A Heteroskedasticity Test Robust to Conditional Mean Misspecification
A Heteroskedasticity Test Robust to Conditional Mean Misspecification
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对条件均值错误指定具有鲁棒性的异方差检验
DOI：
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发表时间：
1992
期刊：
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通讯作者：
Byung
中科院分区：
文献类型：
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作者：
Byung
本文提出了一种新的检验统计量，以确定异方差的存在。所提出的检验不需要在第一阶段回归中对均值回归函数进行参数化。用核估计方法对回归函数进行非参数估计。非参数残差估计，并作为随机干扰项的代理。这种非参数残差对回归函数的误设定具有鲁棒性。利用经典U统计量定理的推广建立了渐近正态性。检验统计量是使用非参数量计算的，但由此产生的推断具有标准卡方分布。版权所有1992年由计量经济学会。
This paper proposes a new test statistic to deter the presence of heteroskedasticity. The proposed test does not require a parametric specification of the mean regression function in the first stage regression. The regression function is estimated nonparametrically by the kernel estimation method. The nonparametric residual is estimated and used as a proxy for the random disturbance term. This nonparametric residual is robust to regression function misspecification. Asymptotic normality is established using extensions of classical U-statistic theorems. The test statistic is computed using the nonparametric quantities, but the resulting inference has a standard chi-square distribution. Copyright 1992 by The Econometric Society.