BOOTSTRAP UNIT ROOT TESTS FOR TIME SERIES WITH NONSTATIONARY VOLATILITY

The presence of permanent volatility shifts in key macroeconomic and financial variables in developed economies appears to be relatively common+ Conventional unit root tests are unreliable in the presence of such behavior, having nonpivotal asymptotic null distributions+ In this paper we propose a bootstrap approach to unit root testing that is valid in the presence of a wide class of permanent variance changes that includes single and multiple ~abrupt and smooth transition! volatility change processes as special cases+ We make use of the so-called wild bootstrap principle, which preserves the heteroskedasticity present in the original shocks+ Our proposed method does not require the practitioner to specify any parametric model for the volatility process+ Numerical evidence suggests that the bootstrap tests perform well in finite samples against a range of nonstationary volatility processes+