Consistent Subsets – Computationally Feasible Methods to Compute the Houtman-Maks-Index
9 Pages Posted: 18 Feb 2015
Date Written: December 17, 2014
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 respect. The first method is a variation of Gross and Kaiser’s (1996) approximate algorithm and is only applicable for two-dimensional data sets, but it is very fast and easy to implement. The second method is a mixed -integer linear programming approach that is slightly more involved but still fast and not limited by the dimension of the data set.
Keywords: Demand theory; efficiency; nonparametric analysis; revealed preference; utility maximisation
JEL Classification: C14, D11, D12
Suggested Citation: Suggested Citation