Environmental Valuation with Discrete Choice Experiments: Guidance on Design, Implementation and Data AnalysisThis open access book offers up-to-date advice and practical guidance on how to undertake a discrete choice experiment as a tool for environmental valuation. It discusses crucial issues in designing, implementing and analysing choice experiments. Compiled by leading experts in the field, the book promotes discrete choice analysis in environmental valuation through a more solid scientific basis for research practice. Instead of providing strict guidelines, the book helps readers avoid common mistakes often found in applied work. It is based on the collective reflections of the scientific network of researchers using discrete choice modelling in the field of environmental valuation (www.envecho.com). |
Contents
1 | |
2 Developing the Questionnaire | 7 |
3 Experimental Design | 37 |
4 Collecting the Data | 50 |
Basics | 61 |
Extensions | 82 |
7 Calculating Marginal and Nonmarginal Welfare Measures | 103 |
8 Validity and Reliability | 111 |
9 Software | 124 |
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Common terms and phrases
allows alternative analysis answer applications approach assumed attribute levels behaviour Cheap Talk choice experiments choice sets choice tasks choose coding coefficients Commons compared complex consequentiality consider context correlation cost decision depends described discrete choice experiments discrete choice models distribution draws Economics effects efficient empirical Environ Resource Econ environmental error estimates et al example focus given groups Hensher Hess heterogeneity hypothetical bias important incentive included income increasing indicate individual interest interviews latent literature logit Manag mean measures methods Meyerhoff mixed mode mWTP observations obtain Olsen packages parameters payment population possible practice preference present protest questionnaire questions random recommended reduce Reminder requires respondents sample scale Scarpa Sect simulation space specific statistical strategies studies survey Train typically utility utility function validity valuation values variables welfare