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

Publication Date: 0/4/2010
© 0 2010 Marcos Álvarez Díaz, Manuel González Gómez, Ángeles Saavedra González, Jacobo De Uña Álvarez
 
Subjects
 
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