This discussion paper resulted in a publication in the <I>Journal of Corporate Finance</I> (2011). Vol. 17, issue 5.<P> This paper analyzes the impact of blockownership dispersion on firm value. Blockholdings by multiple blockholders is a widespread phenomenon in the U.S. market. It is not clear, however,...</p></i>

This discussion paper resulted in an article in the <I>Journal of Empirical Finance</I> (2009). Vol. 16, issue 1, pages 42-54.<P> We study the relation between the credit cycle and macro-economic fundamentals in an intensity-based framework. Using rating transition and default data of U.S. corporates from...</p></i>

We introduce a new model for time-varying spatial dependence. The model extends the well-known static spatial lag model. All parameters can be estimated conveniently by maximum likelihood. We establish the theoretical properties of the model and show that the maximum likelihood estimator for the...

This paper has been accepted for publication in the 'Review of Economics and Statistics'.We propose a dynamic factor model for mixed-measurement and mixed-frequency panel data. In this framework time series observations may come from a range of families of parametric distributions, may be...

We propose a new semiparametric observation-driven volatility model where the form of the error density directly influences the volatility dynamics. This feature distinguishes our model from standard semiparametric GARCH models. The link between the estimated error density and the volatility...

We test whether asymmetric preferences for losses versus gains as in Ang, Chen, and Xing (2006) also affect the pricing of cash flow versus discount rate news as in Campbell and Vuolteenaho (2004). We construct a new four-fold beta decomposition, distinguishing cash flow and discount rate betas...

We propose a new model for dynamic volatilities and correlations of skewed and heavy-tailed data. Our model endows the Generalized Hyperbolic distribution with time-varying parameters driven by the score of the observation density function. The key novelty in our approach is the fact that the...

We determine the importance of long-term and short-term components of state variables for asset allocation decisions. The long-term and short-term decompositions are performed using a variety of filtering techniques. We allow for a flexible semiparametric form of the dependence of asset...

We propose a dynamic factor model for mixed-measurement and mixed-frequency panel data. In this framework time series observations may come from a range of families of parametric distributions, may be observed at different time frequencies, may have missing observations, and may exhibit common...

We introduce a new efficient importance sampler for nonlinear non-Gaussian state space models. By combining existing numerical and Monte Carlo integration methods, we obtain a general and efficient likelihood evaluation method for this class of models. Our approach is based on the idea that only...