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摘要:
The presence of heteroskedasticity in a considered regression model may bias the standard deviations of parameters obtained by the Ordinary Least Square (OLS) method. In this case, several hypothesis tests on the model under consideration may be biased, for example, CHOW’s coefficient stability test (or structural change test), Student’s t-test and Fisher’s F-test. Most of the heteroscedasticity tests in the literature are based on the comparison of variances. Despite the multiplication of equality tests of coefficients of variation (CVs) that have appeared in the literature, to our knowledge, the first and only use of the coefficient of variation in the detection of heteroskedasticity was offered by Li and Yao in 2017. Thus, this paper offers an approach to determine the existence of heteroskedasticity by a test of equality of coefficients of variation. We verify by a Monte Carlo robustness and performance test that our method seems even better than some tests in the literature. The results of this study contribute to the exploitation of the statistical measurement of CV dispersion. They help technicians economists to better verify their hypotheses before making a scientific decision when making a necessary forecast, in order to contribute effectively to the economic and sustainable development of a company or enterprise.
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篇名 Application of Equality Test of Coefficients of Variation to the Heteroskedasticity Test
来源期刊 美国计算数学期刊(英文) 学科 数学
关键词 HETEROSKEDASTICITY Tests EQUALITY TEST COEFFICIENTS of VARIATION Ordinary Least Square (OLS) Method Linear Regression Analysis of Variance (ANOVA)
年,卷(期) 2020,(1) 所属期刊栏目
研究方向 页码范围 73-89
页数 17页 分类号 O17
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HETEROSKEDASTICITY
Tests
EQUALITY
TEST
COEFFICIENTS
of
VARIATION
Ordinary
Least
Square
(OLS)
Method
Linear
Regression
Analysis
of
Variance
(ANOVA)
研究起点
研究来源
研究分支
研究去脉
引文网络交叉学科
相关学者/机构
期刊影响力
美国计算数学期刊(英文)
季刊
2161-1203
武汉市江夏区汤逊湖北路38号光谷总部空间
出版文献量(篇)
355
总下载数(次)
1
总被引数(次)
0
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