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Real-Time Nowcasting of GDP: Factor Model versus Professional Forecasters

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  • Liebermann, Joelle

    (Central Bank of Ireland)

Abstract

This paper performs a fully real-time nowcasting (forecasting) exercise of US real gross domestic product (GDP) growth using Giannone, Reichlin and Small (2008) factor model framework which enables one to handle unbalanced datasets as available in real-time. To this end, we have constructed a novel real-time database of vintages from October 2000 to June 2010 for a panel of US variables, and can hence reproduce, for any given day in that range, the exact information that was available to a real-time forecaster. We track the daily evolution throughout the current and next quarter of the model nowcasting performance. Similarly to Giannone et al. pseudo realtime results, we find that the precision of the nowcasts increases with information releases. Moreover, the Survey of Professional Forecasters (SPF) does not carry additional information with respect to the model best specification, suggesting that the often cited superiority of the SPF, attributable to judgment, is weak over our sample. Then, as one moves forward along the real-time data flow, the continuous updating of the model provides a more precise estimate of current quarter GDP growth and the SPF becomes stale compared to all the model specifications. These results are robust to the recent recession period.

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Bibliographic Info

Paper provided by Central Bank of Ireland in its series Research Technical Papers with number 3/RT/11.

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Date of creation: Mar 2011
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Handle: RePEc:cbi:wpaper:3/rt/11

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Keywords: Real-time data; Nowcasting; Forecasting; Factor model.;

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References

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  1. 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.).
  2. Lucrezia Reichlin & Domenico Giannone & Luca Sala, . "Monetary policy in real time," ULB Institutional Repository 2013/10177, ULB -- Universite Libre de Bruxelles.
    • Domenico Giannone & Lucrezia Reichlin & Luca Sala, 2005. "Monetary Policy in Real Time," NBER Chapters, in: NBER Macroeconomics Annual 2004, Volume 19, pages 161-224 National Bureau of Economic Research, Inc.
  3. Antonello D'Agostino & Kieran McQuinn & Derry O’Brien, 2012. "Nowcasting Irish GDP," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing,CIRET, vol. 2012(2), pages 21-31.
  4. Vincenzo Verardi & Catherine Dehon & Marjorie Gassner, 2009. "Beware of "good" outliers and overoptimistic conclusions," ULB Institutional Repository 2013/9907, ULB -- Universite Libre de Bruxelles.
  5. Faust, Jon & Wright, Jonathan H., 2009. "Comparing Greenbook and Reduced Form Forecasts Using a Large Realtime Dataset," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 468-479.
  6. Bańbura, Marta & Modugno, Michele, 2010. "Maximum likelihood estimation of factor models on data sets with arbitrary pattern of missing data," Working Paper Series 1189, European Central Bank.
  7. Jushan Bai & Serena Ng, 2000. "Determining the Number of Factors in Approximate Factor Models," Econometric Society World Congress 2000 Contributed Papers 1504, Econometric Society.
  8. Catherine Doz & Domenico Giannone & Lucrezia Reichlin, 2006. "A Two-step estimator for large approximate dynamic factor models based on Kalman filtering," THEMA Working Papers 2006-23, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
  9. Angelini, Elena & Camba-Méndez, Gonzalo & Giannone, Domenico & Rünstler, Gerhard & Reichlin, Lucrezia, 2008. "Short-term forecasts of euro area GDP growth," Working Paper Series 0949, European Central Bank.
  10. Boivin, Jean & Ng, Serena, 2005. "Understanding and Comparing Factor-Based Forecasts," MPRA Paper 836, University Library of Munich, Germany.
  11. 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.
  12. D''Agostino, Antonello & Giannone, Domenico & Surico, Paolo, 2007. "(Un)Predictability and Macroeconomic Stability," CEPR Discussion Papers 6594, C.E.P.R. Discussion Papers.
  13. Banbura, Marta & Rünstler, Gerhard, 2011. "A look into the factor model black box: Publication lags and the role of hard and soft data in forecasting GDP," International Journal of Forecasting, Elsevier, vol. 27(2), pages 333-346, April.
  14. G. Rünstler & K. Barhoumi & S. Benk & R. Cristadoro & A. Den Reijer & A. Jakaitiene & P. Jelonek & A. Rua & K. Ruth & C. Van Nieuwenhuyze, 2008. "Short-Term Forecasting of GDP Using Large Monthly Datasets: A Pseudo Real-Time Forecast Evaluation Exercise," Bank of Lithuania Working Paper Series 1, Bank of Lithuania.
  15. Antonello D’ Agostino & Domenico Giannone, 2012. "Comparing Alternative Predictors Based on Large‐Panel Factor Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 74(2), pages 306-326, 04.
  16. Durbin, James & Koopman, Siem Jan, 2001. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, number 9780198523543.
  17. Fair, Ray C & Shiller, Robert J, 1990. "Comparing Information in Forecasts from Econometric Models," American Economic Review, American Economic Association, vol. 80(3), pages 375-89, June.
  18. Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 2005. "The Generalized Dynamic Factor Model: One-Sided Estimation and Forecasting," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 830-840, September.
  19. Bai, Jushan & Ng, Serena, 2007. "Determining the Number of Primitive Shocks in Factor Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 52-60, January.
  20. Jon Faust & Jonathan H. Wright, 2007. "Comparing Greenbook and Reduced Form Forecasts using a Large Realtime Dataset," NBER Working Papers 13397, National Bureau of Economic Research, Inc.
  21. Bernanke, Ben S. & Boivin, Jean, 2003. "Monetary policy in a data-rich environment," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 525-546, April.
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Cited by:
  1. Beber, Alessandro & Brandt, Michael & Luisi, Maurizio, 2013. "Distilling the Macroeconomic News Flow," CEPR Discussion Papers 9360, C.E.P.R. Discussion Papers.
  2. Antonello D'Agostino & Kieran McQuinn & Derry O’Brien, 2012. "Nowcasting Irish GDP," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing,CIRET, vol. 2012(2), pages 21-31.
  3. Liebermann, Joelle, 2012. "Real-time forecasting in a data-rich environment," MPRA Paper 39452, University Library of Munich, Germany.
  4. D’Agostino, Antonello & Schnatz, Bernd, 2012. "Survey-based nowcasting of US growth: a real-time forecast comparison over more than 40 years," Working Paper Series 1455, European Central Bank.

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