We provide a nonparametric revealed preference approach to demand analysis based on homothetic efficiency. Homotheticity is a useful restriction but data rarely satisfies testable conditions. To overcome this we provide a way to estimate homothetic efficiency of consumption choices. It...

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 a nonparametric revealed preference approach to demand analysis based on homothetic efficiency. Homotheticity is a useful restriction but data rarely satisfies testable conditions. To overcome this we provide a way to estimate homothetic efficiency of consumption choices. It...

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...

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...