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Forecasting with Factor-Augmented Regression: A Frequentist Model Averaging Approach, Second Version
Cheng, Xu; Hansen, Bruce E. - Department of Economics, University of Pennsylvania - 2012
across models using weights that minimize the Mallows and the leave-h-out cross validation criteria. The unobserved factor … regressors, we show that the Mallows and leave-h-out cross validation criteria are asymptotically unbiased estimators of the one … and T. Simulations show that the Mallows model averaging and leave-h-out cross-validation averaging methods yield lower …
Persistent link: https://www.econbiz.de/10010822931
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Forecasting with factor-augmented regression : a frequentist model averaging approach
Cheng, Xu; Hansen, Bruce E. - In: Journal of econometrics 186 (2015) 2, pp. 280-293
Persistent link: https://www.econbiz.de/10011349480
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Forecasting GDP at the regional level with many predictors
Lehmann, Robert; Wohlrabe, Klaus - 2013
In this paper, we assess the accuracy of macroeconomic forecasts at the regional level using a large data set at quarterly frequency. We forecast gross domestic product (GDP) for two German states (Free State of Saxony and Baden- Württemberg) and Eastern Germany. We overcome the problem of a...
Persistent link: https://www.econbiz.de/10010427667
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Forecasting GDP at the regional level with many predictors
Lehmann, Robert; Wohlrabe, Klaus - 2013
In this paper, we assess the accuracy of macroeconomic forecasts at the regional level using a large data set at quarterly frequency. We forecast gross domestic product (GDP) for two German states (Free State of Saxony and Baden- Württemberg) and Eastern Germany. We overcome the problem of a...
Persistent link: https://www.econbiz.de/10010350218
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Forecasting gross value-added at the regional level : are sectoral disaggregated predictions superior to direct ones?
Lehmann, Robert; Wohlrabe, Klaus - 2013
In this paper, we ask whether it is possible to forecast gross value-added (GVA) and its sectoral subcomponents at the regional level. With an autoregressive distributed lag model we forecast total and sectoral GVA for one German state (Saxony) with more than 300 indicators from different...
Persistent link: https://www.econbiz.de/10010213032
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Forecasting gross value-added at the regional level: Are sectoral disaggregated predictions superior to direct ones?
Lehmann, Robert; Wohlrabe, Klaus - ifo Leibniz-Institut für Wirtschaftsforschung an der … - 2013
In this paper, we ask whether it is possible to forecast gross value-added (GVA) and its sectoral subcomponents at the regional level. With an autoregressive distributed lagmodel we forecast total and sectoral GVA for one German state (Saxony) with more than 300 indicators from different...
Persistent link: https://www.econbiz.de/10010877592
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Forecasting GDP at the regional level with many predictors
Lehmann, Robert; Wohlrabe, Klaus - Volkswirtschaftliche Fakultät, … - 2013
In this paper, we assess the accuracy of macroeconomic forecasts at the regional level using a large data set at quarterly frequency. We forecast gross domestic product (GDP) for two German states (Free State of Saxony and Baden- Württemberg) and Eastern Germany. We overcome the problem of a...
Persistent link: https://www.econbiz.de/10011210889
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Uncertainty and heterogeneity in factor models forecasting
Luciani, Matteo; Monteforte, Libero - Banca d'Italia - 2013
In this paper, we exploit the heterogeneity in the forecasts obtained by estimating different factor models to measure forecast uncertainty. Our approach is simple and intuitive. It consists first in selecting all the models that outperform some benchmark model, and then in constructing an...
Persistent link: https://www.econbiz.de/10011099661
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Uncertainty and Heterogeneity in factor models forecasting
Luciani, Matteo; Monteforte, Libero - Dipartimento del Tesoro, Ministero dell'Economia e … - 2012
In this paper we propose to exploit the heterogeneity of forecasts produced by different model specifications to measure forecast uncertainty. Our approach is simple and intuitive. It consists in selecting all the models that outperform some benchmark model, and then to construct an empirical...
Persistent link: https://www.econbiz.de/10010559817
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How Useful is Bagging in Forecasting Economic Time Series? A Case Study of US CPI Inflation
Inoue, Atsushi; Kilian, Lutz - C.E.P.R. Discussion Papers - 2005
This paper explores the usefulness of bagging methods in forecasting economic time series from linear multiple regression models. We focus on the widely studied question of whether the inclusion of indicators of real economic activity lowers the prediction mean-squared error of forecast models...
Persistent link: https://www.econbiz.de/10005661494