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3 | Juan Estrada

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Estimating Social Effects with Randomized and Observational Network Data

This paper proposes a novel method to identify and estimate the parameters of interest in the popular so-called linear-in-means regression model in situations where initial randomization of peers induces the observed network of interest. We argue …

Estimating Network Effects and Their Impact on Congressional Polarization

This paper introduces a novel approach to identifying and estimating parameters in a model where legislators choose their expressed political ideology based on roll-call votes. We consider various professional connections, including cosponsorship, …

Legislative Activity Relational Database: A New Open Source Database to Answer Questions about Legislative Politics

Scholars interested in legislative studies typically use observable outcomes such as roll-call votes (RCVs), speeches, and campaign contributions to quantify latent aspects of legislative behavior, such as ideal points, party unity levels, and …

Bayesian Inference of Network Formation Models with Payoff Externalities

This paper provides a novel approach to identification and estimation of a network formation model using observed network data, where the model acknowledges possible externalities in agents' utilities of forming connections with one another. The …

netivreg: Estimation of Peer Effects in Endogenous Social Networks

The command netivreg implements the Generalized Three-Stage Least Squares (G3SLS) estimator developed in Estrada et al. (2020), On the Identification and Estimation of Endogenous Peer Effects in Multiplex Networks) and the Generalized Method of …

Social Interactions in Multilayered Observational Networks

This paper proposes a new method to identify and estimate the parameters of an extension of a linear model of peer effects where individuals form different types of social and professional connections that can affect their outcomes. A stylized model …