Konferenzbeitrag

Forecasting German key macroeconomic variables using large dataset methods

We study the forecasting performance of three alternative large scale approaches for German key macroeconomic variables using a dataset that consists of 123 variables in quarterly frequency. These three approaches handle the dimensionality problem evoked by such a large dataset by aggregating information, yet on different levels. We consider different factor models, a large Bayesian VAR and model averaging techniques, where aggregation takes place before, during and after the estimation of the different models, respectively. We find that overall the large Bayesian VAR provides the most precise forecasts compared to the other large scale approaches and a number of small benchmark models. For some variables the large Bayesian VAR is also the only model producing unbiased forecasts at least for short horizons. While a Bayesian factor augmented VAR with a tight prior also provides quite accurate forecasts overall, the performance of the other methods depends on the variable to be forecast.

Sprache
Englisch

Erschienen in
Series: Beiträge zur Jahrestagung des Vereins für Socialpolitik 2014: Evidenzbasierte Wirtschaftspolitik - Session: Forecasting ; No. B16-V4

Klassifikation
Wirtschaft
Forecasting Models; Simulation Methods
Prices, Business Fluctuations, and Cycles: Forecasting and Simulation: Models and Applications
Money and Interest Rates: Forecasting and Simulation: Models and Applications

Ereignis
Geistige Schöpfung
(wer)
Pirschel, Inske
Wolters, Maik
Ereignis
Veröffentlichung
(wer)
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften, Leibniz-Informationszentrum Wirtschaft
(wo)
Kiel und Hamburg
(wann)
2014

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.

Objekttyp

  • Konferenzbeitrag

Beteiligte

  • Pirschel, Inske
  • Wolters, Maik
  • ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften, Leibniz-Informationszentrum Wirtschaft

Entstanden

  • 2014

Ähnliche Objekte (12)