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Recovering social networks from panel data: identification, simulations and an application

Aureo de Paula, Imran Rasul and Pedro CL Souza
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Pedro CL Souza: Institute for Fiscal Studies

No CWP58/18, CeMMAP working papers from Centre for Microdata Methods and Practice, Institute for Fiscal Studies

Abstract: It is almost self-evident that social interactions can determine economic behavior and outcomes. Yet, 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 model based on the Adaptive Elastic Net GMM method. We showcase the method and its robustness in Monte Carlo simulations using stylized and real world network structures. Finally, we employ the method to study tax competition across US states. We find the identified network structure of tax competition differs markedly from the common assumption of competition between geographically neighboring states. We analyze the identified social interactions matrix to provide novel insights into the long-standing debate on the relative roles of factor mobility and yardstick competition in driving tax setting behavior across states. Most broadly, our results show how the analysis of social interactions can be extended to economic realms where no network data exists.

Date: 2018-10-08
New Economics Papers: this item is included in nep-soc and nep-ure
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (23)

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Related works:
Working Paper: Recovering social networks from panel data: Identification, simulations and an application (2018) Downloads
Working Paper: Recovering Social Networks from Panel Data: Identification, Simulations and an Application (2018) Downloads
Working Paper: Recovering social networks from panel data: identification, simulations and an application (2018) Downloads
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