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Specification Tests For Non Gaussian Maximum Likelihood Estimators
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Book Synopsis Specification Tests for Non-Gaussian Maximum Likelihood Estimators by : Gabriele Fiorentini
Download or read book Specification Tests for Non-Gaussian Maximum Likelihood Estimators written by Gabriele Fiorentini and published by . This book was released on 2018 with total page 70 pages. Available in PDF, EPUB and Kindle. Book excerpt: We propose generalised DWH specification tests which simultaneously compare three or more likelihood-based estimators of conditional mean and variance parameters in multivariate conditionally heteroskedastic dynamic regression models. Our tests are useful for GARCH models and in many empirically relevant macro and finance applications involving VARs and multivariate regressions. To design powerful and reliable tests, we determine the rank deficiencies of the differences between the estimators' asymptotic covariance matrices under the null of correct specification, and take into account that some parameters remain consistently estimated under the alternative of distributional misspecification. Finally, we provide finite sample results through Monte Carlo simulations.
Book Synopsis Maximum Likelihood Estimation by : Scott R. Eliason
Download or read book Maximum Likelihood Estimation written by Scott R. Eliason and published by SAGE. This book was released on 1993 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a short introduction to Maximum Likelihood (ML) Estimation. It provides a general modeling framework that utilizes the tools of ML methods to outline a flexible modeling strategy that accommodates cases from the simplest linear models (such as the normal error regression model) to the most complex nonlinear models linking endogenous and exogenous variables with non-normal distributions. Using examples to illustrate the techniques of finding ML estimators and estimates, the author discusses what properties are desirable in an estimator, basic techniques for finding maximum likelihood solutions, the general form of the covariance matrix for ML estimates, the sampling distribution of ML estimators; the use of ML in the normal as well as other distributions, and some useful illustrations of likelihoods.
Book Synopsis Financial Modeling Under Non-Gaussian Distributions by : Eric Jondeau
Download or read book Financial Modeling Under Non-Gaussian Distributions written by Eric Jondeau and published by Springer Science & Business Media. This book was released on 2007-04-05 with total page 541 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines non-Gaussian distributions. It addresses the causes and consequences of non-normality and time dependency in both asset returns and option prices. The book is written for non-mathematicians who want to model financial market prices so the emphasis throughout is on practice. There are abundant empirical illustrations of the models and techniques described, many of which could be equally applied to other financial time series.
Book Synopsis A Full Heteroscedastic One-way Error Components Model Allowing for Unbalanced Panel by : Bernard Lejeune
Download or read book A Full Heteroscedastic One-way Error Components Model Allowing for Unbalanced Panel written by Bernard Lejeune and published by . This book was released on 2004 with total page 37 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Essays in Honour of Fabio Canova by : Juan J. Dolado
Download or read book Essays in Honour of Fabio Canova written by Juan J. Dolado and published by Emerald Group Publishing. This book was released on 2022-09-21 with total page 203 pages. Available in PDF, EPUB and Kindle. Book excerpt: Both parts of Volume 44 of Advances in Econometrics pay tribute to Fabio Canova for his major contributions to economics over the last four decades.
Book Synopsis Specification Testing and Quasi-maximum Likelihood Estimation by : Jeffrey M. Wooldridge
Download or read book Specification Testing and Quasi-maximum Likelihood Estimation written by Jeffrey M. Wooldridge and published by . This book was released on 1987 with total page 46 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis A Guide to Modern Econometrics by : Marno Verbeek
Download or read book A Guide to Modern Econometrics written by Marno Verbeek and published by John Wiley & Sons. This book was released on 2017-07-31 with total page 523 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Guide to Modern Econometrics, 5th Edition has become established as a highly successful textbook. It serves as a guide to alternative techniques in econometrics with an emphasis on intuition and the practical implementation of these approaches. This fifth edition builds upon the success of its predecessors. The text has been carefully checked and updated, taking into account recent developments and insights. It includes new material on causal inference, the use and limitation of p-values, instrumental variables estimation and its implementation, regression discontinuity design, standardized coefficients, and the presentation of estimation results.
Book Synopsis Maximum Likelihood Estimation with Stata, Fourth Edition by : William Gould
Download or read book Maximum Likelihood Estimation with Stata, Fourth Edition written by William Gould and published by Stata Press. This book was released on 2010-10-27 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Maximum Likelihood Estimation with Stata, Fourth Edition is written for researchers in all disciplines who need to compute maximum likelihood estimators that are not available as prepackaged routines. Readers are presumed to be familiar with Stata, but no special programming skills are assumed except in the last few chapters, which detail how to add a new estimation command to Stata. The book begins with an introduction to the theory of maximum likelihood estimation with particular attention on the practical implications for applied work. Individual chapters then describe in detail each of the four types of likelihood evaluator programs and provide numerous examples, such as logit and probit regression, Weibull regression, random-effects linear regression, and the Cox proportional hazards model. Later chapters and appendixes provide additional details about the ml command, provide checklists to follow when writing evaluators, and show how to write your own estimation commands.
Book Synopsis Econometric Theory and Practice by : P. C. B. Phillips
Download or read book Econometric Theory and Practice written by P. C. B. Phillips and published by Cambridge University Press. This book was released on 2006-01-09 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: The essays in this book explore important theoretical and applied advances in econometrics.
Book Synopsis Consistent Non-Gausian Pseudo Maximum Likelihood Estimators by : Gabriele Fiorentini
Download or read book Consistent Non-Gausian Pseudo Maximum Likelihood Estimators written by Gabriele Fiorentini and published by . This book was released on 2018 with total page 73 pages. Available in PDF, EPUB and Kindle. Book excerpt: We characterise the mean and variance parameters that distributionally misspecified maximum likelihood estimators can consistently estimate in multivariate conditionally heteroskedastic dynamic regression models. We also provide simple closed-form consistent estimators for the rest. The inclusion of means and the explicit coverage of multivariate models make our procedures useful not only for GARCH models but also in many empirically relevant macro and finance applications involving VARs and multivariate regressions. We study the statistical properties of our proposed consistent estimators, as well as their efficiency relative to Gaussian pseudo maximum likelihood procedures. Finally, we provide finite sample results through Monte Carlo simulations.
Book Synopsis Consistency of Quasi-Maximum Likelihood Estimators for Models with Conditional Heteroskedasticity by : Whitney K. Newey
Download or read book Consistency of Quasi-Maximum Likelihood Estimators for Models with Conditional Heteroskedasticity written by Whitney K. Newey and published by . This book was released on 2008 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Econometric Applications of Maximum Likelihood Methods by : Jan Salomon Cramer
Download or read book Econometric Applications of Maximum Likelihood Methods written by Jan Salomon Cramer and published by CUP Archive. This book was released on 1989-04-28 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: The advent of electronic computing permits the empirical analysis of economic models of far greater subtlety and rigour than before, when many interesting ideas were not followed up because the calculations involved made this impracticable. The estimation and testing of these more intricate models is usually based on the method of Maximum Likelihood, which is a well-established branch of mathematical statistics. Its use in econometrics has led to the development of a number of special techniques; the specific conditions of econometric research moreover demand certain changes in the interpretation of the basic argument. This book is a self-contained introduction to this field. It consists of three parts. The first deals with general features of Maximum Likelihood methods; the second with linear and nonlinear regression; and the third with discrete choice and related micro-economic models. Readers should already be familiar with elementary statistical theory, with applied econometric research papers, or with the literature on the mathematical basis of Maximum Likelihood theory. They can also try their hand at some advanced econometric research of their own.
Book Synopsis Asymptotic Properties of maximum Likelihood estimators based on conditional specification by : Pranab Kumar Sen
Download or read book Asymptotic Properties of maximum Likelihood estimators based on conditional specification written by Pranab Kumar Sen and published by . This book was released on 1978 with total page 24 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Robust Testing Procedures Based on S-estimate for the Dispersion Parameter of Univariate and Multivariate Normal Distribution and for the Two-way Mixed Effect Models by : Shagufta Aslam
Download or read book Robust Testing Procedures Based on S-estimate for the Dispersion Parameter of Univariate and Multivariate Normal Distribution and for the Two-way Mixed Effect Models written by Shagufta Aslam and published by . This book was released on 2002 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Misspecification Tests in Econometrics by : L. G. Godfrey
Download or read book Misspecification Tests in Econometrics written by L. G. Godfrey and published by Cambridge University Press. This book was released on 1988 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: Misspecification tests play an important role in detecting unreliable and inadequate economic models. This book brings together many results from the growing literature in econometrics on misspecification testing. It provides theoretical analyses and convenient methods for application. The main emphasis is on the Lagrange multiplier principle, which provides considerable unification, although several other approaches are also considered. The author also examines general checks for model adequacy that do not involve formulation of an alternative hypothesis. General and specific tests are discussed in the context of multiple regression models, systems of simultaneous equations, and models with qualitative or limited dependent variables.
Book Synopsis Maximum Likelihood Estimation by : Scott R. Eliason
Download or read book Maximum Likelihood Estimation written by Scott R. Eliason and published by SAGE Publications. This book was released on 1993-08-09 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Maximum Likelihood Estimation. . . provides a useful introduction. . . it is clear and easy to follow with applications and graphs. . . . I consider this a very useful book. . . . well-written, with a wealth of explanation. . ." --Dougal Hutchison in Educational Research Eliason reveals to the reader the underlying logic and practice of maximum likelihood (ML) estimation by providing a general modeling framework that utilizes the tools of ML methods. This framework offers readers a flexible modeling strategy since it accommodates cases from the simplest linear models (such as the normal error regression model) to the most complex nonlinear models that link a system of endogenous and exogenous variables with non-normal distributions. Using examples to illustrate the techniques of finding ML estimators and estimates, Eliason discusses what properties are desirable in an estimator, basic techniques for finding maximum likelihood solutions, the general form of the covariance matrix for ML estimates, the sampling distribution of ML estimators; the use of ML in the normal as well as other distributions, and some useful illustrations of likelihoods.
Download or read book Biometrika written by D. M. Titterington and published by . This book was released on 2001 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: The year 2001 marks the centenary of Biometrika, one of the world's leading academic journals in statistical theory and methodology. In celebration of this, the book brings together two sets of papers from the journal. The first comprises seven specially commissioned articles (authors: D.R. Cox, A.C. Davison, Anthony C. Atkinson and R.A. Bailey, David Oakes, Peter Hall, T.M.F. Smith, and Howell Tong). These articles review the history of the journal and the most important contributions made by appearing in the journal in a number of important areas of statitisical activity, including general theory and methodology, surveys and time sets. In the process the papers describe the general development of statistical science during the twentieth century. The second group of ten papers are a selection of particularly seminal articles form the journal's first hundred years. The book opens with an introduction by the editors Professor D.M. Titterington and Sir David Cox.
