Adaptive Estimation of Autoregressive Models with Time-Varying Variances
Stable autoregressive models are considered with martingale differences errors scaled by an unknown nonparametric time-varying function generating heterogeneity. An important special case involves structural change in the error variance, but in most practical cases the pattern of variance change over time is unknown and may involve shifts at unknown discrete points in time, continuous evolution or combinations of the two. This paper develops kernel-based estimators of the residual variances and associated adaptive least squares (ALS) estimators of the autoregressive coefficients. Simulations show that efficiency gains are achieved by the adaptive procedure.
Adaptive estimation; Autoregression; Heterogeneity; Nonstationary volatility; Weighted regression
Journal of Econometrics
PHILLIPS, Peter C. B. and Xu, Ke-Li.
Adaptive Estimation of Autoregressive Models with Time-Varying Variances. (2008). Journal of Econometrics. 142, (1), 265-285. Research Collection School Of Economics.
Available at: http://ink.library.smu.edu.sg/soe_research/288
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.