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Full-Text Articles in Economics
Adaptive Estimation Of Autoregressive Models With Time-Varying Variances, Ke-Li Xu, Peter C.B. Phillips
Adaptive Estimation Of Autoregressive Models With Time-Varying Variances, Ke-Li Xu, Peter C.B. Phillips
Cowles Foundation Discussion Papers
Stable autoregressive models of known finite order 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. These are shown to be asymptotically efficient, having the same limit distribution as the infeasible generalized …
Adaptive Estimation Of Autoregressive Models With Time-Varying Variances, Ke-Li Xu, Peter C.B. Phillips
Adaptive Estimation Of Autoregressive Models With Time-Varying Variances, Ke-Li Xu, Peter C.B. Phillips
Cowles Foundation Discussion Papers
Stable autoregressive models of known finite order 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. These are shown to be asymptotically efficient, having the same limit distribution as the infeasible generalized …
Indirect Inference For Dynamic Panel Models, Christian Gouriéroux, Peter C.B. Phillips, Jun Yu
Indirect Inference For Dynamic Panel Models, Christian Gouriéroux, Peter C.B. Phillips, Jun Yu
Cowles Foundation Discussion Papers
It is well-known that maximum likelihood (ML) estimation of the autoregressive parameter of a dynamic panel data model with fixed effects is inconsistent under fixed time series sample size ( T ) and large cross section sample size ( N ) asymptotics. The estimation bias is particularly relevant in practical applications when T is small and the autoregressive parameter is close to unity. The present paper proposes a general, computationally inexpensive method of bias reduction that is based on indirect inference (Gouriéroux et al., 1993), shows unbiasedness and analyzes efficiency. The method is implemented in a simple linear dynamic panel …
Gaussian Inference In Ar(1) Time Series With Or Without A Unit Root, Peter C.B. Phillips, Chirok Han
Gaussian Inference In Ar(1) Time Series With Or Without A Unit Root, Peter C.B. Phillips, Chirok Han
Cowles Foundation Discussion Papers
This note introduces a simple first-difference-based approach to estimation and inference for the AR(1) model. The estimates have virtually no finite sample bias, are not sensitive to initial conditions, and the approach has the unusual advantage that a Gaussian central limit theory applies and is continuous as the autoregressive coefficient passes through unity with a uniform / n rate of convergence. En route, a useful CLT for sample covariances of linear processes is given, following Phillips and Solo (1992). The approach also has useful extensions to dynamic panels.