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...

The pandemic that erupted in 2020 generated a significant increase in public debt, which is likely to draw the attention of economic policy and the economic profession to the evolution and sustainability of debt. This study first shows how the gross sovereign nominal consolidated government debt...

We apply a functional data approach for mixture model-based multivariate innovation clustering to identify different regional innovation portfolios in Europe, considering patterns of specialization among innovation types. We combine patent registration data and other innovation and economic data...

In linear regression analysis, the estimator of the variance of the estimator of the regression coefficients should take into account the clustered nature of the data, if present, since using the standard textbook formula will in that case lead to a severe downward bias in the standard errors....