Monte Carlo Benchmarks for Discrete Response Valuation Methods

by

Ju Chin Huang and V. Kerry Smith( 


Abstract


	This paper argues that the widespread belief that discrete contingent valuation (CV) questions yield substantially larger estimates of the mean (and the median) willingness to pay (WTP) for nonmarket environmental resources in comparison to estimates from open-ended CV questions is unfounded.  A set of Monte Carlo experiments estimate the factors influencing the performance of WTP estimates based on discrete response models.  Most of the error in the WTP estimates arises from the specification errors that are common in most of the empirical models used in the literature.  These experiments suggest models based on choices where WTP is dominated by non use (or passive use) values are likely to have smaller errors than where large use values influence these decisions.  


Key words:  Discrete Response Contingent Valuation, Monte Carlo, Non-Market Valuation

JEL Classification No(s): C93, D12, Q2


( Assistant Professor, Department of Economics, East Carolina University and Arts and Sciences Professor, Duke University and Resources for the Future University Fellow.  Partial support for Smith's research was provided the UNC Sea Grant Program R/MRD-32.