The Robustness of Tests for Consumer Choice Inconsistencies

We explore the in- and out- of sample robustness of tests for consumer choice inconsistencies based on parameter restrictions in parametric models, with a focus on tests proposed by Ketcham, Kuminoff and Powers (2015). We start by arguing that non-parametric alternatives are inherently conservative with respect to detecting mistakes (and one specific test proposed by KKP is incorrect). We then consider several proposed robustness checks of parametric models and argue that they do not separately identify misspecification and choice inconsistencies. We also show that, when implemented using a comprehensive goodness of fit measure, the Keane and Wolpin (2007) test of out of sample forecasting demonstrates that a model allowing for choice inconsistencies forecasts substantially better than one that does not. Finally, we explore the robustness of our 2011 results to alternative normative assumptions.