Comments on "Phillips Curve Inflation Forecasts" by James H. Stock and Mark W. Watson

Pagan, AR

Comments on "Phillips Curve Inflation Forecasts" by James H. Stock and Mark W. Watson

Pagan, AR

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Publisher:: MIT Press
Publication Type:: Chapter
Citation:: Understanding Inflation and the Implications for Monetary Policy: A Phillips Curve Retrospective, 2009, 1st, pp. 187 - 193
Issue Date:: 2009-01

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Field	Value	Language
dc.contributor.author	Pagan, AR	en_US
dc.contributor.editor	Fuhrer, J	en_US
dc.contributor.editor	Little, JS	en_US
dc.contributor.editor	Kodrzycki, YK	en_US
dc.contributor.editor	Olivei, GP	en_US
dc.date.issued	2009-01	en_US
dc.identifier.citation	Understanding Inflation and the Implications for Monetary Policy: A Phillips Curve Retrospective, 2009, 1st, pp. 187 - 193	en_US
dc.identifier.isbn	978-0-262-01363-5	en_US
dc.identifier.uri	http://hdl.handle.net/10453/17313
dc.description.abstract	Stock and Watson provide a thorough (one might say exhaustive) review of the forecasting performance of many inflation models. These include models with some economics in them and others that are purely statistical. Overall, the best of the statistical models seems to be their unobserved components-stochastic volatility (UC-SV) model. This is a two-component model of the form	en_US
dc.publisher	MIT Press	en_US
dc.relation.ispartof	Understanding Inflation and the Implications for Monetary Policy: A Phillips Curve Retrospective	en_US
dc.title	Comments on "Phillips Curve Inflation Forecasts" by James H. Stock and Mark W. Watson	en_US
dc.type	Chapter
utslib.location	Boston, USA	en_US
utslib.for	1402 Applied Economics	en_US
utslib.citation.edition	1st	en_US
dc.location.activity	Shanghai, China
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Business
utslib.copyright.status	closed_access
pubs.consider-herdc	false	en_US
pubs.edition	1st	en_US
pubs.place-of-publication	Boston, USA	en_US

Abstract:

Stock and Watson provide a thorough (one might say exhaustive) review of the forecasting performance of many inflation models. These include models with some economics in them and others that are purely statistical. Overall, the best of the statistical models seems to be their unobserved components-stochastic volatility (UC-SV) model. This is a two-component model of the form

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/17313