Journal of Forest Economics > Vol 16 > Issue 2

On dichotomous choice contingent valuation data analysis: Semiparametric methods and Genetic Programming

Marcos Álvarez Díaz, , marcos.alvarez@uvigo.es Manuel González Gómez, , Ángeles Saavedra González, , Jacobo De Uña Álvarez, ,
 
Suggested Citation
Marcos Álvarez Díaz, Manuel González Gómez, Ángeles Saavedra González and Jacobo De Uña Álvarez (2010), "On dichotomous choice contingent valuation data analysis: Semiparametric methods and Genetic Programming", Journal of Forest Economics: Vol. 16: No. 2, pp 145-156. http://dx.doi.org/10.1016/j.jfe.2009.02.002

Published: 0/4/2010
© 0 2010 Marcos Álvarez Díaz, Manuel González Gómez, Ángeles Saavedra González, Jacobo De Uña Álvarez
 
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Keywords
JEL Codes:C14Q26
Dichotomous choice contingent valuationGenetic programParametric techniquesProportional hazard model
 

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In this article:
Introduction
The methods
Semiparametric methods
Genetic Programming
Object of analysis and data
Results
Conclusion

Abstract

The aim of this paper is twofold. Firstly, we introduce a novel semiparametric technique called Genetic Programming to estimate and explain the willingness to pay to maintain environmental conditions of a specific natural park in Spain. To the authors’ knowledge, this is the first time in which Genetic Programming is employed in contingent valuation. Secondly, we investigate the existence of bias due to the functional rigidity of the traditional parametric techniques commonly employed in a contingent valuation problem. We applied standard parametric methods (logit and probit) and compared with results obtained using semiparametric methods (a proportional hazard model and a genetic program). The parametric and semiparametric methods give similar results in terms of the variables finally chosen in the model. Therefore, the results confirm the internal validity of our contingent valuation exercise.

DOI:10.1016/j.jfe.2009.02.002