Some Properties of Tests for Specification Error in a Linear Regression Model
作者:
JerryG. Thursby,
Peter Schmidt,
期刊:
Journal of the American Statistical Association
(Taylor Available online 1977)
卷期:
Volume 72,
issue 359
页码: 635-641
ISSN:0162-1459
年代: 1977
DOI:10.1080/01621459.1977.10480627
出版商: Taylor & Francis Group
关键词: Approximate doubly noncentralFdistribution;Incorrect functional form;Monte Carlo experiment;Omitted variables;reset;Specification-error tests
数据来源: Taylor
摘要:
This article considers the test reset which is intended to detect a nonzero mean of the disturbance in a linear regression model. Analysis of an approximation to the test statistic's distribution and Monte Carlo experiments reveal that the power of the test may decline as the size of the disturbance mean increases. However, the possibility is remote and declines with increasing sample size. Alternative sets of test variables are considered, and their effect on the power of the test is studied in Monte Carlo experiments. The best set seems to be composed of powers of the explanatory variables.
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