Testing for serial correlation against an ARMA(1, 1) process

被引:39
作者
Andrews, DWK [1 ]
Ploberger, W [1 ]
机构
[1] UNIV ST ANDREWS, DEPT ECON, ST ANDREWS KY16 9A1, FIFE, SCOTLAND
关键词
autoregressive moving average model; consistent test; Lagrange multiplier test; likelihood ratio test; nonstandard testing problem; test of white noise;
D O I
10.2307/2291751
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
This article is concerned with tests for serial correlation in time series and in the errors of regression models. In particular, the nonstandard problem of testing for white noise against autoregressive moving average model ARMA(1, 1) alternatives is considered. The likelihood ratio (LR), sup Lagrange multiplier (LM), and exponential average LM and LR tests are shown to be asymptotically admissible for ARMA(1, 1) alternatives. In addition, they are shown to be consistent against all (weakly stationary strong mixing) non-white noise alternatives. Simulation results compare the tests to several tests in the literature. These results show that the LR and Exp-LR infinity tests have very good all-around power properties for nonseasonal alternatives.
引用
收藏
页码:1331 / 1342
页数:12
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