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The role of country-specific trade and survey data in forecasting euro area manufacturing production: perspective from large panel factor models

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  • Darracq Pariès, Matthieu
  • Maurin, Laurent

Abstract

Several factor-based models are estimated to investigate the role of country-specific trade and survey data in forecasting euro area manufacturing production. Following Boivin and Ng (2006), the emphasis is put on the role of dataset selection on the empirical performance of factor models. First, spectral analysis is used to assess the information content for euro area manufacturing production of external trade and surveys data of the three largest economies as well as two medium-sized highly opened economies. Second, common factors are estimated on four datasets, following two methodologies, Stock and Watson (2002a, 2002b) and Forni et al. (2005). Third, a rolling out of sample forecast comparison exercise is carried out on nine models. Compared to univariate benchmarks, our results are supportive of factor-based models up to two quarters. They show that incorporating survey and external trade information improves the forecast of manufacturing production. They also confirm the findings of Marcellino, Stock and Watson (2003) that, using country information, it is possible to improve forecasts for the euro area. Interesting, the medium-sized highly opened economies provide valuable information to monitor area wide developments, beyond their weight in the aggregate. Conversely, the large countries do not add much to the monitoring of the aggregate, when considered separately. JEL Classification: E37, C3, C53

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Paper provided by European Central Bank in its series Working Paper Series with number 0894.

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Date of creation: May 2008
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Handle: RePEc:ecb:ecbwps:20080894

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Keywords: Dataset; Factor models; Forecasting;

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References

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  1. Jean Boivin & Serena Ng, 2005. "Understanding and Comparing Factor-Based Forecasts," NBER Working Papers 11285, National Bureau of Economic Research, Inc.
  2. 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.
  3. Domenico Giannone & Lucrezia Reichlin & David H Small, 2007. "Nowcasting GDP and Inflation: The Real-Time Informational Content of Macroeconomic Data Releases," Money Macro and Finance (MMF) Research Group Conference 2006 164, Money Macro and Finance Research Group.
  4. D''Agostino, Antonello & Giannone, Domenico, 2007. "Comparing Alternative Predictors Based on Large-Panel Factor Models," CEPR Discussion Papers 6564, C.E.P.R. Discussion Papers.
  5. Schumacher, Christian & Breitung, Jörg, 2006. "Real-time forecasting of GDP based on a large factor model with monthly and quarterly data," Discussion Paper Series 1: Economic Studies 2006,33, Deutsche Bundesbank, Research Centre.
  6. Stock J.H. & Watson M.W., 2002. "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1167-1179, December.
  7. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
  8. Angelini, Elena & Henry, Jérôme & Marcellino, Massimiliano, 2003. "Interpolation and backdating with a large information set," Working Paper Series 0252, European Central Bank.
  9. 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.
  10. Banbura, Marta & Rünstler, Gerhard, 2007. "A look into the factor model black box: publication lags and the role of hard and soft data in forecasting GDP," Working Paper Series 0751, European Central Bank.
  11. Jean Boivin & Serena Ng, 2003. "Are More Data Always Better for Factor Analysis?," NBER Working Papers 9829, National Bureau of Economic Research, Inc.
  12. Marcellino, Massimiliano & Stock, James H. & Watson, Mark W., 2006. "A comparison of direct and iterated multistep AR methods for forecasting macroeconomic time series," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 499-526.
  13. Croux, Christophe & Forni, Mario & Reichlin, Lucrezia, 1999. "A Measure of Comovement for Economic Variables: Theory and Empirics," CEPR Discussion Papers 2339, C.E.P.R. Discussion Papers.
  14. Calista Cheung & Frédérick Demers, 2007. "Evaluating Forecasts from Factor Models for Canadian GDP Growth and Core Inflation," Working Papers 07-8, Bank of Canada.
  15. Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2005. "The generalised dynamic factor model: one sided estimation and forecasting," ULB Institutional Repository 2013/10129, ULB -- Universite Libre de Bruxelles.
  16. Marcellino, Massimiliano & Stock, James H. & Watson, Mark W., 2003. "Macroeconomic forecasting in the Euro area: Country specific versus area-wide information," European Economic Review, Elsevier, vol. 47(1), pages 1-18, February.
  17. George Kapetanios & Massimiliano Marcellino, 2003. "A Comparison of Estimation Methods for Dynamic Factor Models of Large Dimensions," Working Papers 489, Queen Mary, University of London, School of Economics and Finance.
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Cited by:
  1. Katja Drechsel & Laurent Maurin, 2011. "Flow of conjunctural information and forecast of euro area economic activity," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 30(3), pages 336-354, April.

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