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Mildly explosive autoregression with mixing innovations
Authors:Haejune Oh  Sangyeol Lee  Ngai Hang Chan
Affiliation:1. Seoul National University, Republic of Korea;2. Southwest University of Finance and Economics, China;3. The Chinese University of Hong Kong, Hong Kong
Abstract:In this paper, the limit distribution of the least squares estimator for mildly explosive autoregressive models with strong mixing innovations is established, which is shown to be Cauchy as in the iid case. The result is applied to identify the onset and the end of an explosive period of an econometric time series. Simulations and data analysis are also conducted to demonstrate the usefulness of the result.
Keywords:62M10  62F03  Mildly explosive autoregression  Mixing innovations  Limit theorem for least squares estimator
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