The GMM estimator that is usually employed in the panel data literature, has an unbounded influence function. This means that the estimator is easily influenced by outliers in the data. This paper develops a variant of the GMM estimator that is less sensitive to anomalous observations....

We introduce a new fractionally integrated model for covariance matrix dynamics based on the long-memory behavior of daily realized covariance matrix kernels and daily return observations. We account for fat tails in both types of data by appropriate distributional assumptions. The covariance...

We introduce a new dynamic clustering method for multivariate panel data char- acterized by time-variation in cluster locations and shapes, cluster compositions, and, possibly, the number of clusters. To avoid overly frequent cluster switching (flickering), we extend standard cross-sectional...

Multiple blockholder structures are a widespread phenomenon in the U.S. The theoretical literature, however, provides conflicting predictions on whether a single large blockholder or a set of dispersed smaller blockholders is better for firm value. Using U.S. data, we find a negative...

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...