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Bayesian forecasting with highly correlated predictors

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  • Dimitris Korobilis

Abstract

This paper considers Bayesian variable selection in regressions with a large number of possibly highly correlated macroeconomic predictors. I show that by acknowledging the correlation structure in the predictors can improve forecasts over existing popular Bayesian variable selection algorithms.

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File URL: http://www.gla.ac.uk/media/media_241548_en.pdf
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Bibliographic Info

Paper provided by Business School - Economics, University of Glasgow in its series Working Papers with number 2012_12.

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Date of creation: Jul 2012
Date of revision:
Handle: RePEc:gla:glaewp:2012_12

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Keywords: Bayesian semiparametric selection; Dirichlet process prior; correlated predictors; clustered coefficients;

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References

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  1. Korobilis, Dimitris, 2009. "VAR forecasting using Bayesian variable selection," MPRA Paper 21124, University Library of Munich, Germany.
  2. James H. Stock & Mark W. Watson, 1999. "Forecasting Inflation," NBER Working Papers 7023, National Bureau of Economic Research, Inc.
  3. Carmen Fernandez & E Ley & Mark F J Steel, 2004. "Benchmark priors for Bayesian models averaging," ESE Discussion Papers 66, Edinburgh School of Economics, University of Edinburgh.
  4. K. J. Martijn Cremers, 2002. "Stock Return Predictability: A Bayesian Model Selection Perspective," Review of Financial Studies, Society for Financial Studies, vol. 15(4), pages 1223-1249.
  5. Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-62, April.
  6. Gary Koop & Dimitris Korobilis, 2012. "Forecasting Inflation Using Dynamic Model Averaging," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 53(3), pages 867-886, 08.
  7. Jonathan H. Wright, 2003. "Bayesian Model Averaging and exchange rate forecasts," International Finance Discussion Papers 779, Board of Governors of the Federal Reserve System (U.S.).
  8. George, Edward I. & Sun, Dongchu & Ni, Shawn, 2008. "Bayesian stochastic search for VAR model restrictions," Journal of Econometrics, Elsevier, vol. 142(1), pages 553-580, January.
  9. Gary Koop & Simon Potter, 2004. "Forecasting in dynamic factor models using Bayesian model averaging," Econometrics Journal, Royal Economic Society, vol. 7(2), pages 550-565, December.
  10. Dunson, David B. & Herring, Amy H. & Engel, Stephanie M., 2008. "Bayesian Selection and Clustering of Polymorphisms in Functionally Related Genes," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 534-546, June.
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Citations

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Cited by:
  1. Gary, Koop, 2013. "Using VARs and TVP-VARs with Many Macroeconomic Variables," SIRE Discussion Papers 2013-35, Scottish Institute for Research in Economics (SIRE).
  2. Goodness C. Aye & Rangan Gupta & Stephen M. Miller & Mehmet Balcilar, 2014. "Forecasting US Real Private Residential Fixed Investment Using a Large Number of Predictors," Working papers 2014-10, University of Connecticut, Department of Economics.
  3. Korobilis, Dimitris, 2014. "Data-based priors for vector autoregressions with drifting coefficients," MPRA Paper 53772, University Library of Munich, Germany.
  4. Nombulelo Gumata, Alain Kabundi and Eliphas Ndou, 2013. "Important Channels of Transmission Monetary Policy Shock in South Africa," Working Papers 375, Economic Research Southern Africa.
  5. Goodness C. Aye & Stephen M. Miller & Rangan Gupta & Mehmet Balcilar, 2013. "Forecasting the US Real Private Residential Fixed Investment Using Large Number of Predictors," Working Papers 201348, University of Pretoria, Department of Economics.
  6. Dimitris, Korobilis, 2013. "Forecasting with Factor Models: A Bayesian Model Averaging Perspective," MPRA Paper 52724, University Library of Munich, Germany.

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