We show that using data which are properly available in real time when assessing the sensitivity of asset prices to economic news leads to different empirical findings that when data availability and timing issues are ignored. We do this by focusing on a particular example, namely Chen, Roll and...

We examine the prevalence of data, specification, and parameter uncertainty in the formation of simple rules which mimic monetary policy-making decisions. Our approach is to build real-time datasets, simulate a real-time policy-setting environment, and provide a set of prescriptions and...

In this paper we construct output gap and inflation predictions using a variety of dynamic stochastic general equilibrium (DSGE) sticky price models. Predictive density accuracy tests related to the test discussed in Corradi and Swanson ["Journal of Econometrics" (2005a), forthcoming] as well as...

We take a model selection approach to the question of whether a class of adaptive prediction models (artificial neural networks) is useful for predicting future values of nine macroeconomic variables. We use a variety of out-of-sample forecast-based model selection criteria, including forecast...

In this paper we examine the extent to which fluctuations in a number of macroeconomic variables impact on the volume of federal litigation cases. In particular, the impact of aggregate U.S. GDP, consumption, inflation, unemployment, and interest rates on the volume of antitrust, bankruptcy,...

Various inflation forecasting models are compared using a simulated out-of-sample forecasting framework. We focus on the question of whether monetary aggregates are useful for forecasting inflation, but unlike previous work we examine a wide range of forecast horizons and allow for estimated as...