Identifying Network Ties from Panel Data: Theory and an Application to Tax Competition

81 Pages Posted: 20 Mar 2018 Last revised: 23 Oct 2019

See all articles by Aureo de Paula

Aureo de Paula

University College London - Department of Economics

Imran Rasul

University College London - Department of Economics; Centre for Economic Policy Research (CEPR); IZA Institute of Labor Economics

Pedro Souza

Pontificia Universidad Catolina

Multiple version iconThere are 2 versions of this paper

Date Written: March 2018

Abstract

Social interactions determine many economic behaviors, but information on social ties does not exist in most publicly available and widely used datasets. We present results on the identification of social networks from observational panel data that contains no information on

social ties between agents. In the context of a canonical social interactions model, we provide sufficient conditions under which the social interactions matrix, endogenous and exogenous social effect parameters are all globally identified. While this result is relevant across different

estimation strategies, we then describe how high-dimensional estimation techniques can be used to estimate the interactions model based on the Adaptive Elastic Net GMM method. We employ the method to study tax competition across US states. We find the identified social interactions matrix implies tax competition differs markedly from the common assumption of competition between geographically neighboring states, providing further insights for the long-standing debate on the relative roles of factor mobility and yardstick competition in driving tax setting behavior across states. Most broadly, our identification and application show the analysis of social interactions can be extended to economic realms where no network data exists.

Suggested Citation

de Paula, Aureo and Rasul, Imran and Souza, Pedro, Identifying Network Ties from Panel Data: Theory and an Application to Tax Competition (March 2018). Available at SSRN: https://ssrn.com/abstract=3143442

Aureo De Paula (Contact Author)

University College London - Department of Economics ( email )

Gower Street
London WC1E 6BT, WC1E 6BT
United Kingdom

Imran Rasul

University College London - Department of Economics ( email )

Gower Street
London WC1E 6BT, WC1E 6BT
United Kingdom
+44 20 7679 5853 (Phone)
+44 20 7916 2775 (Fax)

Centre for Economic Policy Research (CEPR)

London
United Kingdom

IZA Institute of Labor Economics

P.O. Box 7240
Bonn, D-53072
Germany

Pedro Souza

Pontificia Universidad Catolina ( email )

Santiago
Chile

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