Surveys do! We examine the forecasting power of four alternative methods of forecasting U.S. inflation out-of-sample: time series ARIMA models; regressions using real activity measures motivated from the Phillips curve; term structure models that include linear, non-linear, and arbitrage-free specif...

Ausführliche Beschreibung

Bibliographische Detailangaben

Hauptverfasser:	Ang, Andrew (VerfasserIn), Bekaert, Geert 1964- (VerfasserIn), Wei, Min 1975- (VerfasserIn)
Format:	Buch
Sprache:	English
Veröffentlicht:	Cambridge, Mass. National Bureau of Economic Research 2005
Schriftenreihe:	Working paper series / National Bureau of Economic Research 11538
Online-Zugang:	Volltext
Zusammenfassung:	Surveys do! We examine the forecasting power of four alternative methods of forecasting U.S. inflation out-of-sample: time series ARIMA models; regressions using real activity measures motivated from the Phillips curve; term structure models that include linear, non-linear, and arbitrage-free specifications; and survey-based measures. We also investigate several optimal methods of combining forecasts. Our results show that surveys outperform the other forecasting methods and that the term structure specifications perform relatively poorly. We find little evidence that combining forecasts using means or medians, or using optimal weights with prior information produces superior forecasts to survey information alone. When combining forecasts, the data consistently places the highest weights on survey information.
Beschreibung:	53 S. graph. Darst. 22 cm