We propose a method to recover homothetic preferences from choice data with minor optimization or measurement errors. Our method allows for a more detailed graphical analysis to reveal subjects' preferences and to choose appropriate functional forms for parametric analysis. It can also be used...

We propose a method to recover homothetic preferences from choice data with minor optimization or measurement errors. Our method allows for a more detailed graphical analysis to reveal subjects' preferences and to choose appropriate functional forms for parametric analysis. It can also be used...

We provide two methods to compute the largest subset of a set of observations that is consistent with the Generalised Axiom of Revealed Preference. The algorithm provided by Houtman and Maks (1985) is not comput ationally feasible for larger data sets, while our methods are not limited in that...

This article provides a robust non-parametric approach to demand analysis based on a concept called homothetic efficiency. Homotheticity is a useful restriction or assumption but data rarely satisfy testable conditions. To overcome this problem, this article provides a way to estimate homothetic...

We provide two methods to compute the largest subset of a set of observations that is consistent with the Generalised Axiom of Revealed Preference. The algorithm provided by Houtman and Maks (1985) is not computationally feasible for larger data sets, while our methods are not limited in that...

This article provides a robust non-parametric approach to demand analysis based on a concept called homothetic efficiency. Homotheticity is a useful restriction or assumption but data rarely satisfy testable conditions. To overcome this problem, this article provides a way to estimate homothetic...

We provide two methods to compute the largest subset of a set of observations that is consistent with the Generalised Axiom of Revealed Preference. The algorithm provided by Houtman and Maks (1985) is not comput ationally feasible for larger data sets, while our methods are not limited in that...

We provide two methods to compute the largest subset of a set of observations that is consistent with the Generalised Axiom of Revealed Preference. The algorithm provided by Houtman and Maks (1985) is not computationally feasible for larger data sets, while our methods are not limited in that...