We take a model selection approach to real-time macroeconomic forecasting using linear and nonlinear models. True ex-ante forecasting are constructed by using unrevised as opposed to fully revised data. Model selection as well as model performance measures are considered.

Data on monetary aggregates are subject to periodic redefinitions, presumably in part to improve their link to measures of output. Money data are also revised on a regular basis. Taking these data imperfections into account, we reassess the evidence on the marginal predictive content of M1 and...

In this paper, we add to the literature on the assessment of how well data simulated from new-Keynesian dynamic stochastic general equilibrium (DSGE) models reproduce the dynamic features of historical data. In particular, we evaluate sticky price, sticky price with dynamic indexation, and...

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 than when data availability and timing issues are ignored. We do this by focusing on a particular example, namely Chen, Roll and...

This chapter discusses estimation, specification testing, and model selection of predictive density models. In particular, predictive density estimation is briefly discussed, and a variety of different specification and model evaluation tests due to various authors including Christoffersen and...