Bootstrapping cointegrating regressions

被引:73
|
作者
Li, HY
Maddala, GS
机构
[1] CHINESE UNIV HONG KONG,FAC BUSINESS ADM,DEPT DECIS SCI & MANAGERIAL ECON,HONG KONG,HONG KONG
[2] OHIO STATE UNIV,DEPT ECON,COLUMBUS,OH 43210
关键词
nonstationary time series; small sample bias; size distortion; moving block bootstrap; stationary bootstrap;
D O I
10.1016/S0304-4076(97)00043-2
中图分类号
F [经济];
学科分类号
02 ;
摘要
The paper investigates the usefulness of bootstrap methods for small sample inference in cointegrating regression models. It discusses the standard bootstrap, the recursive bootstrap, the moving block bootstrap and the stationary bootstrap methods. Some guidelines for bootstrap data generation and test statistics to consider are provided and some simulation evidence presented suggests that the bootstrap methods, when properly implemented, can provide significant improvement over asymptotic inference. (C) 1997 Elsevier Science S.A.
引用
收藏
页码:297 / 318
页数:22
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