Testing for common autocorrelation in data‐rich environments
AbstractThis paper proposes a strategy to detect the presence of common serial cor- relation in large‐dimensional systems. We show that partial least squares can be used to consistently recover the common autocorrelation space. Moreover, a Monte Carlo study reveals that univariate autocorrelation tests on the factors obtained by partial least squares outperform traditional tests based on canonical correlation analysis. Some empirical applications are presented to illustrate concepts and methods. Copyright (C) 2010 John Wiley & Sons, Ltd.
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Bibliographic InfoArticle provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.
Volume (Year): 30 (2011)
Issue (Month): 3 (April)
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Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966
serial correlation common feature ; high‐dimensional systems ; partial least squares ; reduced‐rank regression ;
Other versions of this item:
- Gianluca Cubadda & Alain Hecq, 2009. "Testing for Common Autocorrelation in Data Rich Environments," CEIS Research Paper 153, Tor Vergata University, CEIS, revised 04 Dec 2009.
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
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- Margaret M. McConnell & Gabriel Perez Quiros, 1997.
"Output fluctuations in the United States: what has changed since the early 1980s?,"
9735, Federal Reserve Bank of New York.
- Margaret McConnell & Gabriel Perez Quiros, 2000. "Output fluctuations in the United States: what has changed since the early 1980s?," Proceedings, Federal Reserve Bank of San Francisco, issue Mar.
- Gabriel Perez-Quiros & Margaret M. McConnell, 2000. "Output Fluctuations in the United States: What Has Changed since the Early 1980's?," American Economic Review, American Economic Association, vol. 90(5), pages 1464-1476, December.
- Margaret M. McConnell & Gabriel Perez Quiros, 1998. "Output fluctuations in the United States: what has changed since the early 1980s?," Staff Reports 41, Federal Reserve Bank of New York.
- Jan J. J. Groen & George Kapetanios, 2008.
"Revisiting useful approaches to data-rich macroeconomic forecasting,"
327, Federal Reserve Bank of New York.
- Jan J.J. Groen & George Kapetanios, 2008. "Revisiting Useful Approaches to Data-Rich Macroeconomic Forecasting," Working Papers 624, Queen Mary, University of London, School of Economics and Finance.
- Croushore, Dean & Stark, Tom, 2001.
"A real-time data set for macroeconomists,"
Journal of Econometrics,
Elsevier, vol. 105(1), pages 111-130, November.
- Cubadda, Gianluca & Hecq, Alain & Palm, Franz C., 2009.
"Studying co-movements in large multivariate data prior to multivariate modelling,"
Journal of Econometrics,
Elsevier, vol. 148(1), pages 25-35, January.
- Gianluca Cubadda & Alain Hecq & Franz C. Palm, 2008. "Studying Co-Movements in Large Multivariate Data Prior to Multivariate Modelling," CEIS Research Paper 125, Tor Vergata University, CEIS, revised 14 Jul 2008.
- Marco Centoni & Gianluca Cubadda, 2011.
"Modelling comovements of economic time series: a selective survey,"
Department of Statistics, University of Bologna, vol. 71(2), pages 267-294.
- Marco Centoni & Gianluca Cubadda, 2011. "Modelling Comovements of Economic Time Series: A Selective Survey," CEIS Research Paper 215, Tor Vergata University, CEIS, revised 26 Oct 2011.
- Gianluca Cubadda & Barbara Guardabascio, 2010.
"A Medium-N Approach to Macroeconomic Forecasting,"
CEIS Research Paper
176, Tor Vergata University, CEIS, revised 09 Dec 2010.
- Cubadda, Gianluca & Guardabascio, Barbara & Hecq, Alain, 2013.
"A general to specific approach for constructing composite business cycle indicators,"
Elsevier, vol. 33(C), pages 367-374.
- Gianluca Cubadda & Barbara Guardabascio & Alain Hecq, 2012. "A General to Specific Approach for Constructing Composite Business Cycle Indicators," CEIS Research Paper 224, Tor Vergata University, CEIS, revised 27 Feb 2012.
- Hecq Alain & Laurent Sébastien & Palm Franz C., 2012. "On the Univariate Representation of BEKK Models with Common Factors," Research Memorandum 018, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
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