Likelihood-based Inference in Cointegrated Vector Autoregressive Models PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Likelihood-based Inference in Cointegrated Vector Autoregressive Models PDF full book. Access full book title Likelihood-based Inference in Cointegrated Vector Autoregressive Models by Søren Johansen. Download full books in PDF and EPUB format.
Author: Søren Johansen
Publisher: Oxford University Press, USA
ISBN: 0198774508
Category : Business & Economics
Languages : en
Pages : 280
Get Book Here
Book Description
This monograph is concerned with the statistical analysis of multivariate systems of non-stationary time series of type I. It applies the concepts of cointegration and common trends in the framework of the Gaussian vector autoregressive model.
Author: Søren Johansen
Publisher: Oxford University Press, USA
ISBN: 0198774508
Category : Business & Economics
Languages : en
Pages : 280
Get Book Here
Book Description
This monograph is concerned with the statistical analysis of multivariate systems of non-stationary time series of type I. It applies the concepts of cointegration and common trends in the framework of the Gaussian vector autoregressive model.
Author: Luc Bauwens
Publisher: OUP Oxford
ISBN: 0191588466
Category : Business & Economics
Languages : en
Pages : 370
Get Book Here
Book Description
This book contains an up-to-date coverage of the last twenty years advances in Bayesian inference in econometrics, with an emphasis on dynamic models. It shows how to treat Bayesian inference in non linear models, by integrating the useful developments of numerical integration techniques based on simulations (such as Markov Chain Monte Carlo methods), and the long available analytical results of Bayesian inference for linear regression models. It thus covers a broad range of rather recent models for economic time series, such as non linear models, autoregressive conditional heteroskedastic regressions, and cointegrated vector autoregressive models. It contains also an extensive chapter on unit root inference from the Bayesian viewpoint. Several examples illustrate the methods.
Author: John Geweke
Publisher: Oxford University Press
ISBN: 0191618268
Category : Business & Economics
Languages : en
Pages : 576
Get Book Here
Book Description
Bayesian econometric methods have enjoyed an increase in popularity in recent years. Econometricians, empirical economists, and policymakers are increasingly making use of Bayesian methods. This handbook is a single source for researchers and policymakers wanting to learn about Bayesian methods in specialized fields, and for graduate students seeking to make the final step from textbook learning to the research frontier. It contains contributions by leading Bayesians on the latest developments in their specific fields of expertise. The volume provides broad coverage of the application of Bayesian econometrics in the major fields of economics and related disciplines, including macroeconomics, microeconomics, finance, and marketing. It reviews the state of the art in Bayesian econometric methodology, with chapters on posterior simulation and Markov chain Monte Carlo methods, Bayesian nonparametric techniques, and the specialized tools used by Bayesian time series econometricians such as state space models and particle filtering. It also includes chapters on Bayesian principles and methodology.
Author: Katarina Juselius
Publisher: OUP Oxford
ISBN: 0191622966
Category : Business & Economics
Languages : en
Pages : 478
Get Book Here
Book Description
This valuable text provides a comprehensive introduction to VAR modelling and how it can be applied. In particular, the author focuses on the properties of the Cointegrated VAR model and its implications for macroeconomic inference when data are non-stationary. The text provides a number of insights into the links between statistical econometric modelling and economic theory and gives a thorough treatment of identification of the long-run and short-run structure as well as of the common stochastic trends and the impulse response functions, providing in each case illustrations of applicability. This book presents the main ingredients of the Copenhagen School of Time-Series Econometrics in a transparent and coherent framework. The distinguishing feature of this school is that econometric theory and applications have been developed in close cooperation. The guiding principle is that good econometric work should take econometrics, institutions, and economics seriously. The author uses a single data set throughout most of the book to guide the reader through the econometric theory while also revealing the full implications for the underlying economic model. To test ensure full understanding the book concludes with the introduction of two new data sets to combine readers understanding of econometric theory and economic models, with economic reality.
Author: Gary Koop
Publisher: Now Publishers Inc
ISBN: 160198362X
Category : Business & Economics
Languages : en
Pages : 104
Get Book Here
Book Description
Bayesian Multivariate Time Series Methods for Empirical Macroeconomics provides a survey of the Bayesian methods used in modern empirical macroeconomics. These models have been developed to address the fact that most questions of interest to empirical macroeconomists involve several variables and must be addressed using multivariate time series methods. Many different multivariate time series models have been used in macroeconomics, but Vector Autoregressive (VAR) models have been among the most popular. Bayesian Multivariate Time Series Methods for Empirical Macroeconomics reviews and extends the Bayesian literature on VARs, TVP-VARs and TVP-FAVARs with a focus on the practitioner. The authors go beyond simply defining each model, but specify how to use them in practice, discuss the advantages and disadvantages of each and offer tips on when and why each model can be used.
Author: G. S. Maddala
Publisher: Cambridge University Press
ISBN: 9780521587822
Category : Business & Economics
Languages : en
Pages : 528
Get Book Here
Book Description
A comprehensive review of unit roots, cointegration and structural change from a best-selling author.
Author: Helmut Lütkepohl
Publisher: Springer Science & Business Media
ISBN: 3662026910
Category : Business & Economics
Languages : en
Pages : 556
Get Book Here
Book Description
Author: Thomas B. Fomby
Publisher: Emerald Group Publishing Limited
ISBN: 9781781907528
Category : Business & Economics
Languages : en
Pages : 0
Get Book Here
Book Description
Advances in Econometrics publishes original scholarly econometric papers with the intention of expanding the use of developed and emerging econometric techniques by disseminating ideas on the theory and practice of econometrics, throughout the empirical economic, business and social science literature.
Author: Bernhard Pfaff
Publisher: Springer Science & Business Media
ISBN: 0387759670
Category : Business & Economics
Languages : en
Pages : 193
Get Book Here
Book Description
This book is designed for self study. The reader can apply the theoretical concepts directly within R by following the examples.
Author: Patrick T. Brandt
Publisher: SAGE
ISBN: 1412906563
Category : Mathematics
Languages : en
Pages : 121
Get Book Here
Book Description
Many analyses of time series data involve multiple, related variables. Modeling Multiple Time Series presents many specification choices and special challenges. This book reviews the main competing approaches to modeling multiple time series: simultaneous equations, ARIMA, error correction models, and vector autoregression. The text focuses on vector autoregression (VAR) models as a generalization of the other approaches mentioned. Specification, estimation, and inference using these models is discussed. The authors also review arguments for and against using multi-equation time series models. Two complete, worked examples show how VAR models can be employed. An appendix discusses software that can be used for multiple time series models and software code for replicating the examples is available. Key Features: * Offers a detailed comparison of different time series methods and approaches. * Includes a self-contained introduction to vector autoregression modeling. * Situates multiple time series modeling as a natural extension of commonly taught statistical models.
