Journal of Guangxi Normal University(Natural Science Edition) ›› 2022, Vol. 40 ›› Issue (1): 68-81.doi: 10.16088/j.issn.1001-6600.2021060905

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Estimation and Test for Asymmetric DAR Model

CHEN Zhongxiu1, ZHANG Xingfa1,2, XIONG Qiang1,2*, SONG Zefang1,2   

  1. 1. School of Economics and Statistics, Guangzhou University, Guangzhou Guangdong 510006, China;
    2. Lingnan Research Institute of Statistical Science, Guangzhou University, Guangzhou Guangdong 510006, China
  • Received:2021-06-09 Revised:2021-07-14 Online:2022-01-25 Published:2022-01-24

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Abstract: The estimation and testing problems of asymmetric double autoregression (DAR) model are studied in this paper. The parametric component by virtue of quasi maximum likelihood estimation (QMLE) method is firstly proposed. Under some regularity conditions, the resulting estimators are consistent and asymptotically normal. Then, a quasi-likelihood ratio (QLR) statistic to detect asymmetric effect is proposed. The asymptotic properties of the testing statistic are established under null and alternative hypotheses. Finally, both simulation studies and empirical application well demonstrate the finite sample performance of the proposed estimation methodology and testing procedure.

Key words: asymmetric DAR model, QMLE, asymmetry test, asymptotic property

CLC Number: 

  • O212.1
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