A Canonical Correlation Approach for Selecting the Number of Dynamic Factors

Oxford Bulletin of Economics and Statistics

Volumn 75, Issue 1, 2013, Pages 23-36

  Breitung, Jörg ^a   Pigorsch, Uta ^b  

^a UNIVERSITY OF BONN   (Germany)

^b UNIVERSITY OF MANNHEIM   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84871566979     PISSN: 03059049     EISSN: 14680084     Source Type: Journal    
DOI: 10.1111/obes.12003     Document Type: Article

References (30)

1. Amengual, D. and Watson, M. (2007). 'Consistent estimation of the number of dynamic factors in a large N and T panel', Journal of Business and Economic Statistics, Vol. 25, pp. 91-96.
2. Anderson, T. (1984). An introduction to Multivariate Statistical Analysis, 2nd edn, Wiley, New York.
3. Angelini, E., Henry, J. and Mestre, R. (2001). Diffusion Index-based Inflation Forecasts for the Euro Area, ECB Working Paper 61.
4. Artis, M. J., Banerjee, A. and Marcellino, M. (2005). 'Factor forecasts for the UK', Journal of Forecasting, Vol. 24, pp. 279-298.
5. Bai, J. (2003). 'Inferential theory for factor models of large dimensions', Econometrica, Vol. 71, pp. 135-172.
6. Bai, J. and Ng, S. (2002). 'Determining the number of factors in approximate factor models', Econometrica, Vol. 70, pp. 191-221.
7. Bai, J. and Ng, S. (2007). 'Determining the number of primitive shocks in factor models', Journal of Business and Economic Statistics, Vol. 25, pp. 52-60.
8. Banerjee, A., Marcellino, M. and Masten, I. (2010). Forecasting with Factor-augmented Error Correction Models, CEPR Discussion Paper 7677.
9. Breitung, J. and Tenhofen, T. (2011). 'GLS estimation of dynamic factor models', Journal of the American Statistical Association, Vol. 106, pp. 1150-1166.
10. Brisson, M., Campbell, B. and Galbraith, J. (2003). 'Forecasting some low-predictability time series using Diffusion indices', Journal of Forecasting, Vol. 22, pp. 515-531.
11. Bruneau, C., Bandt, O. D., Flageollet, A. and Michaux, E. (2007). 'Forecasting inflation using economic indicators: the case of France', Journal of Forecasting, Vol. 26, pp. 1-22.
12. Eickmeier, S. and Ziegler, C. (2008). 'How successful are dynamic factor models at forecasting output and inflation? A meta-analytic approach', Journal of Forecasting, Vol. 27, pp. 237-265.
13. Favero, C., Marcellino, M. and Neglia, F. (2005). Principal components at work: the empirical analysis of monetary policy with large data sets', Journal of Applied Econometrics, Vol. 20, pp. 603-620.
14. Forni, M., Gianonne, D., Lippi, M. and Reichlin, L. (2009). 'Opening the black box: structural factor models versus structural VARs', Econometric Theory, Vol. 25, pp. 1319-1347.
15. Forni, M., Hallin, M., Lippi, M. and Reichlin, L. (2000). 'The generalized dynamic factor model: identification and estimation', The Review of Economics and Statistics, Vol. 82, pp. 540-554.
16. Forni, M. and Lippi, M. (2001). 'The generalized factor model: representation theory', Econometric Theory, Vol. 17, pp. 1113-1141.
17. Forni, M. and Reichlin, L. (1998). 'Lets get real: a factor-analytical approach to disaggregated business cycle dynamics', Review of Economic Studies, Vol. 65, pp. 453-473.
18. Giannone, D., Reichlin, L. and Sala, L. (2006). 'VARs, factor models and the empirical validation of equilibrium business cycle models', Journal of Econometrics, Vol. 132, pp. 257-279.
19. Hallin, M. and Liska, R. (2007). 'Determining the number of dynamic factors in the general dynamic factor model', Journal of the American Statistical Association, Vol. 102, pp. 603-617.
20. Jacobs, J. and Otter, P. (2008). 'Determining the number of factors and lag order in dynamic factor models: a minimum entropy approach', Econometric Reviews, Vol. 27, pp. 398-427.
21. Marcellino, M. and Kapetanios, G. (2009). 'A parametric estimation method for dynamic factor models of large dimensions', Journal of Time Series Analysis, Vol. 30, pp. 208-238.
22. Marcellino, M., Stock, J., and Watson, M. (2003). 'Macroeconomic forecasting in the Euro area: country specific versus area-wide information', European Economic Review, Vol. 47, pp. 1-18.
23. Onatski, A. (2009). 'Testing hypotheses about the number of factors in large factor models', Econometrica, Vol. 77, pp. 1447-1479.
24. Onatski, A. (2010). 'Determining the number of factors from empirical distribution of eigenvalues', Review of Economics and Statistics, Vol. 92, pp. 1004-1016.
25. den Reijer, A. (2005). Forecasting Dutch GDP Using Large Scale Factor Models, DNB Working Paper 028.
26. Schumacher, C. (2007). 'Forecasting German GDP using alternative factor models based on large datasets', Journal of Forecasting, Vol. 26, pp. 271-302.
27. Stock, J. and Watson, M. (1999). 'Forecasting inflation', Journal of Monetary Economics, Vol. 44, pp. 293-335.
28. Stock, J. and Watson, M. (2002a). 'Forecasting using principal components from a large number of predictors', Journal of the American Statistical Association, Vol. 97, pp. 1167-79.
29. Stock, J. and Watson, M. (2002b). 'Macroeconomic forecasting using diffusion indexes', Journal of Business and Economic Statistics, Vol. 20, pp. 147-162.
30. Stock, J. and Watson, M. (2005). Implications of Dynamic Factor Models for VAR Analysis, NBER Working Paper 11467.