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Type: Working paper
Title: Testing for stochastic dominance in social networks
Author: Doko Tchatoka, F.
Garrard, R.
Masson, V.
Publisher: University of Adelaide, School of Economics
Issue Date: 2017
Series/Report no.: School of Economics Working Papers
Statement of
Firmin Doko Tchatoka, Robert Garrard and Virginie Masson
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 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 India
Keywords: Networks; Tests of stochastic dominance; Bootstrap; Uniform convergence
Description: Also can be found at
Rights: Copyright the authors
RMID: 0030071750
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Appears in Collections:Economics Working papers

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