This paper reexamines the forecasting ability of Phillips curves from both an unconditional and conditional perspective … tend to be unconditionally inferior to those from our univariate forecasting models. We also find, however, that …

The Phillips curve has long been used as a foundation for forecasting inflation. Yet numerous studies indicate that … over the past 20 years or so, inflation forecasts based on the Phillips curve generally do not predict inflation any better … than a univariate forecasting model. In this paper, the authors take a deeper look at the forecasting ability of Phillips …

literature by considering a local approximation around a zero inflation steady state and introducing idiosyncratic shocks. The …

policy, examine the forecast performance in terms of bias and effciency, and explore the implications for the interaction of …

This paper proposes new methodologies for evaluating out-of-sample forecasting performance that are robust to the … choice of the estimation window size. The methodologies involve evaluating the predictive ability of forecasting models over … application shows the usefulness of the methodologies for evaluating exchange rate models' forecasting ability. …

for U.S. output, inflation, and the rate of unemployment. Drawing on both the Bayesian VAR and vector error corrections … (VEC) literature, the author specifies the baseline model as a Bayesian VEC. The author documents the model's forecasting … promise as a workhorse forecasting tool. …

robustness of published econometric results, for analyzing policy, and for forecasting. The data set consists of vintages, or …

Vector-autoregression (VAR) forecast models have been developed for many state economies, including the three states in … Bayesian VAR forecast model for the Philadelphia metropolitan area and the city of Philadelphia. …

optimal forecast is biased under asymmetric loss and that the conditionally optimal amount of bias is time-varying in general …