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Nonlinear time series analysis of business cycles

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Nonlinear time series analysis of business cycles/ editors Costas Milas, Philip Rothman, Dick van Dijk.
Author:	Dijk, Dick van.
other author:	Milas, Costas.
Published:	Boston :Elsevier, : c2006.,
Description:	1 online resource (xxiv, 435 p.).
Subject:	Business cycles - Econometric models. -
Online resource:	http://www.emeraldinsight.com/0573-8555/276
ISBN:	9781849508339 (electronic bk.)

Nonlinear time series analysis of business cycles
Dijk, Dick van.

Nonlinear time series analysis of business cycles[electronic resource] /editors Costas Milas, Philip Rothman, Dick van Dijk. - 1st ed. - Boston :Elsevier,c2006. - 1 online resource (xxiv, 435 p.). - Contributions to economic analysis,v. 2760573-8555 ;. - Contributions to economic analysis ;v. 210..

Includes bibliographical references and index.

Dating business cycle turning points / Marcelle Chauvet, James D. Hamilton -- A new frameworkto analyze business cycle synchronization / Jeffrey A. Modisett, Judge David J. Dreyer -- Non-linearity and instability in the Euro area / Massimiliano Marcellino -- Nonlinear modelling of autoregressive structural breaks in some US macroeconomic series / George Kapetanios, Elias Tzavalis -- Trend-cycle decomposition models with smooth-transition parameters : evidence from U.S. economic time series / Siem Jan Koopman, Soon Yip Wong, David E. Wildasin -- Modeling inflation and money demand usinga fourier-series approximation / Ralf Becker, Stan Hurn -- Random walk smooth transition autoregressive models / Heather M. Anderson, Chin Nam Low -- Nonlinearity and structural changein interest rate reaction functions for the US, UK and Germany / Mehtap Kesriyeli, Denise R. Osborn -- State asymmetries in the effects of monetary policy shocks on output : some new evidence for the Euro-Area / Juan J. Dolado, Ramon Maria-Dolores -- Non-linear dynamics in output, real exchange rates and real money balances : Norway, 1830-2003 / Q.Farooq Akram, (C)yvind Eitrheim, Lucio Sarno -- A predictive comparison ofsome simple long- and short memory models of daily U.S. stock returns,with emphasis on business cycle effects / Geetesh Bhardwaj, Norman R. Swanson -- Nonlinear modeling of the changing lag structure in U.S. housing construction / Christian M. Dahl, Tamer Kulaksizoglu -- Combining predictors and combining information in modelling : forecasting US recession probabilities and output growth/ Michael P. Clements, Ana Beatriz Galvao -- The importance of nonlinearity in reproducing businesscycle features / James Morley, Jeremy Piger -- The vector floor and ceilingmodel / Gary Koop, SimonPotter.

The business cycle has long been the focus of empirical economic research. Until recently statistical analysis of macroeconomic fluctuations was dominated by linear time series methods. Over the past 15 years, however, economists have increasingly applied tractable parametric nonlinear time series models to business cycle data; most prominent in thisset of models are the classes of Threshold AutoRegressive (TAR) models, Markov-Switching AutoRegressive (MSAR) models, and Smooth Transition AutoRegressive (STAR) models. In doing so, several important questions have been addressed in the literature, including: Do out-of-sample (point, interval, density, and turning point) forecasts obtained with nonlinear time series models dominate those generated with linear models? How should business cycles be dated and measured? What is the response ofoutput and employment to oil-price and monetary shocks? How does monetary policy respond to asymmetries over the business cycle? Are businesscycles due more to permanent or to transitory negative shocks? And, isthe business cycle asymmetric, anddoes it matter? Contributions to Economic Analysis was established in 1952. The series purpose is to stimulate the international exchange of scientific information. The series includes books from allareas of macroeconomics and microeconomics.

ISBN: 9781849508339 (electronic bk.)

LCCN: 2005056288Subjects--Topical Terms:

810078
Business cycles
--Econometric models.

LC Class. No.: HB3711 / .N664 2006

Dewey Class. No.: 338.5/420151955

Universal Decimal Class. No.: 330.33:303.725.33

Nonlinear time series analysis of business cycles
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520 $a The business cycle has long been the focus of empirical economic research. Until recently statistical analysis of macroeconomic fluctuations was dominated by linear time series methods. Over the past 15 years, however, economists have increasingly applied tractable parametric nonlinear time series models to business cycle data; most prominent in thisset of models are the classes of Threshold AutoRegressive (TAR) models, Markov-Switching AutoRegressive (MSAR) models, and Smooth Transition AutoRegressive (STAR) models. In doing so, several important questions have been addressed in the literature, including: Do out-of-sample (point, interval, density, and turning point) forecasts obtained with nonlinear time series models dominate those generated with linear models? How should business cycles be dated and measured? What is the response ofoutput and employment to oil-price and monetary shocks? How does monetary policy respond to asymmetries over the business cycle? Are businesscycles due more to permanent or to transitory negative shocks? And, isthe business cycle asymmetric, anddoes it matter? Contributions to Economic Analysis was established in 1952. The series purpose is to stimulate the international exchange of scientific information. The series includes books from allareas of macroeconomics and microeconomics.
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