Author: Whitney K. Newey
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Virtually all empirical studies that assume a time-varying conditional variance use a quasi-maximum likelihood estimator (QMLE). If the density from which the likelihood is constructed is assumed to be Gaussian, the QMLE is known to be consistent under correct specification of both the conditional mean and conditional variance. We show that if both the assumed density and the true density are symmetric a QMLE remains consistent. If, however, either the assumed density or the true density is asymmetric, a QMLE is generally not consistent. To ensure that a QMLE is consistent under asymmetric densities, we include the conditional standard deviation as a regressor. We calculate the efficiency loss associated with the added regressor if the densities are symmetric and show that for a QMLE of the conditional variance parameters of a GARCH process there is no efficiency loss. Finally, we develop a test of consistency of a QMLE from the significance of the additional regressor.

Author: Jörg Henseler
Publisher: Guilford Publications
ISBN: 1462545610
Category : Social Science
Languages : en
Pages : 387

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This book presents powerful tools for integrating interrelated composites--such as capabilities, policies, treatments, indices, and systems--into structural equation modeling (SEM). Jörg Henseler introduces the types of research questions that can be addressed with composite-based SEM and explores the differences between composite- and factor-based SEM, variance- and covariance-based SEM, and emergent and latent variables. Using rich illustrations and walked-through data sets, the book covers how to specify, identify, estimate, and assess composite models using partial least squares path modeling, maximum likelihood, and other estimators, as well as how to interpret findings and report the results. Advanced topics include confirmatory composite analysis, mediation analysis, second-order constructs, interaction effects, and importance–performance analysis. Most chapters conclude with software tutorials for ADANCO and the R package cSEM. The companion website includes data files and syntax for the book's examples, along with presentation slides.

Author:
Publisher:
ISBN:
Category : Mathematical statistics
Languages : en
Pages : 866

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The Current Index to Statistics (CIS) is a bibliographic index of publications in statistics, probability, and related fields.