G2TT
来源类型Working Paper
规范类型报告
DOI10.3386/t0092
来源IDTechnical Working Paper 0092
Testing The Autocorrelation Structure of Disturbances in Ordinary Least Squares and Instrumental Variables Regressions
Robert E. Cumby; John Huizinga
发表日期1990-10-01
出版年1990
语种英语
摘要This paper derives the asymptotic distribution for a vector of sample autocorrelations of regression residuals from a quite general linear model. The asymptotic distribution forms the basis for a test of the null hypothesis that the regression error follows a moving average of order q [greaterthan or equal] 0 against the general alternative that autocorrelations of the regression error are non-zero at lags greater than q. By allowing for endogenous, predetermined and/or exogenous regressors, for estimation by either ordinary least squares or a number of instrumental variables techniques, for the case q>0, and for a conditionally heteroscedastic error term, the test described here is applicable in a variety of situations where such popular tests as the Box-Pierce (1970) test, Durbin's (1970) h test, and Godfrey's (1978b) Lagrange multiplier test are net applicable. The finite sample properties of the test are examined in Monte Carlo simulations where, with a sample sizes of 50 and 100 observations, the test appears to be quite reliable.
主题Econometrics
URLhttps://www.nber.org/papers/t0092
来源智库National Bureau of Economic Research (United States)
引用统计
资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/560750
推荐引用方式
GB/T 7714
Robert E. Cumby,John Huizinga. Testing The Autocorrelation Structure of Disturbances in Ordinary Least Squares and Instrumental Variables Regressions. 1990.
条目包含的文件
文件名称/大小 资源类型 版本类型 开放类型 使用许可
t0092.pdf(2015KB)智库出版物 限制开放CC BY-NC-SA浏览
个性服务
推荐该条目
保存到收藏夹
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Robert E. Cumby]的文章
[John Huizinga]的文章
百度学术
百度学术中相似的文章
[Robert E. Cumby]的文章
[John Huizinga]的文章
必应学术
必应学术中相似的文章
[Robert E. Cumby]的文章
[John Huizinga]的文章
相关权益政策
暂无数据
收藏/分享
文件名: t0092.pdf
格式: Adobe PDF
此文件暂不支持浏览

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。