Email            eric.auerbach [at]        

Cell               (845) 797-8632                       

Address       University of California, Berkeley
                     Department of Economics
                     530 Evans #3880
                     Berkeley, CA 94720-3880

I am a PhD candidate in Economics at UC Berkeley. 

My research interests are in Econometrics and Network Economics.

I will be available for interviews at the AEA/ASSA Annual Meeting in Chicago (January 6-8, 2017)

Job Market Paper 

I study a linear model in which the regressors and errors covary with drivers of link formation in a large network. Neither the endogenous relationship nor the distribution of network links are restricted parametrically. Instead, the model is identified by variation in the regressors unexplained by the distribution of network links. I propose a new semiparametric estimator based on matching pairs of agents with similar columns of the squared adjacency matrix, the ijth entry of which contains the number of other agents linked to both agents i and j. I find sufficient conditions for the estimator to be consistent and asymptotically normal, and provide a consistent estimator for its asymptotic variance. While this paper focuses on cases in which the network is represented by a binary, symmetric, and square adjacency matrix, I also discuss extensions to weighted, directed, bipartite, multiple, sampled, and higher-order networks.

Work in Progress