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Unit Root Test for Panel Data AR(1) Time Series Model With Linear Time Trend and Augmentation Term: A Bayesian Approach

机译:面板数据的单位根测试AR(1)时间序列模型具有线性时间趋势和增强术语:贝叶斯方法

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摘要

The univariate time series models, in the case of unit root hypothesis, are more biased towards the acceptance of the Unit Root Hypothesis especially in a short time span. However, the panel data time series model is more appropriate in such situation. The Bayesian analysis of unit root testing for a panel data time series model is considered. An autoregressive panel data AR(1) model with linear time trend and augmentation term has been considered and derived the posterior odds ratio for testing the presence of unit root hypothesis under appropriate prior assumptions. A simulation study and real data analysis are carried out for the derived theorem.
机译:在单位根本假设的情况下,单变量时间序列模型更加偏向于接受单位根假设,特别是在短时间内跨度。但是,面板数据时间序列模型在这种情况下更适合。考虑了面板数据时间序列模型的单位根系测试的贝叶斯分析。具有线性时间趋势和增强术语的自回归面板数据AR(1)模型并衍生出在适当的先前假设下测试单位根本假设的后部比率。为衍生定理进行了模拟研究和实际数据分析。

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