Time series data are a collection of chronological observations which are generated by
several domains such as medical and financial fields. Over the years, different tasks such as …

Randomized experiments are a powerful methodology for data-driven evaluation of
decisions or interventions. Yet, their validity may be undermined by network interference …

The interaction of economic agents is one of the most important elements in economic
analyses. Social interactions on subjective outcomes, behavior, or decisions, are inherently …

This paper studies nonparametric estimation of treatment and spillover effects using
observational data from a single large network. We consider a model in which interference …

We identify and estimate heterogeneous social effects within groups of individuals that make
binary choices. These heterogeneous social effects, which include peer and contextual …

This paper studies the uniqueness of a quantal response equilibrium (QRE) in a broad class
of n-person normal form games. We make three main contributions. First, we show that the …

Despite the growing interest in causal and statistical inference for settings with data
dependence, few methods currently exist to account for missing data in dependent data …

This paper studies estimation and inference in a dyadic network formation model with
observed covariates, unobserved heterogeneity, and nontransferable utilities. With the …

Accurate estimation of treatment effects is essential for decision-making across various
scientific fields. This task, however, becomes challenging in areas like social sciences and …

Nonprogressive diffusion describes the dissemination of behavior on a social network,
where the agents are allowed to reverse their decisions as time evolves. It has a wide variety …