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Leading Indicators for Euro-area Inflation and GDP Growth

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Author Info
Anindya Banerjee
Massimiliano Marcellino
Igor Masten

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Abstract

In this paper, we evaluate the role of a set of variables as leading indicators for Euro-area inflation and GDP growth. Our leading indicators are taken from the variables in the European Central Bank's (ECB) Euro-area-wide model database, plus a set of similar variables for the US. We compare the forecasting performance of each indicator "ex post" with that of purely autoregressive models. We also analyse three different approaches to combining the information from several indicators. First, "ex post", we discuss the use as indicators of the estimated factors from a dynamic factor model for all the indicators. Secondly, within an "ex ante" framework, an automated model selection procedure is applied to models with a large set of indicators. No future information is used, future values of the regressors are forecast, and the choice of the indicators is based on their past forecasting records. Finally, we consider the forecasting performance of groups of indicators and factors and methods of pooling the "ex ante" single-indicator or factor-based forecasts. Some sensitivity analyses are also undertaken for different forecasting horizons and weighting schemes of forecasts to assess the robustness of the results. Copyright 2005 Blackwell Publishing Ltd.

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File URL: http://www.blackwell-synergy.com/doi/abs/10.1111/j.1468-0084.2005.00141.x
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Publisher Info
Article provided by Department of Economics, University of Oxford in its journal Oxford Bulletin of Economics & Statistics.

Volume (Year): 67 (2005)
Issue (Month): s1 (December)
Pages: 785-813
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Handle: RePEc:bla:obuest:v:67:y:2005:i:s1:p:785-813

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  1. Marcellino, Massimiliano, 2002. "Forecasting EMU Macroeconomic Variables," CEPR Discussion Papers 3529, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
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  2. Krolzig, Hans-Martin & Hendry, David F., 2001. "Computer automation of general-to-specific model selection procedures," Journal of Economic Dynamics and Control, Elsevier, vol. 25(6-7), pages 831-866, June. [Downloadable!] (restricted)
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  3. Beyer, Andreas & Doornik, Jurgen A & Hendry, David F, 2001. "Constructing Historical Euro-Zone Data," Economic Journal, Royal Economic Society, vol. 111(469), pages F102-21, February. [Downloadable!] (restricted)
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  4. Banerjee, Anindya & Marcellino, Massimiliano & Masten, Igor, 2003. "Leading Indicators for Euro Area Inflation and GDP Growth," CEPR Discussion Papers 3893, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
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  5. M. Hashem Pesaran & Allan Timmermann, 1995. "Predictability of Stock Returns: Robustness and Economic Significance," University of California at San Diego, Economics Working Paper Series 95-19, Department of Economics, UC San Diego.
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  6. Kevin D. Hoover & Stephen J. Perez, 1999. "Data mining reconsidered: encompassing and the general-to-specific approach to specification search," Econometrics Journal, Royal Economic Society, vol. 2(2), pages 167-191.
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  7. James H. Stock & Mark W. Watson, 1998. "Diffusion Indexes," NBER Working Papers 6702, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  8. Anindya BANERJEE & Massimiliano MARCELLINO, 2002. "Are There Any Reliable Leading Indicators for US Inflation and GDP Growth?," Economics Working Papers ECO2002/21, European University Institute. [Downloadable!]
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  9. Michael ARTIS & Anindya BANERJEE & Massimiliano MARCELLINO, 2001. "Factor Forecasts for the UK," Economics Working Papers ECO2001/15, European University Institute. [Downloadable!]
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  10. Stephen G. Cecchetti & Rita S. Chu & Charles Steindel, 2000. "The unreliability of inflation indicators," Current Issues in Economics and Finance, Federal Reserve Bank of New York, issue Apr. [Downloadable!]
  11. Fagan, Gabriel & Henry, Jerome & Mestre, Ricardo, 2005. "An area-wide model for the euro area," Economic Modelling, Elsevier, vol. 22(1), pages 39-59, January. [Downloadable!] (restricted)
  12. Stock, James H. & Watson, Mark W., 1999. "Forecasting inflation," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 293-335, October. [Downloadable!] (restricted)
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  13. Marcellino, Massimiliano, 2002. "Forecast Pooling for Short Time Series of Macroeconomic Variables," CEPR Discussion Papers 3313, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
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  14. David F. Hendry & Michael P. Clements, 2004. "Pooling of forecasts," Econometrics Journal, Royal Economic Society, vol. 7(1), pages 1-31, 06. [Downloadable!] (restricted)
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  15. James H. Stock & Mark W. Watson, 2001. "Forecasting output and inflation: the role of asset prices," Proceedings, Federal Reserve Bank of San Francisco, issue Mar. [Downloadable!]
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  16. Thomas J. Sargent & Christopher A. Sims, 1977. "Business cycle modeling without pretending to have too much a priori economic theory," Working Papers 55, Federal Reserve Bank of Minneapolis. [Downloadable!]
  17. Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2000. "The Generalized Dynamic-Factor Model: Identification And Estimation," The Review of Economics and Statistics, MIT Press, vol. 82(4), pages 540-554, November. [Downloadable!] (restricted)
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  18. Marcellino, Massimiliano & Stock, James H. & Watson, Mark W., 2003. "Macroeconomic forecasting in the Euro area: Country specific versus area-wide information," European Economic Review, Elsevier, vol. 47(1), pages 1-18, February. [Downloadable!] (restricted)
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  19. Gabriel Fagan & Jérôme Henry & Ricardo Mestre, 2001. "An area-wide model (AWM) for the euro area," Working Paper Series 42, European Central Bank. [Downloadable!]
  20. Michael P. Clements & David F. Hendry, 2001. "Forecasting Non-Stationary Economic Time Series," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262531895.
  21. David F. Hendry & Hans-Martin Krolzig, 1999. "Improving on 'Data mining reconsidered' by K.D. Hoover and S.J. Perez," Econometrics Journal, Royal Economic Society, vol. 2(2), pages 202-219.
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