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Real-Time Nowcasting Nominal GDP Under Structural Break

  • Barnett, William A.
  • Chauvet, Marcelle
  • Leiva-Leon, Danilo

This paper provides early assessments of current U.S. Nominal GDP growth, which has been considered as a potential new monetary policy target. The nowcasts are computed using the exact amount of information that policy makers have available at the time predictions are made. However, real time information arrives at different frequencies and asynchronously, which poses the challenge of mixed frequencies, missing data, and ragged edges. This paper proposes a multivariate state space model that not only takes into account asynchronous information inflow it also allows for potential parameter instability. We use small scale confirmatory factor analysis in which the candidate variables are selected based on their ability to forecast GDP nominal. The model is fully estimated in one step using a nonlinear Kalman filter, which is applied to obtain simultaneously both optimal inferences on the dynamic factor and parameters. Differently from principal component analysis, the proposed factor model captures the comovement rather than the variance underlying the variables. We compare the predictive ability of the model with other univariate and multivariate specifications. The results indicate that the proposed model containing information on real economic activity, inflation, interest rates, and Divisia monetary aggregates produces the most accurate real time nowcasts of nominal GDP growth.

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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 53699.

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Date of creation: 14 Feb 2014
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Handle: RePEc:pra:mprapa:53699
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  1. Elena Angelini & Gonzalo Camba‐Mendez & Domenico Giannone & Lucrezia Reichlin & Gerhard Rünstler, 2011. "Short‐term forecasts of euro area GDP growth," Econometrics Journal, Royal Economic Society, vol. 14(1), pages C25-C44, February.
  2. Domenico Giannone & Lucrezia Reichlin & David 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.).
  3. Camacho, Maximo & Pérez-Quirós, Gabriel, 2009. "Introducing the Euro-STING: Short-Term Indicator of Euro Area Growth," CEPR Discussion Papers 7343, C.E.P.R. Discussion Papers.
  4. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-44, January.
  5. Stock, J.H. & Watson, M.W., 1989. "New Indexes Of Coincident And Leading Economic Indicators," Papers 178d, Harvard - J.F. Kennedy School of Government.
  6. Kuzin, Vladimir & Marcellino, Massimiliano & Schumacher, Christian, 2009. "MIDAS vs. mixed-frequency VAR: Nowcasting GDP in the Euro Area," CEPR Discussion Papers 7445, C.E.P.R. Discussion Papers.
  7. S. Boragan Aruoba & Francis X. Diebold & Chiara Scotti, 2008. "Real-Time Measurement of Business Conditions," NBER Working Papers 14349, National Bureau of Economic Research, Inc.
  8. Doz, Catherine & Giannone, Domenico & Reichlin, Lucrezia, 2006. "A quasi maximum likelihood approach for large approximate dynamic factor models," Working Paper Series 0674, European Central Bank.
  9. Jean Boivin & Serena Ng, 2003. "Are More Data Always Better for Factor Analysis?," NBER Working Papers 9829, National Bureau of Economic Research, Inc.
  10. Chang-Jin Kim & Charles R. Nelson, 1999. "Has The U.S. Economy Become More Stable? A Bayesian Approach Based On A Markov-Switching Model Of The Business Cycle," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 608-616, November.
  11. Chauvet, Marcelle & Potter, Simon, 2001. "Recent Changes in the US Business Cycle," Manchester School, University of Manchester, vol. 69(5), pages 481-508, Special I.
  12. Margaret McConnell & Gabriel Perez Quiros, 2000. "Output fluctuations in the United States: what has changed since the early 1980s?," Proceedings, Federal Reserve Bank of San Francisco, issue Mar.
  13. Kim, Chang-Jin, 1994. "Dynamic linear models with Markov-switching," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 1-22.
  14. Marcelle Chauvet & Jeremy M. Piger, 2005. "A comparison of the real-time performance of business cycle dating methods," Working Papers 2005-021, Federal Reserve Bank of St. Louis.
  15. Tom Stark & Dean Croushore, 2001. "Forecasting with a real-time data set for macroeconomists," Working Papers 01-10, Federal Reserve Bank of Philadelphia.
  16. Leiva-Leon, Danilo, 2013. "Real vs. Nominal Cycles: A Multistate Markov-Switching Bi-Factor Approach," MPRA Paper 54456, University Library of Munich, Germany.
  17. Máximo Camacho & Jaime Martínez-Martín, 2014. "Real-time forecasting us GDP from small-scale factor models," Banco de Espa�a Working Papers 1425, Banco de Espa�a.
  18. Martin D. D. Evans, 2005. "Where Are We Now? Real-Time Estimates of the Macroeconomy," International Journal of Central Banking, International Journal of Central Banking, vol. 1(2), September.
  19. Barnett, William A., 2012. "Getting it Wrong: How Faulty Monetary Statistics Undermine the Fed, the Financial System, and the Economy," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262016915, June.
  20. Tommaso Proietti & Filippo Moauro, 2004. "Dynamic Factor Analysis with Nonlinear Temporal Aggregation Constraints," Econometrics 0401003, EconWPA.
  21. Bańbura, Marta & Giannone, Domenico & Modugno, Michele & Reichlin, Lucrezia, 2013. "Now-casting and the real-time data flow," Working Paper Series 1564, European Central Bank.
  22. Götz T.B. & Hecq A.W., 2013. "Nowcasting causality in mixed frequency vector autoregressive models," Research Memorandum 050, Maastricht University, Graduate School of Business and Economics (GSBE).
  23. Marta Bańbura & Michele Modugno, 2014. "Maximum Likelihood Estimation Of Factor Models On Datasets With Arbitrary Pattern Of Missing Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(1), pages 133-160, 01.
  24. William Barnett & Jia Liu & Ryan Mattson & Jeff van den Noort, 2012. "The New CFS Divisia Monetary Aggregates: Design, Construction, and Data Sources," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201208, University of Kansas, Department of Economics, revised May 2012.
  25. Dean Croushore & Tom Stark, 1999. "A real-time data set for macroeconomists," Working Papers 99-4, Federal Reserve Bank of Philadelphia.
  26. Domenico Giannone & Lucrezia Reichlin & David Small, 2008. "Nowcasting: the real time informational content of macroeconomic data releases," ULB Institutional Repository 2013/6409, ULB -- Universite Libre de Bruxelles.
  27. 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.
  28. Alvarez, Rocio & Camacho, Maximo & Pérez-Quirós, Gabriel, 2012. "Finite sample performance of small versus large scale dynamic factor models," CEPR Discussion Papers 8867, C.E.P.R. Discussion Papers.
  29. Michael T. Belongia & Peter N. Ireland, 2012. "A "Working" Solution to the Question of Nominal GDP Targeting," Boston College Working Papers in Economics 802, Boston College Department of Economics, revised 04 Jan 2013.
  30. Frank Schorfheide & Dongho Song, 2012. "Real-time forecasting with a mixed-frequency VAR," Working Papers 701, Federal Reserve Bank of Minneapolis.
  31. Marcelle Chauvet & James D. Hamilton, 2005. "Dating Business Cycle Turning Points," NBER Working Papers 11422, National Bureau of Economic Research, Inc.
  32. Roberto S. Mariano & Yasutomo Murasawa, 2003. "A new coincident index of business cycles based on monthly and quarterly series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(4), pages 427-443.
  33. Chib, Siddhartha, 1998. "Estimation and comparison of multiple change-point models," Journal of Econometrics, Elsevier, vol. 86(2), pages 221-241, June.
  34. Chauvet, Marcelle, 1998. "An Econometric Characterization of Business Cycle Dynamics with Factor Structure and Regime Switching," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 969-96, November.
  35. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-84, March.
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