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Short-Term Forecasting of Czech Quarterly GDP Using Monthly Indicators

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Abstract

The authors 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. The authors 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. The authors benchmark their results to the performance of a naive 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

Article provided by Charles University Prague, Faculty of Social Sciences in its journal Finance a uver - Czech Journal of Economics and Finance.

Volume (Year): 61 (2011)
Issue (Month): 6 (December)
Pages: 566-583

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Handle: RePEc:fau:fauart:v:61:y:2011:i:6:p:566-583

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Keywords: GDP forecasting; bridge models; principal components; dynamic factor models; 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. 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.
  3. 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.
  4. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
  5. Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2003. "The Generalized Dynamic Factor Model. One-Sided Estimation and Forecasting," LEM Papers Series 2003/13, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
  6. n/a, 2002. "Credibility of the Russian Stabilisation Programme in 1995-98," NIESR Discussion Papers 149, National Institute of Economic and Social Research.
  7. 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.
  8. 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.
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  10. Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 1999. "The Generalized Dynamic Factor Model: Identification and Estimation," CEPR Discussion Papers 2338, C.E.P.R. Discussion Papers.
  11. 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.
  12. 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.).
  13. 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.
  14. 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.
  15. Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-63, July.
  16. 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.
  17. 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.
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Cited by:
  1. 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, August.
  2. Banbura, Marta & Giannone, Domenico & Modugno, Michele & Reichlin, Lucrezia, 2012. "Now-casting and the real-time data flow," CEPR Discussion Papers 9112, C.E.P.R. Discussion Papers.
  3. 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, August.
  4. Kamil Galuscak & Adam Gersl & Marcela Gronychova & Petr Hlavac & Petr Jakubik & Lubos Komarek & Zlatuse Komarkova & Tomas Konecny & Jakub Seidler, 2014. "Stress-Testing Analyses of the Czech Financial System," Occasional Publications - Edited Volumes, Czech National Bank, Research Department, edition 1, volume 12, number rb12/1 edited by Jan Babecky & Roman Horvath, August.
  5. 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, August.
  6. Marek Rusnak, 2013. "Nowcasting Czech GDP in Real Time," Working Papers 2013/06, Czech National Bank, Research Department.

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