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.
Decomposing U.S. Nominal Interest Rates into Expected Inflation and Ex Ante Real Interest Rates Using Structural VAR MethodologyIn this paper, the author uses structural vector autoregression methodology to decompose U.S. nominal interest rates into an expected inflation component and an ex ante real interest rate component. He identifies inflation expectations and ex ante real interest rate shocks by assuming that nominal interest rates and inflation expectations move one-for-one in the long-run—they are cointegrated (1,1)—and that the real interest rate is stationary.