Testing for Nonlinearity in Mean in the Presence of Heteroskedasticity

This paper considers an important practical problem in testing time-series data for nonlinearity in mean, namely, the distortion in the size of the test encountered if the the data are heteroskedastic. It is shown that using a heteroskedastic consistent auxiliary regression together with the wild bootstrap is an e®ective way of dealing with the problem. Simulation results indicate that signi¯cant improvements in empirical size are obtained, particularly in small samples.nonlinearity in mean, heteroskedasticity, wild bootstrap, empirical size and power