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Fixed-effect regressions on network data

Authors: Koen Jochmans and Martin Weidner
Date: 08 August 2016
Type: cemmap Working Paper, CWP32/16
DOI: 10.1920/wp.cem.2016.3216

Abstract

This paper studies inference on fixed eff ects in a linear regression model estimated from network data. We derive bounds on the variance of the fixed-e ffect estimator that uncover the importance of the smallest non-zero eigenvalue of the (normalized) Laplacian of the network and of the degree structure of the network. The eigenvalue is a measure of connectivity, with smaller values indicating less-connected networks. These bounds yield conditions for consistent estimation and convergence rates, and allow to evaluate the accuracy of first-order approximations to the variance of the fixed-eff ect estimator.

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Koen Jochmans and Martin Weidner May 2017, Fixed-effect regressions on network data, cemmap Working Paper, CWP26/17, The IFS

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