Efficient GMM and MD estimation of autoregressive models

被引：5
|
作者：
Kim, YS
Qian, HL
Schmidt, P [1 ]
机构：
[1] Michigan State Univ, Dept Econ, E Lansing, MI 48824 USA
[2] Victoria Univ Wellington, Sch Econ & Finance, Wellington, New Zealand
来源：
ECONOMICS LETTERS | 1999年 / 62卷 / 03期
关键词：
autoregressive model; GMM; minimum distance;
D O I：
10.1016/S0165-1765(99)00017-8
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
This paper considers minimum distance estimation of the AR(p) model. Given the first p autocorrelations, higher-order autocorrelations are shown to be redundant. Thus, given non-normality, improvements to the normal quasi-MLE must depend on something other than autocorrelations. (C) 1999 Elsevier Science S.A. All rights reserved.
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页码：265 / 270
页数：6
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