Design Efficiency for Non-Market Valuation with Choice Modelling: How to Measure it, What to Report and Why

We review the basic principles for the evaluation of design efficiency in discrete choice modelling with a focus on efficiency of WTP estimates from the multinomial logit model. The discussion is developed under the realistic assumption that researchers can plausibly define a prior belief on the range of values for the utility coefficients. D-, A-, B-, S- and C-errors are compared as measures of design performance in applied studies and their rationale is discussed. An empirical example based on the generation and comparison of fifteen separate designs from a common set of assumptions illustrates the relevant considerations to the context of non-market valuation, with particular emphasis placed on C-efficiency. Conclusions are drawn for the practice of reporting in non-market valuation and for future work on design research.

[1]  John R. Hauser,et al.  Research Note---On Managerially Efficient Experimental Designs , 2007 .

[2]  Riccardo Scarpa,et al.  Designs with a priori information for nonmarket valuation with choice experiments: A Monte Carlo study , 2007 .

[3]  R. Scarpa,et al.  Benefit Estimates for Landscape Improvements: Sequential Bayesian Design and Respondents’ Rationality in a Choice Experiment , 2005, Land Economics.

[4]  John M. Rose,et al.  Designing Stated Choice Experiments: State of the Art , 2007 .

[5]  K. Train,et al.  Utility in WTP Space: A Tool to Address Confounding Random Scale Effects in Destination Choice to the Alps , 2006 .

[6]  D. Hensher How do respondents process stated choice experiments? Attribute consideration under varying information load , 2006 .

[7]  Peter Goos,et al.  A Comparison of Criteria to Design Efficient Choice Experiments , 2006 .

[8]  David A. Hensher,et al.  Revealing Differences in Willingness to Pay due to the Dimensionality of Stated Choice Designs: An Initial Assessment , 2006 .

[9]  Peter Goos,et al.  A Comparison of Criteria to Design Efficient , 2006 .

[10]  John R. Hauser,et al.  On Managerially Efficient Experimental Designs , 2006 .

[11]  Jordan J. Louviere,et al.  Quick and easy choice sets: Constructing optimal and nearly optimal stated choice experiments , 2005 .

[12]  Deborah J. Street,et al.  Optimal designs for choice experiments with asymmetric attributes , 2005 .

[13]  John M. Rose,et al.  Applied Choice Analysis: A Primer , 2005 .

[14]  D. Hensher,et al.  Assessing the influence of design dimensions on stated choice experiment estimates , 2005 .

[15]  F. Norwood,et al.  Effect of Experimental Design on Choice‐Based Conjoint Valuation Estimates , 2005 .

[16]  Michel Wedel,et al.  Heterogeneous Conjoint Choice Designs , 2005 .

[17]  John M. Rose,et al.  Efficiency and sample size requirements for stated choice studies , 2005 .

[18]  Riccardo Scarpa,et al.  Performance of Error Component Models for Status-Quo Effects in Choice Experiments , 2005 .

[19]  Kenneth Train,et al.  Discrete Choice Models in Preference Space and Willingness-to Pay Space , 2005 .

[20]  John M. Rose,et al.  Applied Choice Analysis: List of tables , 2005 .

[21]  John M. Rose,et al.  Applied Choice Analysis: List of tables , 2005 .

[22]  David A. Hensher,et al.  IDENTIFYING THE INFLUENCE OF STATED CHOICE DESIGN DIMENSIONALITY ON WILLINGNESS TO PAY FOR TRAVEL TIME SAVINGS , 2004 .

[23]  Jordan J. Louviere,et al.  A 20+ Years’ Retrospective on Choice Experiments , 2004 .

[24]  Peter Goos,et al.  Comparing algorithms and criteria for designing Bayesian conjoint choice experiments , 2004 .

[25]  D. Street,et al.  Optimal and near-optimal pairs for the estimation of effects in 2-level choice experiments , 2004 .

[26]  Ta Theo Arentze,et al.  Transport stated choice responses: effects of task complexity, presentation format and literacy , 2003 .

[27]  Kenneth E. Train,et al.  Discrete Choice Methods with Simulation , 2016 .

[28]  Wiebke Kuklys,et al.  Stated choice methods: analysis and application, Jordan J. Louviere, David A. Hensher and Joffre D. Swait, Cambridge University Press, ISBN: 0-521-78830-7 , 2002 .

[29]  Peeter W. J. Verlegh,et al.  Range and Number-of-Levels Effects in Derived and Stated Measures of Attribute Importance , 2002 .

[30]  Michel Wedel,et al.  Profile Construction in Experimental Choice Designs for Mixed Logit Models , 2002 .

[31]  J. R. DeShazo,et al.  Designing Choice Sets for Stated Preference Methods: The Effects of Complexity on Choice Consistency , 2002 .

[32]  Barbara Kanninen,et al.  Optimal Design for Multinomial Choice Experiments , 2002 .

[33]  William S. Breffle,et al.  Comparing Choice Question Formats for Evaluating Natural Resource Tradeoffs , 2002, Land Economics.

[34]  M. Wedel,et al.  Designing Conjoint Choice Experiments Using Managers' Prior Beliefs , 2001 .

[35]  Jordan J. Louviere,et al.  An exploratory analysis of the effect of numbers of choice sets in designed choice experiments: an airline choice application , 2001 .

[36]  David S. Bunch,et al.  OPTIMAL DESIGNS FOR 2 k PAIRED COMPARISON EXPERIMENTS , 2001 .

[37]  Jordan J. Louviere,et al.  Attribute Range Effects in Binary Response Tasks , 2000 .

[38]  William L. Moore,et al.  A Comparison of Conjoint Methods When There Are Many Attributes , 1999 .

[39]  Joel Huber,et al.  The Importance of Utility Balance in Efficient Choice Designs , 1996 .

[40]  Alan D. J. Cooke,et al.  Attribute Range and Response Range: Limits of Compatibility in Multiattribute Judgment , 1995 .

[41]  Anna Alberini,et al.  Optimal Designs for Discrete Choice Contingent Valuation Surveys: Single-Bound, Double-Bound, and Bivariate Models , 1995 .

[42]  J. Louviere,et al.  The Role of the Scale Parameter in the Estimation and Comparison of Multinomial Logit Models , 1993 .

[43]  Barbara Kanninen,et al.  Design of Sequential Experiments for Contingent Valuation Studies , 1993 .

[44]  Barbara Kanninen,et al.  Optimal Experimental Design for Double-Bounded Dichotomous Choice Contingent Valuation , 1993 .

[45]  R. D. Cook,et al.  A Comparison of Algorithms for Constructing Exact D-Optimal Designs , 1980 .

[46]  R. Emori CASE STUDY 9 , 1977 .

[47]  P. Zarembka Frontiers in econometrics , 1973 .

[48]  D. McFadden Conditional logit analysis of qualitative choice behavior , 1972 .