Testing for Stochastic Dominance in Social Networks

Firmin Doko Tchatoka, Robert Garrard () and Virginie Masson

No 2017-02, School of Economics and Public Policy Working Papers from University of Adelaide, School of Economics and Public Policy

Abstract: This paper illustrates how stochastic dominance criteria can be used to rank social networks in terms of efficiency, and develops statistical inference procedures for assessing these criteria. The tests proposed can be viewed as extensions of a Pearson goodness-of-fit test and a studentized maximum modulus test often used to partially rank income distributions and inequality measures. We establish uniform convergence of the empirical size of the tests to the nominal level, and show their consistency under the usual conditions that guarantee the validity of the approximation of a multinomial distribution to a Gaussian distribution. Furthermore, we propose a bootstrap method that enhances the finite-sample properties of the tests. The performance of the tests is illustrated via Monte Carlo experiments and an empirical application to risk sharing networks in rural India.

Keywords: Networks; Tests of stochastic dominance; Bootstrap; Uniform convergence. (search for similar items in EconPapers)
JEL-codes: C12 C13 C36 (search for similar items in EconPapers)
Date: 2017-02
New Economics Papers: this item is included in nep-ecm and nep-ore
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