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Real-time inflation forecasting in a changing world
This paper revisits the accuracy of inflation forecasting using activity and expectations variables. We apply Bayesian-model averaging across different regression specifications selected from a set of potential predictors that includes lagged values of inflation, a host of real activity data, term structure data, nominal data, and surveys. In this model average, we can entertain different channels of structural instability by incorporating stochastic breaks in the regression parameters of each individual specification within this average, allowing for breaks in the error variance of the ...