Work on testing for bubbles has caused much debate, much of which has focussed on methodology. Monte Carlo simulations reported in Evans (1991) showed that standard tests for unit roots and cointegration frequently reject the presence of bubbles even when such bubbles are present by construction. Evans referred to this problem as the pitfall of testing for bubbles.
The purpose of this study is to test the hypothesis that inflation uncertainty increases at higher levels of inflation. Our analysis is based on the generalized autoregressive conditional heteroscedasticity (GARCH) class of models, which allow the conditional variance of the error term to be time-varying. Since this variance is a proxy for inflation uncertainty, a positive relationship between the conditional variance and inflation would be interpreted as evidence that inflation uncertainty increases with the level of inflation.