Publication: Detección de raíces unitarias y cointegración mediante métodos de subespacios
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2005
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Instituto Complutense de Análisis Económico. Universidad Complutense de Madrid
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Abstract
En este trabajo se propone un nuevo procedimiento para detectar raíces unitarias basado en métodos de subespacios. Nuestra propuesta tiene tres aspectos originales principales. Primero, la misma metodología puede aplicarse a series individuales o a vectores de series temporales. Segundo, utiliza una familia flexible de criterios de información, cuyas funciones de pérdida pueden adaptarse a las propiedades estadísticas de los datos. Finalmente, no requiere especificar un proceso estocástico para las series
analizadas. Un ejercicio de simulación muestra que el método tiene buenas propiedades en muestras finitas y su aplicación práctica se ilustra mediante el análisis de varias series reales.
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Clasificación AMS: 62M10 - 62H20
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Abuaf, N. y Jorion, P. (1990). Purchasing Power Parity in the Long Run. The Journal of Finance, vol. 45, 157–174.
Akaike, H. (1975). Markovian Representation of Stochastic Processes by Canonical Variables. SIAM Journal of Control, vol. 13, n´um. 1, 162–173.
Akaike, H. (1976). Canonical Correlation Analysis of Time Series and the Use of an Information Criterion. Academic Press.
Aoki, M. (1990). State Space Modelling of Time Series. Springer Verlag, New York.
Aström, K. J. y Eykhoff, P. (1971). System Identification, A Survey. Automatica, vol. 7, 123–162.
Bauer, D. (1998). Some Asymptotic Theory for the Estimation of Linear Systems Using Maximum Likelihood Methods or Subspace Algorithms. Tesis Doctoral, TU Wien.
Bauer, D. y Wagner, M. (2002). Estimating Cointegrated Systems Using Subspace Algorithms. Journal of Econometrics, vol. 111, 47–84.
Box, G. E. P. y Jenkins, G. M. (1976). Time Series Analysis, Forecasting and Control. Holden-Day, San Francisco, 2a ed.
Casals, J. (1997). Métodos de Subespacios en Econometría. Tesis Doctoral, Universidad Complutense de Madrid.
Chui, N. L. C. (1997). Subspace Methods and Informative Experiments for System Identification. Tesis Doctoral, Pembroke College Cambridge.
Dickey, D. A. y Fuller, W. A. (1979). Distribution of the Estimators for Autoregressive Time Series with Unit Root. Journal of the American Statistical Association, vol. 74, 427–431.
Eckart, C. y Young, G. (1936). The Approximation of One Matrix by Another of Lower Rank. Psychometrika, vol. 1, 211–218.
Flôres, R. G., Jorion, P., Preumont, P. Y., y Szafarz, A. (1999). Multivariate Unit Roots Test of PPP Hypothesis. Journal of Empirical Finance, vol. 6, 335–353.
García Hiernaux, A. (2005). Identificación de Modelos para Series Temporales mediante Métodos de Subespacios. Tesis Doctoral, Universidad Complutense de Madrid.
Grubb, H. (1992). A Multivariate Time Series Analysis of Some Flour Price Data. Applied Statistics, vol. 41, 95–107.
Ho, B. y Kalman, R. (1966). Effective Construction of Linear State-Variable Models from Input-Output Functions. Regelungstechnik, vol. 14, 545–548.
Jenkins, G. M. y Alavi, A. S. (1981). Somes Aspects of Modelling and Forecasting Multivariate Time Series. Journal of Time Series Analysis, vol. 2, núm. 1, 1–47.
Johansen, S. (1988). Statistical Analysis of Cointegration Vectors. Journal of Economic Dynamics and Control, vol. 12, 231–254.
Johansen, S. (1991). Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autorregresive Models. Econometrica, vol. 59, 1551–1580.
Larimore, W. E. (1983). System Identification, Reduced-Order Filtering and Modeling Via Canonical Variate Analysis. Proceedings of the American Control Conference, ACC, San Francisco, p´aginas 445–451.
Larimore, W. E. (1990). Canonical Variate Analysis in Identification, Filtering and Adaptive Control. Proceedings of the 29th Conference on Decision and Control, Hawaii, páginas 596–604.
Lütkepohl, H. y Poskitt, D. S. (1996). Specification of Echelon Form VARMA Models. Journal of Business and Economic Statistics, vol. 14, núm. 1, 69–79.
Martín Manjón, R. y Treadway, A. (1997). The Fed Controls Only One of the two Interest Rates in the U.S. Economy. Documento de Trabajo del ICAE, , núm. 9716.
Phillips, P. B. C. y Durlauf, N. S. (1986). Multiple Time Series Regression with Integrated Process. Review of Economic Studies, vol. 53, 473–495.
Poskitt, D. S. (2000). Strongly Consistent Determination of Cointegrating Rank Via Canonical Correlations. Journal of Business and Economic Statistics, vol. 18, 77–90.
Terceiro, J. (1990). Estimation of Dynamics Econometric Models with Errors in Variables. Springer-Verlag, Berlin.
Tiao, G. C. y Tsay, R. S. (1989). Model Specification in Multivariate Time Series. Journal of the Royal Statistical Society, B Series, vol. 51, núm. 2, 157–213.
Van Overschee, P. y De Moor, B. (1994). N4SID: Subspace Algorithms for the Identification of Combined Deterministic-Stochastic Systems. Automatica, vol. 30, núm. 1, 75–93.
Viberg, M. (1995). Subspace-Based Methods for the Identification of the Linear Time Invariant Systems. Automatica, vol. 31, núm. 12, 1835–1852.