期刊
JOURNAL OF ENVIRONMENTAL ECONOMICS AND MANAGEMENT
卷 53, 期 3, 页码 342-363出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.jeem.2006.10.007
关键词
experimental design; choice experiments; D-criterion; nonmarket valuation
Good practice in experimental design is essential for choice experiments used in nonmarket valuation. We review the practice of experimental design for choice experiments in environmental economics and we compare it with advances in experimental design. We then evaluate the statistical efficiency of four different designs by means of Monte Carlo experiments. Correct and incorrect specifications are investigated with gradually more precise information on the true parameter values. The data generating process (DGP) is based on estimates from data of a real study. Results indicate that D-efficient designs are promising, especially when based on Bayesian algorithms with informative prior. However, if good quality a priori information is lacking, and if there is strong uncertainty about the real DGP-conditions which are quite common in environmental valuation-then practitioners might be better off with shifted designs built from conventional fractional factorial designs for linear models. (c) 2007 Elsevier Inc. All rights reserved.
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