Approximately Median-Unbiased Estimation of Autoregressive Models
提出单变量AR(p)模型带时间趋势的近似中位数无偏估计量，并应用于Nelson-Plosser宏观数据等，发现多数序列比最小二乘估计更持久，部分序列存在单位根。
This article introduces approximately median-unbiased estimators for univariate AR(p) models with time trends. Confidence intervals also are considered. The methods are applied to the Nelson–Plosser macroeconomic data series, the extended Nelson–Plosser macroeconomic data series, and some annual stock-dividend and price series. The results show that most of the series exhibit substantially greater persistence than least squares estimates and some Bayesian estimates suggest. For example, for the extended Nelson–Plosser data set, 8 of the 14 series are estimated to have a unit root, but 6 are estimated to be trend stationary. In contrast, the least squares estimates indicate trend stationarity for all of the series.