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A Review of Forecasting Techniques for Large Data Sets

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  • Jana Eklund

    ()
    (Bank of England)

  • George Kapetanios

    ()
    (Queen Mary, University of London)

Abstract

This paper provides a review which focuses on forecasting using statistical/econometric methods designed for dealing with large data sets.

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File URL: http://www.econ.qmul.ac.uk/papers/doc/wp625.pdf
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Bibliographic Info

Paper provided by Queen Mary, University of London, School of Economics and Finance in its series Working Papers with number 625.

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Date of creation: Mar 2008
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Handle: RePEc:qmw:qmwecw:wp625

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Related research

Keywords: Macroeconomic forecasting; Factor models; Forecast combination; Principal components;

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References

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  1. Hendry, David F., 1995. "Dynamic Econometrics," OUP Catalogue, Oxford University Press, number 9780198283164, October.
  2. Eklund, Jana & Karlsson, Sune, 2005. "Forecast Combination and Model Averaging using Predictive Measures," Working Paper Series 191, Sveriges Riksbank (Central Bank of Sweden).
  3. Brüggemann, Ralf & Krolzig, Hans-Martin & Lütkepohl, Helmut, 2002. "Comparison of model reduction methods for VAR processes," SFB 373 Discussion Papers 2002,80, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
  4. Banbura, Marta & Giannone, Domenico & Reichlin, Lucrezia, 2007. "Bayesian VARs with Large Panels," CEPR Discussion Papers 6326, C.E.P.R. Discussion Papers.
  5. Andrea Carriero & George Kapetanios & Massimiliano Marcellino, 2007. "Forecasting Large Datasets with Reduced Rank Multivariate Models," Working Papers 617, Queen Mary, University of London, School of Economics and Finance.
  6. George Kapetanios & Vincent Labhard & Simon Price, 2006. "Forecasting using Bayesian and Information Theoretic Model Averaging: An Application to UK Inflation," Working Papers 566, Queen Mary, University of London, School of Economics and Finance.
  7. Christine De Mol & Domenico Giannone & Lucrezia Reichlin, 2008. "Forecasting using a large number of predictors: is Bayesian shrinkage a valid alternative to principal components?," ULB Institutional Repository 2013/6411, ULB -- Universite Libre de Bruxelles.
  8. George Kapetanios & Vincent Labhard & Simon Price, 2006. "Forecasting Using Predictive Likelihood Model Averaging," Working Papers 567, Queen Mary, University of London, School of Economics and Finance.
  9. Marta Bańbura, 2008. "Large Bayesian VARs," 2008 Meeting Papers 334, Society for Economic Dynamics.
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Cited by:
  1. Teresa Buchen & Klaus Wohlrabe, 2013. "Assessing the Macroeconomic Forecasting Performance of Boosting - Evidence for the United States, the Euro Area, and Germany," CESifo Working Paper Series 4148, CESifo Group Munich.
  2. Chudik, Alexander & Pesaran, M. Hashem, 2014. "Theory and practice of GVAR modeling," Globalization and Monetary Policy Institute Working Paper 180, Federal Reserve Bank of Dallas.
  3. Bell, Venetia & Co, Lai Wah & Stone, Sophie & Wallis, gavin`, 2014. "Nowcasting UK GDP growth," Bank of England Quarterly Bulletin, Bank of England, vol. 54(1), pages 58-68.
  4. Liu, Philip & Matheson, Troy & Romeu, Rafael, 2012. "Real-time forecasts of economic activity for Latin American economies," Economic Modelling, Elsevier, vol. 29(4), pages 1090-1098.
  5. Alexander Chudik & Hashem Pesaran, 2014. "Theory and Practice of GVAR Modeling," Cambridge Working Papers in Economics 1408, Faculty of Economics, University of Cambridge.

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