An Examination of Distributed Lag Model Coefficients Estimated with Smoothness Priors PDF Download
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Author: S. S. Thurman
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 46
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Book Description
Author: S. S. Thurman
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 46
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Book Description
Author: S. S. Thurman
Publisher:
ISBN:
Category : Distributed lags (Economics)
Languages : en
Pages : 27
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Book Description
Author: S. S. Thurman
Publisher:
ISBN:
Category : Distributed lags (Economics)
Languages : en
Pages : 17
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Book Description
Author: Grace Wahba
Publisher:
ISBN:
Category : Distribution (Probability theory)
Languages : en
Pages : 12
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Book Description
Author: Svend Hylleberg
Publisher: Academic Press
ISBN: 1483277747
Category : Business & Economics
Languages : en
Pages : 284
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Book Description
Seasonality in Regression presents the problems of seasonality in economic regression models. This book discusses the procedures that may have application in practical econometric work. Organized into eight chapters, this book begins with an overview of the tremendous increase in the computational capabilities made by the development of the electronic computer that has profound implications for the way seasonality is handled by economists. This text then examines some seasonal models and their characteristics. Other chapters consider the most frequently applied evaluation criteria and appraise the values in the applications. This book discusses as well the frequency domain estimators and provides insight into problems of estimating the disturbance–covariance matrix through the use of the disturbance spectrum. The final chapter deals with the main objective of the treatment of personality to formulate and estimate econometric models. This book is a valuable resource for economists and econometricians who have knowledge of econometrics at an advanced undergraduate or graduate level.
Author:
Publisher:
ISBN:
Category : Statistics
Languages : en
Pages : 530
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Book Description
Author: W.E. Griffiths
Publisher: Elsevier
ISBN: 148329708X
Category : Business & Economics
Languages : en
Pages : 391
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Book Description
This volume honors George Judge and his many, varied and outstanding contributions to econometrics, statistics, mathematical programming and spatial equilibrium modeling. The papers are grouped into four parts, each part representing an area in which Professor Judge has made a significant contribution. The authors have all benefited in some way, directly or indirectly, through an association with George Judge and his work. The three papers in Part I are concerned with various aspects of pre-test and Stein-rule estimation. Part II contains applications of Bayesian methodology, new developments in Bayesian methodology, and an overview of Bayesian econometrics. The papers in Part III comprise new developments in time-series analysis, improved estimation and Markov chain analysis. The final part on spatial equilibrium modeling contains papers that had their origins from Professor Judge's pioneering work in the 60's.
Author: Hirotugu Akaike
Publisher:
ISBN:
Category :
Languages : en
Pages : 17
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Book Description
In the application of Shiller's smoothness prior for distributed lag estimation the main difficulty is the selection of hyperparameters of the prior distribution. In this paper the use of a maximum likelihood procedure is proposed for this purpose and its performance is demonstrated by numerical examples.
Author: Genshiro Kitagawa
Publisher: Springer Science & Business Media
ISBN: 1461207614
Category : Mathematics
Languages : en
Pages : 265
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Book Description
Smoothness Priors Analysis of Time Series addresses some of the problems of modeling stationary and nonstationary time series primarily from a Bayesian stochastic regression "smoothness priors" state space point of view. Prior distributions on model coefficients are parametrized by hyperparameters. Maximizing the likelihood of a small number of hyperparameters permits the robust modeling of a time series with relatively complex structure and a very large number of implicitly inferred parameters. The critical statistical ideas in smoothness priors are the likelihood of the Bayesian model and the use of likelihood as a measure of the goodness of fit of the model. The emphasis is on a general state space approach in which the recursive conditional distributions for prediction, filtering, and smoothing are realized using a variety of nonstandard methods including numerical integration, a Gaussian mixture distribution-two filter smoothing formula, and a Monte Carlo "particle-path tracing" method in which the distributions are approximated by many realizations. The methods are applicable for modeling time series with complex structures.
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Author: P. A. V. B. Swamy
Publisher:
ISBN:
Category : Economic forecasting
Languages : en
Pages : 42
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Book Description
