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Article
Bias-Adjusted Estimation in the ARX(1) Model
Computational Statistics and Data Analysis (2007)
  • Simon Broda, University of Zurich
  • Kai Carstensen
  • Marc Paolella, University of Zurich
Abstract

A new point estimator for the AR(1) coefficient in the linear regression model with arbitrary exogenous regressors and stationary AR(1) disturbances is developed. Its construction parallels that of the median-unbiased estimator, but uses the mode as a measure of central tendency. The mean-adjusted estimator is also considered, and saddlepoint approximations are used to lower the computational burden of all the estimators. Large-scale simulation studies for assessing their small-sample properties are conducted. Their relative performance depends almost exclusively on the value of the autoregressive parameter, with the new estimator dominating over a large part of the parameter space.

Keywords
  • Autoregression; Bias correction; Saddlepoint approximation
Disciplines
Publication Date
2007
Citation Information
Simon Broda, Kai Carstensen and Marc Paolella. "Bias-Adjusted Estimation in the ARX(1) Model" Computational Statistics and Data Analysis Vol. 51 (2007)
Available at: http://works.bepress.com/kai_carstensen/3/