Abstract
We consider a test based on quantile regressions to verify the presence of conditional heteroskedasticity. The test does not rely on distributional assumptions of the errors, nor on a function describing the pattern of heteroskedasticity. It compares the slope coefficients of the regressions computed at different quantiles. Under homoskedasticity, different regression quantiles yield parallel hyperplanes, and the slope coefficients are not significantly different from one quantile to the other. This is not the case when heteroskedasticity occurs. A Monte Carlo study is implemented in order to verify the behavior of this class of tests for conditional heteroskedasticity based on quantile regressions.
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