This paper introduces a new factor structure suitable for modeling large realized covariance matrices with full likelihood based estimation. Parametric and nonparametric versions are introduced. Due to the computational advantages of our approach we can model the factor nonparametrically as a...

This paper proposes a flexible way of modeling dynamic heterogeneous covariance breakdowns in multivariate GARCH (MGARCH) models. During periods of normal market activity, volatility dynamics are governed by an MGARCH specification. A covariance breakdown is any significant temporary deviation...

This article studies the negative signals associated with non-promotion. I first show theoretically that, when workers’ productivity rises little with additional years on the same job level, the negative signal associated with non-promotion leads to wage decreases. On the other hand, when...

This article studies the consequences of firm delayering on wages and the wage distribution inside firms. I consider a job-assignment model with asymmetric information and a slot constraint. The model predicts that more efficient firms are not necessarily larger than less efficient firms if...

This article studies the negative signals associated with non-promotion. I first show theoretically that, when workers’ productivity rises little with additional years on the same job level, the negative signal associated with non-promotion leads to wage decreases. On the other hand, when...

This paper introduces several new Bayesian nonparametric models suitable for capturing the unknown conditional distribution of realized covariance (RCOV) matrices. Existing dynamic Wishart models are extended to countably infinite mixture models of Wishart and inverse-Wishart distributions. In...