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Experimental Designs for Environmental Valuation with Choice-Experiments: A Monte-Carlo Investigation

Silvia Ferrini () and Riccardo Scarpa ()

Working Papers in Economics from University of Waikato

Abstract: We review the practice of experimental design in the environmental economics literature concerned with choice experiments. We then contrast this with advances in the field of experimental design and present a comparison of statistical efficiency across four different experimental designs evaluated by Monte Carlo experiments. Two different situations are envisaged. First, a correct a priori knowledge of the multinomial logit specification used to derive the design and then an incorrect one. The data generating process is based on estimates from data of a real choice experiment with which preference for rural landscape attributes were studied. Results indicate the D-optimal designs are promising, especially those based on Bayesian algorithms with informative prior. However, if good a priori information is lacking, and if there is strong uncertainty about the real data generating process - conditions which are quite common in environmental valuation - then practitioners might be better off with conventional fractional designs from linear models. Under misspecification, a design of this type produces less biased estimates than its competitors.

Keywords: logit experimental design; efficiency; Monte Carlo choice experiments; non-market valuation (search for similar items in EconPapers)
JEL-codes: C13 C15 C25 C99 Q26 (search for similar items in EconPapers)
Pages: 37 pages
Date: 2005-12-13
New Economics Papers: this item is included in nep-agr, nep-dcm, nep-ecm and nep-env
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