Arbeitspapier
A review of forecasting techniques for large data sets
This paper provides a review which focuses on forecasting using statistical/econometric methods designed for dealing with large data sets.
- Language
-
Englisch
- Bibliographic citation
-
Series: Working Paper ; No. 625
- Classification
-
Wirtschaft
Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
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
- Subject
-
Macroeconomic forecasting
Factor models
Forecast combination
Principal components
Prognoseverfahren
- Event
-
Geistige Schöpfung
- (who)
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Eklund, Jana
Kapetanios, George
- Event
-
Veröffentlichung
- (who)
-
Queen Mary University of London, Department of Economics
- (where)
-
London
- (when)
-
2008
- Handle
- Last update
- 10.03.2025, 11:42 AM CET
Data provider
This object is provided by:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Eklund, Jana
- Kapetanios, George
- Queen Mary University of London, Department of Economics
Time of origin
- 2008
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Forecasting with measurement errors in dynamic models
Revisiting useful approaches to data-rich macroeconomic forecasting
Choosing the optimal set of instruments from large instrument sets
Factor analysis using subspace factor models: Some theoretical results and an application to UK inflation forecasting
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Factor-GMM estimation with large sets of possibly weak instruments
A new method for determining the number of factors in factor models with large datasets
A testing procedure for determining the number of factors in approximate factor models with large datasets
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Forecasting government bond yields with large Bayesian VARs
Forecasting large datasets with reduced rank multivariate models
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