Doko Tchatoka, F.Garrard, R.Masson, V.2017-06-252017-06-252017http://hdl.handle.net/2440/106215Also can be found at https://ideas.repec.org/p/adl/wpaper/2017-02.htmlThis paper illustrates how stochastic dominance criteria can be used to rank social networks in terms of efficiency, and develops statistical inference procedures for as- sessing 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 IndiaenCopyright the authorsNetworks; Tests of stochastic dominance; Bootstrap; Uniform convergenceWorking paper0030071750291047Doko Tchatoka, F. [0000-0003-1876-0633]Masson, V. [0000-0002-3597-3019]