Hedonic Prices and Colinearity: An Empirical Comparison of Statistical and Neuronal Solutions

Pierre Desmet ()

Post-Print from HAL

Abstract: The hedonic price method is well adapted to the calculation of relative prices and the estimation of the quality price relationship for a complex product. The main weakness lies in the use of multiple regression for the evaluation of the coefficients when there is very little data and when the variables are correlated. In this article, various methods, statistical and neuronal, are compared from both the predictive capacity point of view as well as that of the facial validity of the expected results. The neuronal approach is globally more successful than PLS regression but neither of the two methods leads to an acceptable solution to the problems of interpretation of the coefficients (signs and values ) stemming from colinearity.

Keywords: hedonic prices; neural networks; pls regression; automobile (search for similar items in EconPapers)
Date: 2000-05-25
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Published in Fuzzy Economic Review, 2000, 5 (1), pp.61-75

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:halshs-00143422

Access Statistics for this paper

More papers in Post-Print from HAL
Bibliographic data for series maintained by CCSD ().