Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/211148
Authors: 
de Paula Neto, Áureo Nilo
Rasul, Imran
Souza, Pedro C. L.
Year of Publication: 
2019
Series/Report no.: 
cemmap working paper No. CWP55/19
Abstract: 
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.
JEL: 
C31
D85
H71
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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