A test of normality using nonparametrlic residuals |
| |
Authors: | Yoon-Jae Whang |
| |
Institution: |
a Department of Economics, Ewha University, Korea |
| |
Abstract: | In this paper, we develop a test of the normality assumption of the errors using the residuals from a nonparametric kernel regression. Contrary to the existing tests based on the residuals from a parametric regression, our test is thus robust to misspecification of the regression function. The test statistic proposed here is a Bera-Jarque type test of skewness and kurtosis. We show that the test statistic has the usual x2(2) limit distribution under the null hypothesis. In contrast to the results of Rilstone (1992), we provide a set of primitive assumptions that allow weakly dependent observations and data dependent bandwidth parameters. We also establish consistency property of the test. Monte Carlo experiments show that our test has reasonably good size and power performance in small samples and perfornu better than some of the alternative tests in various situations. |
| |
Keywords: | Nonparametric kernel estimator Normality test Skewness Ihrtosis Empirical process |
本文献已被 InformaWorld 等数据库收录! |