GME versus OLS - Which is the best to estimate utility functions?
This paper estimates von Neumann andMorgenstern utility functions comparing the generalized maximum entropy (GME) with OLS, using data obtained by utility elicitation methods. Thus, it provides a comparison of the performance of the two estimators in a real data small sample setup. The results confirm the ones obtained for small samples through Monte Carlo simulations. The difference between the two estimators is small and it decreases as the width of the parameter support vector increases. Moreover the GME estimator is more precise than the OLS one. Overall the results suggest that GME is an interesting alternative to OLS in the estimation of utility functions when data is generated by utility elicitation methods.
|Date of creation:||2010|
|Date of revision:|
|Contact details of provider:|| Postal: Colégio Espírito SANTO|
Phone: (351) 266 740 869
Web page: http://www.cefage.uevora.pt
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:cfe:wpcefa:2010_02. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Angela Pacheco)
If references are entirely missing, you can add them using this form.