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Title: Quasi-likelihood estimation of structure-changed threshold double autoregressive models Authors:  Feifei Guo - Hong Kong University of Science and Technology (Hong Kong) [presenting]
Abstract: The quasi-maximum likelihood estimator (QMLE) of the structure-changed and two-regime threshold double autoregressive model is investigated. It is shown that both the estimated threshold and change-point are $n$-consistent, and they converge weakly to the smallest minimizer of a compound Poisson process and the location of minima of a two-sided random walk, respectively. Other estimated parameters are $n^(1/2)$-consistent and asymptotically normal. The performance of the QMLE are assessed via simulation studies and a real example is given to illustrate our procedure.