This paper considers linear panel data models with a grouped pattern of heterogeneity
when the latent group membership structure and/or the values of slope coefficients change …

Individuals or companies in a large social or financial network often display rather
heterogeneous behaviors for various reasons. In this work, we propose a network vector …

This paper provides a framework for joint estimation and identification of latent group
structures in panel data models using a pairwise fusion penalized approach. The latent …

The present special issue features a collection of papers presented at the 2017 International
Panel Data Conference, hosted by the University of Macedonia in Thessaloniki, Greece. The …

In this paper, we consider the least squares estimation of a panel structure threshold
regression (PSTR) model where both the slope coefficients and threshold parameters may …

We develop a procedure to identify latent group structures in linear panel data models that
exploits a grou** in the error variances of cross-sectional units. To accommodate such …

In this work, we study the event occurrences of individuals interacting in a network. To
characterize the dynamic interactions among the individuals, we propose a group network …

This paper provides a new multi-dimensional clustering approach for unobserved
heterogeneity in panel data models. Each unit is associated with multiple clusters. For …

This paper considers estimating the slope parameters and forecasting in potentially
heterogeneous panel data regressions with a long time dimension. We propose a novel …

While the Vector Autoregression (VAR) model has received extensive attention for modelling
complex time series, quantile VAR analysis remains relatively underexplored for high …