We propose a novel observation-driven dynamic finite mixture model for the study of banking data. The model accommodates time-varying component means and covariance matrices, normal and Student's $t$ distributed mixtures, and economic determinants of time-varying parameters. Monte Carlo...

Digital technologies have led to the emergence of many platforms in our economy today. In certain platform networks, buyers in one market purchase services from providers in many other markets, whereas other platform networks may comprise local clusters in which buyers primarily purchase...

Analyses of spatial or network data are now very common. Nevertheless, statistical inference is challenging since unobserved heterogeneity can be correlated across neighboring observational units. We develop an estimator for the variance-covariance matrix (VCV) of OLS and 2SLS that allows for...

We estimate the distribution of marginal propensities to consume (MPCs) using a new approach based on the fuzzy C-means algorithm (Dunn 1973; Bezdek 1981). The algorithm generalizes the K-means methodology of Bonhomme and Manresa (2015) to allow for uncertain group assignment and to recover...