Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/149778
Authors: 
Jochmans, Koen
Weidner, Martin
Year of Publication: 
2016
Series/Report no.: 
cemmap working paper, Centre for Microdata Methods and Practice CWP32/16
Abstract: 
This paper studies inference on fixed effects in a linear regression model estimated from network data. We derive bounds on the variance of the fixed-effect 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-effect estimator.
Subjects: 
fixed effects
graph
Laplacian
network data
variance bound
JEL: 
C23
C55
Document Type: 
Working Paper

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