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A Note on Nonlinearity Bias and Dichotomous Choice CVM: Implications for Aggregate Benefits Estimation

Published online by Cambridge University Press:  15 September 2016

R.A. Souter
Affiliation:
USDA Forest Service, Southern Research Station, Forestry Sciences Lab, Athens, Georgia
J.M. Bowker
Affiliation:
USDA Forest Service, Southern Research Station, Forestry Sciences Lab, Athens, Georgia
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Abstract

It is a generally known statistical fact that the mean of a nonlinear function of a set of random variables is not equivalent to the function evaluated at the means of the variables. However, in dichotomous choice contingent valuation studies a common practice is to calculate an overall mean (or median) by integrating over offer space (numerically or analytically) an estimated logit or probit function in which sample mean values for the concomitant variables are used. We demonstrate this procedure to be incorrect and we statistically test the procedure against the correct method for nonlinear models. Using data resulting in a well-behaved logit model, we reject the hypothesis of congruence between the two means. Such a finding should be considered in future single response dichotomous choice CVM studies, particularly when aggregation is of interest.

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Articles
Copyright
Copyright © 1996 Northeastern Agricultural and Resource Economics Association 

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