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Nowcasting, Business Cycle Dating and the Interpretation of New Information when Real-Time Data are Available

  • Lee, Kevin
  • Olekalns, Nils
  • Shields, Kalvinder K

A canonical model is described which reflects the real-time informational context of decision-making. Comparisons are drawn with ‘conventional’ models that incorrectly omit market-informed insights on future macroeconomic conditions and inappropriately incorporate information that was not available at the time. It is argued that conventional models are misspecified and misinterpret news but that these deficiencies will not be exposed either by diagnostic tests applied to the conventional models or by typical impulse response analyses. This is demonstrated through an analysis of quarterly US data 1968q4-2008q4. However, estimated real-time models considerably improve out-ofsample forecasting performance, provide more accurate ‘nowcasts’ of the current state of the macroeconomy and provide more timely indicators of the business cycle. The point is illustrated through an analysis of the US recessions of 1990q3-1991q2 and 2001q1-2001q4 and the most recent experiences of 2008.

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Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 7426.

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Date of creation: Sep 2009
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Handle: RePEc:cpr:ceprdp:7426
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  1. Evan F. Koenig & Sheila Dolmas & Jeremy Piger, 2000. "The use and abuse of "real-time" data in economic forecasting," International Finance Discussion Papers 684, Board of Governors of the Federal Reserve System (U.S.).
  2. M. Hashem Pesaran & Martin Weale, 2005. "Survey Expectations," IEPR Working Papers 05.30, Institute of Economic Policy Research (IEPR).
  3. Giannone, Domenico & Reichlin, Lucrezia & Small, David, 2005. "Nowcasting GDP and Inflation: The Real Time Informational Content of Macroeconomic Data Releases," CEPR Discussion Papers 5178, C.E.P.R. Discussion Papers.
  4. Todd E. Clark & Michael W. McCracken, 1999. "Tests of equal forecast accuracy and encompassing for nested models," Research Working Paper 99-11, Federal Reserve Bank of Kansas City.
  5. Jacobs, Jan P.A.M. & van Norden, Simon, 2011. "Modeling data revisions: Measurement error and dynamics of "true" values," Journal of Econometrics, Elsevier, vol. 161(2), pages 101-109, April.
  6. Athanasios Orphanides & Simon van Norden, 2002. "The Unreliability of Output-Gap Estimates in Real Time," The Review of Economics and Statistics, MIT Press, vol. 84(4), pages 569-583, November.
  7. Anthony Garratt & Kevin Lee & M. Hashem Pesaran & Yongcheol Shin, 2003. "A Long run structural macroeconometric model of the UK," Economic Journal, Royal Economic Society, vol. 113(487), pages 412-455, 04.
  8. Garratt, Anthony & Lee, Kevin & Pesaran, M. Hashem & Shin, Yongcheol, 2012. "Global and National Macroeconometric Modelling: A Long-Run Structural Approach," OUP Catalogue, Oxford University Press, number 9780199650460, March.
  9. Ang, Andrew & Bekaert, Geert & Wei, Min, 2007. "Do macro variables, asset markets, or surveys forecast inflation better?," Journal of Monetary Economics, Elsevier, vol. 54(4), pages 1163-1212, May.
  10. Anthony Garratt & Kevin Lee & Emi Mise & Kalvinder Shields, 2008. "Real-Time Representations of the Output Gap," The Review of Economics and Statistics, MIT Press, vol. 90(4), pages 792-804, November.
  11. A Garratt & K Lee & M H Pesaran & Yongcheol Shin, 2004. "Forecast Uncertainties in Macroeconomics Modelling: An Application to the UK Economy," ESE Discussion Papers 64, Edinburgh School of Economics, University of Edinburgh.
  12. N. Kundan Kishor & Evan F. Koenig, 2005. "VAR estimation and forecasting when data are subject to revision," Working Papers 0501, Federal Reserve Bank of Dallas.
  13. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
  14. Brunner, Allan D, 2000. "On the Derivation of Monetary Policy Shocks: Should We Throw the VAR Out with the Bath Water?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 32(2), pages 254-79, May.
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