Ir al contenido

Documat


Detección de raíces unitarias y cointegración mediante métodos de subespacios

  • ALFREDO GARCÍA-HIERNAUX [1] Árbol académico ; JOSÉ CASALS [2] ; MIGUEL JEREZ [2]
    1. [1] Universidad Carlos III de Madrid

      Universidad Carlos III de Madrid

      Madrid, España

    2. [2] Universidad Complutense de Madrid

      Universidad Complutense de Madrid

      Madrid, España

  • Localización: Revista Colombiana de Estadística, ISSN-e 2389-8976, ISSN 0120-1751, Vol. 30, Nº. 1, 2007, págs. 77-96
  • Idioma: español
  • Títulos paralelos:
    • Subspace-Based Methods to Determine Unit Roots and Cointegrating Ranks
  • Enlaces
  • Resumen
    • español

      Proponemos un nuevo procedimiento para detectar raíces unitarias basado en métodos de subespacios. Su planteamiento comporta tres aspectos fundamentales. Primero, la misma metodología se puede aplicar a series individuales o a vectores de series temporales. Segundo, utiliza una familia flexible de criterios de información, cuyas funciones de pérdida se pueden adaptar a las propiedades estadísticas de los datos. Finalmente, no requiere especificar un proceso estocástico para las series analizadas. Se demuestra la consistencia del método y los ejercicios de simulación revelan buenas propiedades en muestras finitas. Además, su aplicación práctica se ilustra mediante el análisis de varias series reales.

    • English

      We propose a new procedure to detect unit roots based on subspace methods. It has three main original aspects. First, the same method can be applied to single or multiple time series. Second, it uses a flexible family of information criteria, which loss functions can be adapted to the statistical properties of the data. Last, it does not require the specification of a stochastic process for the series analyzed. This procedure is consistent and a simulation exercise shows that it has good finite sample properties. Its application is illustrated with the analysis of several real time series

  • Referencias bibliográficas
    • Abuaf, N.,Jorion, P.. (1990). ‘Purchasing Power Parity in the Long Run’. The Journal of Finance. 45. 157174
    • 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.
    • D., Bauer. (1998). Some Asymptotic Theory for the Estimation of Linear Systems Using Maximum Likelihood Methods or Subspace Algorithms.
    • Bauer, D.,Ljung, L.. (2002). ‘Some Facts About the Choice of the Weighting Matrices in Larimore Type of Subspace Algorithms’. Automatica....
    • Bauer, D.,Wagner, M.. (2002). ‘Estimating Cointegrated Systems Using Subspace Algorithms’. Journal of Econometrics. 111. 4784
    • Bengtsson, T.,Cavanaugh, J.. (2006). ‘An Improved Akaike Information Criterion for State-Space Model Selection’. Computational Statistics...
    • Casals, J.. (1997). Métodos de subespacios en econometría.
    • Casals, J.,Sotoca, S.,Jerez, M.. (1999). ‘A Fast Stable Method to Compute the Likelihood of Time Invariant State Space Models’. Economics...
    • Chui, N. L. C.. (1997). Subspace Methods and Informative Experiments for System Identification.
    • Dickey, D. A.,Fuller, W. A.. (1979). ‘Distribution of the Estimators for Autoregressive Time Series with Unit Root’. Journal of the American...
    • Eckart, C.,Young, G.. (1936). ‘The Approximation of One Matrix by Another of Lower Rank’. Psychometrika. 1. 211218
    • Favoreel, W.,De Moor, B.,Van Overschee, P.. (2000). ‘Subspace State Space System Identification for Industrial Processes’. Journal of Process...
    • Flôres, R. G.,Jorion, P.,Preumont, P. Y.,Szafarz, A.. (1999). ‘Multivariate Unit Roots Test of PPP Hypothesis’. Journal of Empirical Finance....
    • García-Hiernaux, A.. (2005). Identificación de modelos para series temporales mediante métodos de subespacios.
    • Grubb, H.. (1992). ‘A Multivariate Time Series Analysis of Some Flour Price Data’. Applied Statistics. 41. 95107
    • Ho, B.,Kalman, R.. (1966). Effective Construction of Linear State-Variable Models from Input-Output Functions’. Regelungstechnik. 14. 545548
    • Hurvich, C.,Shumway, R.,Tsai, C.. (1990). ‘Improved Estimators of Kullback-Leibler in Information for Autoregressive Model Selection in Small...
    • Johansen, S.. (1991). ‘Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models’. Econometrica....
    • Larimore, W. E.. (1983). System Identification, Reduced-Order Filtering and Modeling Via Canonical Variate Analysis. ‘Proceedings of the American...
    • Larimore, W. E.. (1990). Canonical Variate Analysis in Identification, Filtering and Adaptive Control. ‘Proceedings of the 29th Conference...
    • Lütkepohl, H.,Poskitt, D. S.. (1996). ‘Specification of Echelon Form VARMA Models’. Journal of Business and Economic Statistics. 14. 6979
    • Martín Manjón, R.,Treadway, A.. (1997). ‘The Fed Controls Only One of the Two Interest Rates in the U.S. Economy’. Documento de Trabajo del...
    • Phillips, P. B. C.,Durlauf, N. S.. (1986). ‘Multiple Time Series Regression with Integrated Process’. Review of Economic Studies. 53. 473495
    • Poskitt, D. S.. (2000). ‘Strongly Consistent Determination of Cointegrating Rank Via Canonical Correlations’. Journal of Business and Economic...
    • Terceiro, J.. (1990). Estimation of Dynamics Econometric Models with Errors in Variables. Springer-Verlag. Berlin.
    • Tiao, G. C.,Tsay, R. S.. (1989). ‘Model Specification in Multivariate Time Series’. Journal of the Royal Statistical Society, B Series. 51....
    • Van Overschee, P.,De Moor, B.. (1994). ‘N4SID: Subspace Algorithms for the Identification of Combined Deterministic-Stochastic Systems’. Automatica....
    • Viberg, M.. (1995). ‘Subspace-Based Methods for the Identification of the Linear Time-Invariant Systems’. Automatica. 31. 18351852
Los metadatos del artículo han sido obtenidos de SciELO Colombia

Fundación Dialnet

Mi Documat

Opciones de artículo

Opciones de compartir

Opciones de entorno