Nonstationary dynamic factor analysis

Journal of Statistical Planning and Inference

Volumn 136, Issue 4, 2006, Pages 1237-1257

  Peña, Daniel ^a   Poncela, Pilar ^b  

^a UNIVERSIDAD CARLOS III DE MADRID   (Spain)

^b UNIVERSIDAD AUTÓNOMA DE MADRID   (Spain)

Author keywords

Canonical correlation; Cointegration and common factors; Eigenvectors and eigenvalues; Generalized covariance matrices; Vector time series; Wiener processes

Indexed keywords

EID: 29444433399     PISSN: 03783758     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jspi.2004.08.020     Document Type: Article

References (46)

1. O. Aguilar M. West Bayesian dynamic factor models and portfolio allocation J. Business Econ. Statist. 18 2000 338-356
2. S.K. Ahn Inference of vector autoregressive models with cointegration and scalar components J. Amer. Statist. Assoc. 437 1997 350-356
3. H. Akaike Markovian representation of stochastic processes and its application to the analysis of autoregressive moving average processes Ann. Inst. Statist. Math. 26 1974 363-387
4. T.W. Anderson The use of factor analysis in the statistical analysis of multiple time series Psychometrika 28 1963 1-25
5. S.A. Anderson H.K. Bröns S.T. Jensen Distribution of eigenvalues in Multivariate Statistical Analysis Ann. Statist. 11 1983 392-415
6. S.K. Ansley R. Kohn Exact likelihood of vector autoregressive-moving average process with missing or aggregated data Biometrika 70 1983 275-278
7. J. Bai S. Ng Determining the number of factors in approximate factor models Econometrica 70 2002 191-222
8. R. Bellman Introduction to Matrix Analysis 1960 McGraw-Hill New York
9. P. Billingsley Convergence of Probability Measures 1968 Wiley New York
10. G. Box G. Tiao A canonical analysis of multiple time series Biometrika 64 1977 355-365
11. Brillinger, D.R., 1981. Time series Data Analysis and Theory, expanded ed. Holden-Day, San Francisco.
12. J.E. Cavanaugh R.H. Shumway On computing the expected Fisher information matrix for state-space model parameters Statist. Probab. Lett. 26 1996 347-355
13. N.H. Chan C.Z. Wei Limiting distributions of least squares estimates of unstable autoregressive processes Ann. Statist. 16 1988 367
14. A.P. Dempster N.M. Laird D.B. Rubin Maximum likelihood from incomplete data via the EM algorithm J. Roy. Statist. Soc. B 39 1977 1-38
15. J. Durbin S.J. Koopman Time series analysis by state space methods 2001 Oxford University Press Oxford
16. R.F. Engle C.W.J. Granger Co-integration and error correction: Representation, estimation and testing Econometrica 55 1987 251-276
17. A. Escribano D. Peña Cointegration and common factors J. Time Ser. Anal. 15 1994 577-586
18. M. Forni M. Hallin M. Lippi L. Reichlin The generalized dynamic factor model: Identification and estimation Rev. Econ. Statist. 82 2000 540-554
19. G. Gardner A.C. Harvey G.D.A. Phillips An algorithm for exact maximum likelihood estimation of autoregressive-moving average models by means of Kalman filtering Appl. Statist. 29 1980 311-322
20. J.F. Geweke K.J. Singleton Maximum likelihood confirmatory analysis of economic time series Internat. Econ. Rev. 22 1981 37-54
21. A.D. Hall H.M. Anderson C.W.J. Granger A cointegration analysis of treasury bill yields Rev. Econ. Statist. 74 1992 117-126
22. J. Hamilton Time Series Analysis 1994 Princeton University Press Princeton
23. A. Harvey Forecasting Structural Time Series Models and the Kalman Filter second ed 1989 Cambridge University Press Cambridge
24. S. Johansen Estimation and hypothesis testing of cointegration vectors in Gaussian vector autoregressive models Econometrica 59 1991 1551-1580
25. M. King E. Sentana S. Wadhwani Volatility and links between national stock markets Econometrica 62 1994 901-933
26. S.J. Koopman Disturbance moother for state space models Biometrika 80 1993 117-126
27. H. Lütkepohl Introduction to Multiple Time Series Analysis 1993 Springer Berlin
28. D. Peña Forecasting growth with time series models J. Forecasting 14 1995 97-105
29. D. Peña G. Box Identifying a simplifying structure in time series J. Amer. Statist. Assoc. 82 1987 836-843
30. P.C.B. Phillips S.N. Durlauf Multiple Time Series Regressions with Integrated Processes Rev. Econ. Stud. 53 1986 473-496
31. M.B. Priestley T.S. Rao J. Tong Applications of principal component analysis and factor analysis in the identification of multivariable systems IEEE Trans. Automat. Control 19 1974 703-704
32. G.C. Reinsel Elements of Multivariate Time Series Analysis 1993 Springer New York
33. G.C. Reinsel S.K. Ahn Vector autoregressive models with unit roots and reduced rank structure: Estimation, likelihood ratio test, and forecasting J. Time Ser. Anal. 13 1992 353-375
34. P.M. Robinson Generalized canonical analysis for time series J. Multivariate Anal. 3 1973 141-160
35. R.H. Shumway D.S. Stoffer An approach to time series smoothing and forecasting using the EM algorithm J. Time Ser. Anal. 3 1982 253-264
36. R.H. Shumway D.S. Stoffer Time Series Analysis and its Applications 2000 Springer New York
37. J.H. Stock M.W. Watson Testing for common trends J. Amer. Statist. Assoc. 83 1988 1097-1107
38. J.H. Stock M.W. Watson Forecasting using principal components from a large number of predictors J. Amer. Statist. Assoc. 97 2002 1167-1179
39. D.S. Stoffer K.D. Wall Bootstrapping state-space models: Gaussian maximum likelihood estimation and the Kalman filter J. Amer. Statist. Assoc. 86 1991 1024-1033
40. K. Tanaka Time series analysis. Nonstationary and Noninvertible Distribution Theory 1996 Wiley New York
41. G.C. Tiao R.S. Tsay Model specification in multivariate time series J. Roy. Statist. Soc. B 51 1989 157-213
42. R.S. Tsay G.C. Tiao Asymptotic properties of multivariate nonstationary processes with applications to autoregressions Ann. Statist. 18 1990 220-250
43. R.P. Velu G.C. Reinsel D.W. Wichern Reduced rank models for multiple time series Biometrika 73 1986 105-118
44. M.W. Watson R.F. Engle Alternative algorithms for the estimation of dynamic, mimic and varying coefficient regression models J. Econometr. 23 1983 385-400
45. L.S. Wu J.S. Pai J.R.M. Hosking An algorithm for estimating parameters of state-space models Statist. Probab. Lett. 28 1996 99-106
46. H. Zhang Treasury yield curves and cointegration Appl. Econ. 25 1993 361-367