摘要
This paper analyzes multiple structural changes by GMDH （Group Meth- ods of Data Handling）, which have obvious advantages. Our method extends the model of Lumsdaine ＆ Papell[1] （1997）, and it could be applied to the case of more than two structural changes. Because of simultaneously considering every structural change of the hypothesis, it is likely to be of particular relevance in practice. And it can decrease large investigation costs by MATLAB programming. What is more, we can select the criterion value of F incremental statistic to control the significance of the breaks, based on kinds of investigation intentions. And the empirical evidences on Shenzhen Composite Index are presented to illustrate the usefulness of our method.
