[HTML][HTML] Estimation of panel group structure models with structural breaks in group memberships and coefficients
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 …
when the latent group membership structure and/or the values of slope coefficients change …
Simultaneous estimation and group identification for network vector autoregressive model with heterogeneous nodes
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 …
heterogeneous behaviors for various reasons. In this work, we propose a network vector …
Celebrating 40 years of panel data analysis: Past, present and future
V Sarafidis, T Wansbeek - Journal of Econometrics, 2021 - Elsevier
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 …
Panel Data Conference, hosted by the University of Macedonia in Thessaloniki, Greece. The …
Panel threshold regressions with latent group structures
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 …
regression (PSTR) model where both the slope coefficients and threshold parameters may …
[PDF][PDF] Clustering for multi-dimensional heterogeneity
X Cheng, F Schorfheide, P Shao - 2019 - colorado.edu
This paper provides a new multi-dimensional clustering approach for unobserved
heterogeneity in panel data models. Each unit is associated with multiple clusters. For …
heterogeneity in panel data models. Each unit is associated with multiple clusters. For …
Estimation and identification of latent group structures in panel data
A Mehrabani - Journal of Econometrics, 2023 - Elsevier
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 …
structures in panel data models using a pairwise fusion penalized approach. The latent …
[PDF][PDF] Unobserved clusters of time-varying heterogeneity in nonlinear panel data models
M Mugnier - Job Market Paper, 2022 - congress-files.s3.amazonaws.com
In non-experimental longitudinal studies, researchers often estimate causal effects
assuming time-constant unobserved heterogeneity or linear-in-parameters conditional …
assuming time-constant unobserved heterogeneity or linear-in-parameters conditional …
To pool or not to pool: What is a good strategy for parameter estimation and forecasting in panel regressions?
This paper considers estimating the slope parameters and forecasting in potentially
heterogeneous panel data regressions with a long time dimension. We propose a novel …
heterogeneous panel data regressions with a long time dimension. We propose a novel …
Two-way Homogeneity Pursuit for Quantile Network Vector Autoregression
While the Vector Autoregression (VAR) model has received extensive attention for modelling
complex time series, quantile VAR analysis remains relatively underexplored for high …
complex time series, quantile VAR analysis remains relatively underexplored for high …
Detecting latent communities in network formation models
This paper proposes a logistic undirected network formation model which allows for
assortative matching on observed individual characteristics and the presence of edge-wise …
assortative matching on observed individual characteristics and the presence of edge-wise …