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 paper analyzes the conditions under which consistent estimation can be achieved in instrumental variables (IV) regression when the available instruments are weak and the number of instruments, K_n, goes to infinity with the sample size. We show that consistent estimation depends importantly...

This paper develops Wald-type tests for general (possibly nonlinear) restrictions in the context of a weakly-identified heteroskedastic IV regression. In particular, it is first shown that, in a framework with many weak instruments, consistency and asymptotic normality can be obtained when...

In this paper we take an agnostic view of the Phillips curve debate, and carry out an empirical investigation of the relative and absolute efficacy of Calvo sticky price (SP), sticky information (SI), and sticky price with indexation models (SPI), with emphasis on their ability to mimic...