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Short-Term Forecasting of Czech Quarterly GDP Using Monthly Indicators

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Author Info

  • Katerina Arnostova
  • David Havrlant
  • Lubos Ruzicka
  • Peter Toth

Abstract

We evaluate the out-of-sample forecasting performance of six competing models at horizons of up to three quarters ahead in a pseudo-real time setup. All the models use information in monthly indicators released ahead of quarterly GDP. We estimate two models – averaged vector autoregressions and bridge equations – relying on just a few monthly indicators. The remaining four models condition the forecast on a large set of monthly series. These models comprise two standard principal components models, a dynamic factor model based on the Kalman smoother and a generalized dynamic factor model. We benchmark our results to the performance of a naïve model and the historical near-term forecasts of the Czech National Bank’s staff. The findings are also compared with a related study conducted by ECB staff (Barhoumi et al., 2008). In the Czech case, standard principal components is the most precise model overall up to three quarters ahead. However, the CNB staff’s historical forecasts were the most accurate one quarter ahead.

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Bibliographic Info

Paper provided by Czech National Bank, Research Department in its series Working Papers with number 2010/12.

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Date of creation: Dec 2010
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Handle: RePEc:cnb:wpaper:2010/12

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Keywords: Bridge models; dynamic factor models; GDP forecasting; principal components; real-time evaluation.;

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References

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  1. Maximo Camacho & Gabriel Perez-Quiros, 2010. "Introducing the euro-sting: Short-term indicator of euro area growth," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 663-694.
  2. George Kapetanios & Vincent Labhard & Simon Price, 2007. "Forecast combination and the Bank of England’s suite of statistical forecasting models," Bank of England working papers 323, Bank of England.
  3. Mario Forni & Marc Hallin & Lucrezia Reichlin & Marco Lippi, 2000. "The generalised dynamic factor model: identification and estimation," ULB Institutional Repository 2013/10143, ULB -- Universite Libre de Bruxelles.
  4. 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.
  5. Domenico Giannone & Lucrezia Reichlin & Luca Sala, 2005. "Monetary policy in real time," ULB Institutional Repository 2013/6401, 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.
  6. Baffigi, Alberto & Golinelli, Roberto & Parigi, Giuseppe, 2004. "Bridge models to forecast the euro area GDP," International Journal of Forecasting, Elsevier, vol. 20(3), pages 447-460.
  7. 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.
  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. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
  10. Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-62, April.
  11. Francis X. Diebold & Robert S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
  12. Forni M. & Hallin M., 2003. "The Generalized Dynamic Factor Model: One-Sided Estimation and Forecasting," Computing in Economics and Finance 2003 143, Society for Computational Economics.
  13. Karim Barhoumi & Szilard Benk & Riccardo Cristadoro & Ard Den Reijer & Audrone Jakaitiene & Piotr Jelonek & António Rua & Gerhard Rünstler & Karsten Ruth & Christophe Van Nieuwenhuyze, 2008. "Short-term forecasting of GDP using large monthly datasets - a pseudo real-time forecast evaluation exercise," Occasional Paper Series 84, European Central Bank.
  14. Gonzalo Camba-Mendez & George Kapetanios & Richard J. Smith & Martin R. Weale, 2001. "An automatic leading indicator of economic activity: forecasting GDP growth for European countries," Econometrics Journal, Royal Economic Society, vol. 4(1), pages 37.
  15. 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.
  16. Kitchen, John & Monaco, Ralph, 2003. "Real-Time Forecasting in Practice: The U.S. Treasury Staff's Real-Time GDP Forecast System," MPRA Paper 21068, University Library of Munich, Germany, revised Oct 2003.
  17. Fischer, Ilan & Harvey, Nigel, 1999. "Combining forecasts: What information do judges need to outperform the simple average?," International Journal of Forecasting, Elsevier, vol. 15(3), pages 227-246, July.
  18. Maximo Camacho & Gabriel Perez-Quiros, 2009. "Ñ-STING: España Short Term INdicator of Growth," Banco de Espa�a Working Papers 0912, Banco de Espa�a.
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Cited by:
  1. Robert Ambrisko & Vitezslav Augusta & Jan Babecky & Michal Franta & Dana Hajkova & Petr Kral & Jan Libich & Pavla Netusilova & Milan Rikovsky & Jakub Rysanek & Pavel Soukup & Petr Stehlik & Vilem Vale, 2013. "Macroeconomic Effects of Fiscal Policy," Occasional Publications - Edited Volumes, Czech National Bank, Research Department, edition 2, volume 11, number rb11/2 edited by Jan Babecky & Kamil Galuscak.
  2. Bańbura, Marta & Giannone, Domenico & Modugno, Michele & Reichlin, Lucrezia, 2013. "Now-casting and the real-time data flow," Working Paper Series 1564, European Central Bank.
  3. Jaromir Baxa & Michal Franta & Tomas Havranek & Roman Horvath & Miroslav Plasil & Marek Rusnak & Borek Vasicek, 2013. "Transmission of Monetary Policy," Occasional Publications - Edited Volumes, Czech National Bank, Research Department, edition 1, volume 11, number rb11/1 edited by Jan Babecky & Roman Horvath.
  4. Marek Rusnak, 2013. "Nowcasting Czech GDP in Real Time," Working Papers 2013/06, Czech National Bank, Research Department.
  5. Katerina Arnostova & Jozef Barunik & Jan Filacek & Michal Franta & David Havrlant & Roman Horvath & Filip Novotny & Marie Rakova & Lubos Ruzicka & Branislav Saxa & Katerina Smidkova & Peter Toth, 2012. "Macroeconomic Forecasting: Methods, Accuracy and Coordination," Occasional Publications - Edited Volumes, Czech National Bank, Research Department, edition 1, volume 10, number rb10/1 edited by Jan Babecky.

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