Google data in bridge equation models for German GDP
Year of publication: |
2019
|
---|---|
Authors: | Götz, Thomas B. ; Knetsch, Thomas A. |
Published in: |
International journal of forecasting. - Amsterdam [u.a.] : Elsevier, ISSN 0169-2070, ZDB-ID 283943-X. - Vol. 35.2019, 1, p. 45-66
|
Subject: | Big data | Boosting | Bridge equation models | Forecasting | LASSO | Partial least squares | Principal components analysis | Deutschland | Germany | Prognoseverfahren | Forecasting model | Big Data | Kleinste-Quadrate-Methode | Least squares method | Statistische Methode | Statistical method | Partielle kleinste Quadrate | Schätztheorie | Estimation theory | Schätzung | Estimation |
Type of publication: | Article |
---|---|
Type of publication (narrower categories): | Aufsatz in Zeitschrift ; Article in journal |
Language: | English |
Notes: | Erratum enthalten in: International journal of forecasting, Volume 37, issue 3 (July/September 2021), Seite 1314-1315 |
Other identifiers: | 10.1016/j.ijforecast.2018.08.001 [DOI] |
Source: | ECONIS - Online Catalogue of the ZBW |
-
Google data in bridge equation models for German GDP
Götz, Thomas B., (2017)
-
Google data in bridge equation models for German GDP
Götz, Thomas B., (2017)
-
Forecasting net charge-off rates of banks : what model works best?
Barth, James R., (2018)
- More ...
-
Google data in bridge equation models for German GDP
Götz, Thomas B., (2017)
-
Google data in bridge equation models for German GDP
Götz, Thomas B., (2017)
-
Testing for Granger causality in large mixed-frequency VARs
Götz, Thomas B., (2015)
- More ...