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

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

Abstract

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.

Suggested Citation

  • Lee, Kevin & Olekalns, Nils & Shields, Kalvinder, 2009. "Nowcasting, Business Cycle Dating and the Interpretation of New Information when Real-Time Data are Available," CEPR Discussion Papers 7426, C.E.P.R. Discussion Papers.
  • Handle: RePEc:cpr:ceprdp:7426
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    1. Evan F. Koenig & Sheila Dolmas & Jeremy Piger, 2003. "The Use and Abuse of Real-Time Data in Economic Forecasting," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 618-628, August.
    2. Giannone, Domenico & Reichlin, Lucrezia & Small, David, 2008. "Nowcasting: The real-time informational content of macroeconomic data," Journal of Monetary Economics, Elsevier, vol. 55(4), pages 665-676, May.
    3. 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.
    4. Clark, Todd E. & McCracken, Michael W., 2001. "Tests of equal forecast accuracy and encompassing for nested models," Journal of Econometrics, Elsevier, vol. 105(1), pages 85-110, November.
    5. Pesaran, M. Hashem & Weale, Martin, 2006. "Survey Expectations," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 14, pages 715-776, Elsevier.
    6. Christiano, Lawrence J. & Eichenbaum, Martin & Evans, Charles L., 1999. "Monetary policy shocks: What have we learned and to what end?," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 2, pages 65-148, Elsevier.
    7. Croushore, Dean & Evans, Charles L., 2006. "Data revisions and the identification of monetary policy shocks," Journal of Monetary Economics, Elsevier, vol. 53(6), pages 1135-1160, September.
    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.
    9. Michael D. Bordo & Joseph G. Haubrich, 2008. "The Yield Curve as a Predictor of Growth: Long-Run Evidence, 1875-1997," The Review of Economics and Statistics, MIT Press, vol. 90(1), pages 182-185, February.
    10. 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, April.
    11. N. Kundan Kishor & Evan F. Koenig, 2009. "VAR Estimation and Forecasting When Data Are Subject to Revision," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(2), pages 181-190, July.
    12. 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.
    13. 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.
    14. Domenico Giannone & Lucrezia Reichlin & David H. Small, 2005. "Nowcasting GDP and inflation: the real-time informational content of macroeconomic data releases," Finance and Economics Discussion Series 2005-42, Board of Governors of the Federal Reserve System (U.S.).
    15. 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.
    16. Dean Croushore, 2011. "Frontiers of Real-Time Data Analysis," Journal of Economic Literature, American Economic Association, vol. 49(1), pages 72-100, March.
    17. 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.
    18. John B. Taylor, 1999. "Monetary Policy Rules," NBER Books, National Bureau of Economic Research, Inc, number tayl99-1.
    19. Garratt A. & Lee K. & Pesaran M.H. & Shin Y., 2003. "Forecast Uncertainties in Macroeconomic Modeling: An Application to the U.K. Economy," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 829-838, January.
    20. G. Elliott & C. Granger & A. Timmermann (ed.), 2006. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 1, number 1.
    21. 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 254-279, May.
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    Cited by:

    1. Lee, Kevin & Shields, Kalvinder K., 2011. "Decision-making in hard times: What is a recession, why do we care and how do we know when we are in one?," The North American Journal of Economics and Finance, Elsevier, vol. 22(1), pages 43-60, January.
    2. Kirdan Lees, 2009. "Overview of a recent Reserve Bank workshop: nowcasting with model combination," Reserve Bank of New Zealand Bulletin, Reserve Bank of New Zealand, vol. 72, pages 31-33, March.
    3. Jennifer L. Castle & David F. Hendry, 2010. "Nowcasting from disaggregates in the face of location shifts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 200-214.
    4. Kevin Lee & James Morley & Kalvinder Shields, 2015. "The Meta Taylor Rule," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 47(1), pages 73-98, February.
    5. Jennifer Castle & David Hendry & Oleg Kitov, 2013. "Forecasting and Nowcasting Macroeconomic Variables: A Methodological Overview," Economics Series Working Papers 674, University of Oxford, Department of Economics.

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    More about this item

    Keywords

    Structural modelling; Real-time data; Nowcasting; Business cycles;
    All these keywords.

    JEL classification:

    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies

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