Estimating break points in a time series regression with structural changes
Estimating break points in a time series regression with structural changes
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DOI：
10.1016/s0378-4754(03)00123-x
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发表时间：
2004-01
期刊：
影响因子：
--
通讯作者：
K. Maekawa;Zonglu He;K. Tee
中科院分区：
文献类型：
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作者：
K. Maekawa;Zonglu He;K. Tee
在计量经济学文献中，当I（1）和I（0）模型中存在结构变化时，当断点个数已知或未知时（尽管断点的位置未知），提出了许多单位根的检验方法。最近，Hatanaka和Yamada [A unit root test in the presence of structural changes in I（1）and I（0）models，in：R.F. Engle，H.白色（编辑），Cointegration，Causality，and Forecasting：A Festschrift in Honour of克莱夫W.J.格兰杰，牛津大学出版社，牛津，1999（第11章）]提出了一个单位根检验由两个步骤组成：估计断点和检验单位根，但他们的方法导致断点估计值出现显著的负偏差。本文试图利用加权对称估计来消除负偏差。
In econometric literatures, a number of tests for unit roots have been proposed in the presence of structural changes in I(1) and I(0) model when the numbers of break points are or are not known (though their locations are unknown). Recently, Hatanaka and Yamada [A unit root test in the presence of structural changes in I(1) and I(0) models, in: R.F. Engle, H. White (Eds.), Cointegration, Causality, and Forecasting: A Festschrift in Honour of Clive W.J. Granger, Oxford University Press, Oxford, 1999 (Chapter 11)] proposed a unit root test consisted of two steps: estimating break points and testing a unit root, but their methods resulted in remarkable negative biases in the break points estimates. Our paper attempts to eliminate the negative biases by utilizing the weighted symmetric estimation.