Candelaria, Luis E. (2020) A semiparametric network formation model with unobserved linear heterogeneity. Working Paper. Coventry, UK: University of Warwick. Department of Economics. Warwick economics research papers series (WERPS) (1279). (Unpublished)

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Abstract

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 preference parameters associated with homophily on observed attributes when the distributions of the unobserved factors are not parametrically specified. This paper offers two main contributions to the literature on network formation. First, it establishes a new point identification result for the vector of parameters that relies on the existence of a special regressor. The identification proof is constructive and characterizes a closed-form for the parameter of interest. Second, it introduces a simple two-step semiparametric estimator for the vector of parameters with a first-step kernel estimator. The estimator is computationally tractable and can be applied to both dense and sparse networks. Moreover, I show that the estimator is consistent and has a limiting normal distribution as the number of individuals in the network increases. Monte Carlo experiments demonstrate that the estimator performs well in finite samples and in networks with different levels of sparsity.

Item Type:	Working or Discussion Paper (Working Paper)
Subjects:	H Social Sciences > HB Economic Theory H Social Sciences > HM Sociology Q Science > QA Mathematics
Divisions:	Faculty of Social Sciences > Economics
Library of Congress Subject Headings (LCSH):	Social networks, Econometrics, Mathematical statistics, Regression analysis
Series Name:	Warwick economics research papers series (WERPS)
Publisher:	University of Warwick. Department of Economics
Place of Publication:	Coventry, UK
ISSN:	0083-7350
Official Date:	July 2020
Dates:	Date Event July 2020 Available
Number:	1279
Institution:	University of Warwick
Status:	Not Peer Reviewed
Publication Status:	Unpublished
Access rights to Published version:	Open Access
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