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Environmental Valuation with Discrete Choice Experiments : Guidance on Design, Implementation and Data Analysis.

Bibliographic Details
Main Author: Mariel, Petr.
Other Authors: Hoyos, David., Meyerhoff, Jürgen., Czajkowski, Mikolaj., Dekker, Thijs., Glenk, Klaus., Jacobsen, Jette Bredahl., Liebe, Ulf., Olsen, Søren Bøye., Sagebiel, Julian.
Format: eBook
Language:English
Published: Cham : Springer International Publishing AG, 2020.
Edition:1st ed.
Series:SpringerBriefs in Economics Series
Subjects:
Electronic books.
Online Access:Click to View
Table of Contents:
  • Intro
  • Preface
  • References
  • Contents
  • Abbreviations
  • 1 Theoretical Background
  • 1.1 Welfare Economics
  • 1.2 Random Utility Maximisation Model
  • References
  • 2 Developing the Questionnaire
  • 2.1 Structure of the Questionnaire
  • 2.2 Description of the Environmental Good
  • 2.3 Survey Pretesting: Focus Groups and Pilot Testing
  • 2.4 Incentive Compatibility
  • 2.5 Consequentiality
  • 2.6 Cheap Talk, Opt-Out Reminder and Oath Script
  • 2.7 Instructional Choice Sets
  • 2.8 Identifying Protesters
  • 2.9 Identifying Strategic Bidders
  • 2.10 Payment Vehicle and Cost Vector Design
  • References
  • 3 Experimental Design
  • 3.1 The Dimensionality of a Choice Experiment
  • 3.1.1 Number of Choice Tasks
  • 3.1.2 Number of Attributes
  • 3.1.3 Number of Alternatives
  • 3.1.4 Other Dimensionality Issues
  • 3.2 Statistical Design of the Choice Tasks
  • 3.3 Checking Your Statistical Design
  • References
  • 4 Collecting the Data
  • 4.1 Sampling Issues
  • 4.2 Survey Mode (Internet, Face-To-Face, Postal)
  • References
  • 5 Econometric Modelling: Basics
  • 5.1 Coding of Attribute Levels: Effects, Dummy or Continuous
  • 5.2 Functional Form of the Attributes in the Utility Function
  • 5.3 Econometric Models
  • 5.3.1 Multinomial (Conditional) Logit
  • 5.3.2 Mixed Logit Models-Random Parameter, Error Component and Latent Class Models
  • 5.3.3 G-MXL Model
  • 5.3.4 Hybrid Choice Models
  • 5.4 Coefficient Distribution in RP-MXL
  • 5.5 Specifics for the Cost Attribute
  • 5.6 Correlation Between Random Coefficients
  • 5.7 Assuring Convergence
  • 5.8 Random Draws in RP-MXL
  • References
  • 6 Econometric Modelling: Extensions
  • 6.1 WTP-Space Versus Preference Space
  • 6.2 Scale Heterogeneity
  • 6.3 Information Processing Strategies
  • 6.4 Random Regret Minimisation-An Alternative to Utility Maximisation
  • 6.5 Attribute Non-attendance.
  • 6.6 Anchoring and Learning Effects
  • References
  • 7 Calculating Marginal and Non-marginal Welfare Measures
  • 7.1 Calculating Marginal Welfare Measures
  • 7.2 Aggregating Welfare Effects
  • 7.3 WTP Comparison
  • References
  • 8 Validity and Reliability
  • 8.1 The Three Cs: Content, Construct and Criterion Validity
  • 8.2 Testing Reliability
  • 8.3 Comparing Models
  • 8.3.1 Model Fit-Based Strategies to Choose Among Different Models
  • 8.3.2 Cross Validation
  • 8.4 Prediction
  • References
  • 9 Software
  • References.

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