 The wild bootstrap, proposed originally by Wu (1986), is suited when the model exhibits heteroskedasticity.The idea is, like the residual bootstrap, to leave the regressors at their sample value, but to resample the response variable based on the residuals values.That is, for each replicate, one computes a new formula_57 based on

so the residuals are randomly multiplied by a random variable formula_59 with mean 0 and variance 1.