conditional heteroskedasticity. We show that the wild bootstrap provides convenient critical values for the considered OLS …-based statistics under both homoskedastic and conditionally heteroskedastic model errors. The wild bootstrap is easy to implement and … approximations. We prove further that the wild bootstrap retains its validity for inference within a system of pooled equations …

In this paper we introduce a bootstrap procedure to test parameter restrictions in vector autoregressive models which … is robust in cases of conditionally heteroskedastic error terms. The adopted wild bootstrap method does not require any … Monte Carlo investigation empirical size and power properties of the new method are illustrated. We compare the bootstrap …