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Conditional term structure of inflation forecast uncertainty: the copula approach
The paper introduces the concept of conditional inflation forecast uncertainty. It is proposed that the joint and conditional distributions of the bivariate forecast uncertainty can be derived from estimation unconditional distributions of these uncertainties and applying appropriate copula function. Empirical results have been obtained for Canada and US. Term structure has been evaluated in the form of unconditional and conditional probabilities of hitting the inflation range of ±1% around the Canadian inflation target. The paper suggests a new measure of inflation forecast uncertainty that accounts for possible inter-country dependence. It is shown that evaluation of targeting precision can be effectively improved with the use of ex-ante formulated conditional and unconditional probabilities of inflation being within the pre-defined band around the target.