Dating business cycle turning points / Marcelle Chauvet, James D. Hamilton -- A new framework to 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 st...

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Bibliographische Detailangaben

Format:	Elektronisch E-Book
Sprache:	English
Veröffentlicht:	Boston Elsevier c2006
Ausgabe:	1st ed
Schriftenreihe:	Contributions to economic analysis v. 276
Schlagworte:	bisacsh Business & Economics / Economics / Microeconomics Business & Economics / Economics / General Business strategy Business mathematics & systems Business cycles / Econometric models Econometric models Nonlinear systems Konjunkturzyklus Nichtlineare Zeitreihenanalyse
Online-Zugang:	FHN01 FWS01 FWS02 UEI01 UER01 Volltext
Zusammenfassung:	Dating business cycle turning points / Marcelle Chauvet, James D. Hamilton -- A new framework to 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 using a fourier-series approximation / Ralf Becker, Stan Hurn -- Random walk smooth transition autoregressive models / Heather M. Anderson, Chin Nam Low -- Nonlinearity and structural change in 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, Øyvind Eitrheim, Lucio Sarno -- A predictive comparison of some 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 business cycle features / James Morley, Jeremy Piger -- The vector floor and ceiling model / Gary Koop, Simon Potter 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 this set 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 of output and employment to oil-price and monetary shocks? How does monetary policy respond to asymmetries over the business cycle? Are business cycles due more to permanent or to transitory negative shocks? And, is the business cycle asymmetric, and does 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 all areas of macroeconomics and microeconomics
Beschreibung:	Includes bibliographical references and index 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 this set 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 of output and employment to oil-price and monetary shocks? How does monetary policy respond to asymmetries over the business cycle? Are business cycles due more to permanent or to transitory negative shocks? And, is the business cycle asymmetric, and does 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 all areas of macroeconomics and microeconomics
Beschreibung:	1 Online-Ressource (xxiv, 435 p.)
ISBN:	9781849508339