Arbeitspapier
Boosting Non-linear Predictability of Macroeconomic Time Series
We apply the boosting estimation method to investigate to what ex-tent and at what horizons macroeconomic time series have nonlinearpredictability coming from their own history. Our results indicate thatthe U.S. macroeconomic time series have more exploitable nonlinearpredictability than previous studies have found. On average, the mostfavorable out-of-sample performance is obtained by a two-stage proce-dure, where a conventional linear prediction model is fine-tuned by theboosting technique.
- Sprache
-
Englisch
- Erschienen in
-
Series: Discussion paper ; No. 124
- Klassifikation
-
Wirtschaft
Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
Forecasting Models; Simulation Methods
Macroeconomics: Consumption, Saving, Production, Employment, and Investment: Forecasting and Simulation: Models and Applications
Prices, Business Fluctuations, and Cycles: Forecasting and Simulation: Models and Applications
Money and Interest Rates: Forecasting and Simulation: Models and Applications
- Thema
-
boosting
forecasting
linear autoregression
mean squarederror
non-linearity
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Kauppi, Heikki
Virtanen, Timo
- Ereignis
-
Veröffentlichung
- (wer)
-
Aboa Centre for Economics (ACE)
- (wo)
-
Turku
- (wann)
-
2018
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:42 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Kauppi, Heikki
- Virtanen, Timo
- Aboa Centre for Economics (ACE)
Entstanden
- 2018
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