论文信息 - A Consistent Nonparametric Test of Symmetry in Linear Regression Models

A Consistent Nonparametric Test of Symmetry in Linear Regression Models

Abstract This article proposes a consistent nonparametric test of the hypothesis that the disturbance in a linear regression model is distributed symmetrically around zero. Simulation results show that the test has good size and power properties for sample sizes as small as 50. We illustrate the use of the test in a cross-country model of inflation and monetary growth.

Yanqin Fan | Ramazan Gençay

[1] G. Belle,et al. Measuring Affinity of Distributions , 1973 .

[2] I. Ahmad. Nonparametric estimation of an affinity measure between two absolutely continuous distributions with hypotheses testing applications , 1980 .

[3] Whitney K. Newey,et al. Adaptive estimation of regression models via moment restrictions , 1988 .

[4] J. Marron. Automatic smoothing parameter selection: A survey , 1988 .

[5] P. Robinson. Consistent Nonparametric Entropy-Based Testing , 1991 .

[6] P. Bickel. On Adaptive Estimation , 1982 .

[7] E. F. Schuster. Estimation of a Probability Density Function and Its Derivatives , 1969 .

[8] Glenn M. MacDonald,et al. Some Large-Sample Tests for Nonnormality in the Linear Regression Model , 1980 .

[9] Hypotheses testing based on modified nonparametric estimation of an affinity measure between two distributions , 1993 .

[10] Roger Koenker,et al. A note on studentizing a test for heteroscedasticity , 1981 .

[11] Vincent N. LaRiccia,et al. Testing goodness of fit via nonparametric function estimation techniques , 1993 .