This paper shows that convexity of the short-run Phillips curve is a source of positive inflation bias even when policymakers target the natural unemployment rate, that is when they operate with prudent discretion, and their loss function is symmetric. Optimal monetary policy also induces positive co-movement between average inflation, average unemployment and inflation variability-suggesting a new motive for inflation stabilization policy-and positively skewed unemployment distributions. The reduced form model is applied to the post-disinflation period (1986-2006) in developed countries and its properties are illustrated numerically for the United States.
At what forecast horizon is one time series more predictable than another? This paper applies the Diebold-Kilian conditional predictability measure to assess the out-of-sample performance of three alternative models of daily GBP/USD and DEM/USD exchange rate returns. Predictability is defined as a non-linear statistic of a model's relative expected losses at short and long forecast horizons, allowing flexible choice of both the estimation procedure and loss function. The long horizon is set to 2 weeks and one month ahead and forecasts evaluated according to MSE loss. Bootstrap methodology is used to estimate the data's conditional predictability using GARCH models. This is then compared to predictability under a random walk and a model using the prediction bias in uncovered interest parity (UIP). We find that both exchange rates are less predictable using GARCH than using a random walk, but they are more predictable using UIP than a random walk. Predictability using GARCH is relatively higher for the 2-weeks-than for the 1-month long forecast horizon. Comparing the results using a random walk to that using UIP reveals 'pockets' of predictability, that is, particular short horizons for which predictability using the random walk exceeds that using UIP, or vice versa. Overall, GBP/USD returns appear more predictable than DEM/USD returns at short horizons.
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