Discriminating Methods: Tests for Non-Nested Discrete Choice Models

Abstract

We consider the problem of choosing between rival statistical models that are non-nested in terms of their functional forms. We assess the ability of two tests, one parametric and one distribution-free, to discriminate between such models. Our Monte Carlo simulations demonstrate that both tests are, to varying degrees, able to discriminate between strategic and non-strategic discrete choice models. The distribution-free test appears to have greater relative power in small samples.