Several Bayesian model combination schemes, including some novel approaches that simultaneously allow for parameter uncertainty, model uncertainty and robust time varying model weights, are compared in terms of forecast accuracy and economic gains using financial and macroeconomic time series....

This paper considers spot variance path estimation from datasets of intraday high frequency asset prices in the presence of diurnal variance patterns, jumps, leverage effects and microstructure noise. We rely on parametric and nonparametric methods. The estimated spot variance path can be used...

We analyze the economic forces underlying cross-border Mergers and Acquistions (M&As) using a large bilateral panel data set. The frequent occurrence of zero observations provides essential information on the structure of M&A flows, which we model empirically using a two-stage procedure. At the...

By combining two large data sets (on international trade flows and cross-border mergers and acquisitions - M&As), we test two implications of Neary’s (2003, 2007) general oligopolistic equilibrium (GOLE) model (incorporating strategic interaction between firms in a general equilibrium...

In this paper we investigate whether the dynamic properties of the U.S. business cycle have changed in the last fifty years. For this purpose we develop a flexible business cycle indicator that is constructed from a moderate set of macroeconomic time series. The coincident economic indicator is...