Principal Components Analysis of Cointegrated Time Series
- 11 February 1997
- journal article
- research article
- Published by Cambridge University Press (CUP) in Econometric Theory
- Vol. 13 (4) , 529-557
- https://doi.org/10.1017/s0266466600005995
Abstract
This paper considers the analysis of cointegrated time series using principal components methods. These methods have the advantage of requiring neither the normalization imposed by the triangular error correction model nor the specification of a finite-order vector autoregression. An asymptotically efficient estimator of the cointegrating vectors is given, along with tests forcointegration and tests of certain linear restrictions on the cointegrating vectors. An illustrative application is provided.Keywords
This publication has 25 references indexed in Scilit:
- Testing for Cointegration in a System of EquationsEconometric Theory, 1995
- Residual-Based Tests for the Null of Stationarity with Applications to U.S. Macroeconomic Time SeriesEconometric Theory, 1994
- A Residual-Based Test of the Null of Cointegration Against the Alternative of No CointegrationEconometric Theory, 1994
- Estimation and Testing of Cointegrated Systems by an Autoregressive ApproximationEconometric Theory, 1992
- Estimation for Partially Nonstationary Multivariate Autoregressive ModelsJournal of the American Statistical Association, 1990
- Estimation for Partially Nonstationary Multivariate Autoregressive ModelsJournal of the American Statistical Association, 1990
- Asymptotic Properties of Residual Based Tests for CointegrationEconometrica, 1990
- Testing for Common TrendsJournal of the American Statistical Association, 1988
- Asymptotic Properties of Least Squares Estimators of Cointegrating VectorsEconometrica, 1987
- Co-Integration and Error Correction: Representation, Estimation, and TestingEconometrica, 1987