A Decision-Theoretic Analysis of the Unit-Root Hypothesis Using Mixtures of Elliptical Models
提出一种基于决策理论的单位根检验方法，通过预测方差定义损失函数，并扩展似然函数以包含非正态分布、结构突变和移动平均误差，实证发现多数序列的趋势平稳后验概率较高，但决策分析常选择单位根模型。
This paper develops a formal decision theoretic approach to testing for a unit root in economic time series.The approach is empirically implemented by specifying a loss function based on predictive variances; models are chosen so as to minimize expected loss.In addition, the paper broadens the class of likelihood functions traditionally considered in the Bayesian unit root literature by: i) Allowing for departures from normality via the specification of a likelihood based on general elliptical densities; ii) allowing for structural breaks to occur; Hi) allowing for moving average errors; and iv) using mixtures of various submodels to create a very flexible overall likelihood.Empirical results indicate that, while the posterior probability of trend-stationarity is quite high for most of the series considered, the unit root model is often selected in the decision theoretic analysis.