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A daily indicator of economic growth for the euro area

A daily indicator of economic growth for the euro area In this paper, we study alternative methods to construct a daily indicator of growth for the euro area. We aim for an indicator that (i) provides reliable predictions, (ii) can be easily updated at the daily frequency, (iii) gives interpretable signals, and (iv) it is linear. Using a large panel of daily and monthly data for the euro area we explore the performance of two classes of models: bridge and U-MIDAS models, and different forecast combination strategies. Forecasts obtained from U-MIDAS models, combined with the inverse MSE weights, best satisfy the required criteria. Keywords: nowcasting; mixed-frequency data. Copyright © 2017 Inderscience Enterprises Ltd. V. Aprigliano et al. Reference to this paper should be made as follows: Aprigliano, V., Foroni, C., Marcellino, M., Mazzi, G. and Venditti, F. (2017) `A daily indicator of economic growth for the euro area', Int. J. Computational Economics and Econometrics, Vol. 7, Nos. 1/2, pp.43­63. Biographical notes: Valentina Aprigliano is an Economist at the Economic Outlook and Monetary Policy Directorate of the Bank of Italy. She joined the Central Bank in 2012, and she has been dealing with short-term forecasting of the economic activity in the euro area and its major countries, ever since. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Computational Economics and Econometrics Inderscience Publishers

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Publisher
Inderscience Publishers
Copyright
Copyright © 2017 Inderscience Enterprises Ltd.
ISSN
1757-1170
eISSN
1757-1189
DOI
10.1504/IJCEE.2017.080636
Publisher site
See Article on Publisher Site

Abstract

In this paper, we study alternative methods to construct a daily indicator of growth for the euro area. We aim for an indicator that (i) provides reliable predictions, (ii) can be easily updated at the daily frequency, (iii) gives interpretable signals, and (iv) it is linear. Using a large panel of daily and monthly data for the euro area we explore the performance of two classes of models: bridge and U-MIDAS models, and different forecast combination strategies. Forecasts obtained from U-MIDAS models, combined with the inverse MSE weights, best satisfy the required criteria. Keywords: nowcasting; mixed-frequency data. Copyright © 2017 Inderscience Enterprises Ltd. V. Aprigliano et al. Reference to this paper should be made as follows: Aprigliano, V., Foroni, C., Marcellino, M., Mazzi, G. and Venditti, F. (2017) `A daily indicator of economic growth for the euro area', Int. J. Computational Economics and Econometrics, Vol. 7, Nos. 1/2, pp.43­63. Biographical notes: Valentina Aprigliano is an Economist at the Economic Outlook and Monetary Policy Directorate of the Bank of Italy. She joined the Central Bank in 2012, and she has been dealing with short-term forecasting of the economic activity in the euro area and its major countries, ever since.

Journal

International Journal of Computational Economics and EconometricsInderscience Publishers

Published: Jan 1, 2017

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