Ferrini, SilviaScarpa, Riccardo2008-12-152008-12-152005-12Ferrini, S. & Scarpa, R. (2005). Experimental designs for environmental valuation with choice-experiments: A Monte Carlo investigation. (Department of Economics Working Paper Series, Number 8/05). Hamilton, New Zealand: University of Waikato.https://hdl.handle.net/10289/1642We 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.application/pdfenlogit experimental designefficiencyMonte Carlochoice experimentsnon-market valuationWorking Paper