This paper studies panel data models with interactive fixed effects where the regressors are
allowed to be correlated with the idiosyncratic error terms. We propose a two-step profile …

This paper studies high-dimensional vector autoregressions (VARs) augmented with
common factors that allow for strong cross-sectional dependence. Models of this type …

We consider estimation and inference for a regression coefficient in panels with interactive
fixed effects (ie, with a factor structure). We show that previously developed estimators and …

This paper studies uniform inference in a linear panel data model when the slope
coefficients may exhibit heterogeneity over both the individual and time dimensions and they …

This paper studies large N and large T conditional quantile panel data models with
interactive fixed effects. We propose a nuclear norm penalized estimator of the coefficients …

This paper analyzes a semiparametric model of network formation in the presence of
unobserved agent-specific heterogeneity. The objective is to identify and estimate the …

In this paper, we propose a class of low-rank panel quantile regression models which allow
for unobserved slope heterogeneity over both individuals and time. We estimate the …

This paper considers a linear panel model with interactive fixed effects and unobserved
individual and time heterogeneities that are captured by some latent group structures and an …

Recent years have seen a growing array of activities in developing statistical models for
modelling real‐life networks. Since many of these networks are sparse, an all too often …

This paper considers a network formation model when links are potentially misclassified. We
focus on a game-theoretical model of strategic network formation with incomplete …