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Dynamic Hierarchical Factor Model

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  • Emanuel Moench

    (Federal Reserve Bank of New York)

  • Serena Ng

    (Columbia University)

  • Simon Potter

    (Federal Reserve Bank of New York)

Abstract

This paper uses multilevel factor models to characterize within- and between-block variations as well as idiosyncratic noise in large dynamic panels. Block-level shocks are distinguished from genuinely common shocks, and the estimated block-level factors are easy to interpret. The framework achieves dimension reduction and yet explicitly allows for heterogeneity between blocks. The model is estimated using an MCMC algorithm that takes into account the hierarchical structure of the factors. The importance of block-level variations is illustrated in a four-level model estimated on a panel of 445 series related to different categories of real activity in the United States. © 2013 The President and Fellows of Harvard College and the Massachusetts Institute of Technology.

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Bibliographic Info

Article provided by MIT Press in its journal Review of Economics and Statistics.

Volume (Year): 95 (2013)
Issue (Month): 5 (December)
Pages: 1811-1817

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Handle: RePEc:tpr:restat:v:95:y:2013:i:5:p:1811-1817

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Related research

Keywords: diffusion index forecasting; monitoring; large dimensional panel;

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Cited by:
  1. Gary Koop & Dimitris Korompilis, 2009. "UK Macroeconomic Forecasting with Many Predictors: Which Models Forecast Best and When Do They Do So?," Working Papers, University of Strathclyde Business School, Department of Economics 0917, University of Strathclyde Business School, Department of Economics.
  2. Nagayasu, Jun, 2013. "Interdependence in Real Effective Exchange Rates: Evidence from the Dynamic Hierarchical Factor Model," MPRA Paper 45955, University Library of Munich, Germany.
  3. Hallin, Marc & Liska, Roman, 2011. "Dynamic factors in the presence of blocks," Journal of Econometrics, Elsevier, Elsevier, vol. 163(1), pages 29-41, July.
  4. Bai, Jushan & Wang, Peng, 2012. "Identification and estimation of dynamic factor models," MPRA Paper 38434, University Library of Munich, Germany.
  5. Beck, Guenter W. & Hubrich, Kirstin & Marcellino, Massimiliano, 2012. "On the importance of sectoral and regional shocks for price setting," IMFS Working Paper Series, Institute for Monetary and Financial Stability (IMFS), Goethe University Frankfurt 63, Institute for Monetary and Financial Stability (IMFS), Goethe University Frankfurt.
  6. Georges Bresson & Jean-Michel Etienne & Pierre Mohnen, 2011. "How important is innovation? A Bayesian factor-augmented productivity model on panel data," Working Papers, HAL halshs-00812155, HAL.
  7. Beck, Guenter W. & Hubrich, Kirstin & Marcellino, Massimiliano, 2009. "On the importance of sectoral shocks for price-setting," CFS Working Paper Series, Center for Financial Studies (CFS) 2009/32, Center for Financial Studies (CFS).
  8. Neville Francis & Michael T. Owyang & Özge Savascin, 2012. "An endogenously clustered factor approach to international business cycles," Working Papers, Federal Reserve Bank of St. Louis 2012-014, Federal Reserve Bank of St. Louis.
  9. Elena Andreou & Eric Ghysels & Andros Kourtellos, 2010. "Should Macroeconomic Forecasters Use Daily Financial Data and How?," Working Paper Series, The Rimini Centre for Economic Analysis 42_10, The Rimini Centre for Economic Analysis.
  10. Neville Francis, 2012. "The Low-Frequency Impact of Daily Monetary Policy Shock," 2012 Meeting Papers, Society for Economic Dynamics 198, Society for Economic Dynamics.
  11. Castle, Jennifer L. & Clements, Michael P. & Hendry, David F., 2013. "Forecasting by factors, by variables, by both or neither?," Journal of Econometrics, Elsevier, Elsevier, vol. 177(2), pages 305-319.
  12. Michael Kirker, 2010. "What drives core inflation? A dynamic factor model analysis of tradable and nontradable prices," Reserve Bank of New Zealand Discussion Paper Series DP2010/13, Reserve Bank of New Zealand.
  13. Neville Francis & Eric Ghysels & Michael T. Owyang, 2011. "The low-frequency impact of daily monetary policy shocks," Working Papers, Federal Reserve Bank of St. Louis 2011-009, Federal Reserve Bank of St. Louis.

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