Journal
MATHEMATICAL AND COMPUTER MODELLING
Volume 56, Issue 7-8, Pages 152-166Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.mcm.2011.12.002
Keywords
Empirical likelihood; Least squares estimation; Asymptotic normality; Generalized random coefficient autoregressive model; Confidence region
Categories
Funding
- National Natural Science Foundation of China [10971081, 11001105, 11071126, 10926156, 11071269, J0730101]
- Specialized Research Fund for the Doctoral Program of Higher Education [20070183023, 20110061110003]
- Program for New Century Excellent Talents in University [NCET-08-237]
- Jilin University [201100011, 200810024, 200903278]
- Ministry of Education [11YJAZH125]
- Science and Technology Development Program of Jilin Province
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In this paper, we consider the application of the empirical likelihood method to the generalized random coefficient autoregressive (GRCA) model. The empirical log-likelihood ratio statistics are proposed and the nonparametric versions of the Wilk's theorem are obtained. Furthermore, when the order of the model is 1, we also derive a test statistic to test the stationary-ergodicity based on the conditional least-squares method. Numerical results from simulation studies suggest that the empirical likelihood method is more accurate than the normal approximation-based method of Hwang and Basawa (1998) [1]. Some simulation studies are also conducted to investigate the finite sample performances of the proposed test. (c) 2011 Elsevier Ltd. All rights reserved.
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