Conditional Maximum Likelihood Estimation for a Dynamic Test Model PDF Download

Author: Wilhelm F. Kempf
Publisher:
ISBN:
Category : Psychometrics
Languages : en
Pages : 146

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Book Description

Author: Francesco Bartolucci
Publisher:
ISBN:
Category :
Languages : en
Pages : 31

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Book Description
We show how the dynamic logit model for binary panel data may be approximated by a quadratic exponential model. Under the approximating model, simple sufficient statistics exist for the subject-specific parameters introduced to capture the unobserved heterogeneity between subjects. The latter must be distinguished from the state dependence which is accounted for by including the lagged response variable among the regressors. By conditioning on the sufficient statistics, we derive a pseudo conditional likelihood estimator for the structural parameters of the dynamic logit model which is very simple to compute. Asymptotic properties of this estimator are derived. Simulation results show that the estimator is competitive in terms of efficiency with estimators very recently proposed in the econometric literature. We also show how the approach may be exploited to construct a Wald-type test for state dependence.

Author: Hugo Kruiniger
Publisher:
ISBN:
Category : Economics
Languages : en
Pages : 42

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Author: Russell B. Millar
Publisher: John Wiley & Sons
ISBN: 1119977711
Category : Mathematics
Languages : en
Pages : 286

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Book Description
This book takes a fresh look at the popular and well-established method of maximum likelihood for statistical estimation and inference. It begins with an intuitive introduction to the concepts and background of likelihood, and moves through to the latest developments in maximum likelihood methodology, including general latent variable models and new material for the practical implementation of integrated likelihood using the free ADMB software. Fundamental issues of statistical inference are also examined, with a presentation of some of the philosophical debates underlying the choice of statistical paradigm. Key features: Provides an accessible introduction to pragmatic maximum likelihood modelling. Covers more advanced topics, including general forms of latent variable models (including non-linear and non-normal mixed-effects and state-space models) and the use of maximum likelihood variants, such as estimating equations, conditional likelihood, restricted likelihood and integrated likelihood. Adopts a practical approach, with a focus on providing the relevant tools required by researchers and practitioners who collect and analyze real data. Presents numerous examples and case studies across a wide range of applications including medicine, biology and ecology. Features applications from a range of disciplines, with implementation in R, SAS and/or ADMB. Provides all program code and software extensions on a supporting website. Confines supporting theory to the final chapters to maintain a readable and pragmatic focus of the preceding chapters. This book is not just an accessible and practical text about maximum likelihood, it is a comprehensive guide to modern maximum likelihood estimation and inference. It will be of interest to readers of all levels, from novice to expert. It will be of great benefit to researchers, and to students of statistics from senior undergraduate to graduate level. For use as a course text, exercises are provided at the end of each chapter.

Author: Gerhard Hakon Fischer
Publisher:
ISBN:
Category :
Languages : en
Pages : 16

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Author: Yongmiao Hong
Publisher: World Scientific
ISBN: 9811220204
Category : Business & Economics
Languages : en
Pages : 523

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Book Description
Modern economies are full of uncertainties and risk. Economics studies resource allocations in an uncertain market environment. As a generally applicable quantitative analytic tool for uncertain events, probability and statistics have been playing an important role in economic research. Econometrics is statistical analysis of economic and financial data. In the past four decades or so, economics has witnessed a so-called 'empirical revolution' in its research paradigm, and as the main methodology in empirical studies in economics, econometrics has been playing an important role. It has become an indispensable part of training in modern economics, business and management.This book develops a coherent set of econometric theory, methods and tools for economic models. It is written as a textbook for graduate students in economics, business, management, statistics, applied mathematics, and related fields. It can also be used as a reference book on econometric theory by scholars who may be interested in both theoretical and applied econometrics.

Author: Cheng Hsiao
Publisher: Cambridge University Press
ISBN: 1009076604
Category : Business & Economics
Languages : en
Pages : 539

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Book Description
Now in its fourth edition, this comprehensive introduction of fundamental panel data methodologies provides insights on what is most essential in panel literature. A capstone to the forty-year career of a pioneer of panel data analysis, this new edition's primary contribution will be the coverage of advancements in panel data analysis, a statistical method widely used to analyze two or higher-dimensional panel data. The topics discussed in early editions have been reorganized and streamlined to comprehensively introduce panel econometric methodologies useful for identifying causal relationships among variables, supported by interdisciplinary examples and case studies. This book, to be featured in Cambridge's Econometric Society Monographs series, has been the leader in the field since the first edition. It is essential reading for researchers, practitioners and graduate students interested in the analysis of microeconomic behavior.

Author: Raymond L. Chambers
Publisher: CRC Press
ISBN: 1420011359
Category : Mathematics
Languages : en
Pages : 374

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Book Description
Sample surveys provide data used by researchers in a large range of disciplines to analyze important relationships using well-established and widely used likelihood methods. The methods used to select samples often result in the sample differing in important ways from the target population and standard application of likelihood methods can lead to

Author: Anil Kashyap
Publisher: Academic Press
ISBN: 0080956319
Category : Computers
Languages : en
Pages : 351

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Book Description
Dynamic Stochastic Models from Empirical Data

Author: Scott R. Eliason
Publisher: SAGE
ISBN: 9780803941076
Category : Mathematics
Languages : en
Pages : 100

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Book Description
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.