Attribute-Based Methods

Stated preference methods of environmental valuation have been used by economists for decades where behavioral data have limitations. The contingent valuation method (Chapter 5) is the oldest stated preference approach, and hundreds of contingent valuation studies have been conducted. More recently, and especially over the last decade, a new class of stated preference methods has been developed, which we generically refer to as attribute-based methods (ABMs). As with contingent valuation, numerous ABM variants exist, employing, for example, different constructs for eliciting preferences. In this chapter, we describe the various ABMs currently used, explain how to construct an attribute-based experiment, and recommend methods for environmental valuation.

[1]  Kevin J. Boyle,et al.  Stated Preference Methods for Valuation of Forest Attributes , 2003 .

[2]  J. Bennett,et al.  The choice modelling approach to environmental valuation , 2001 .

[3]  F. H. Barron,et al.  AXIOMATIC CONJOINT MEASUREMENT , 1977 .

[4]  Wesley D. Seitz,et al.  Measuring Water Quality Benefits , 1986 .

[5]  Kevin J. Boyle,et al.  Using Conjoint Analysis to Derive Estimates of Compensating Variation , 1996 .

[6]  K. Train.  Recreation Demand Models with Taste Differences Over People , 1998 .

[7]  D. Hensher.  Stated preference analysis of travel choices: the state of practice , 1994 .

[8]  David F. Layton,et al.  Random Coefficient Models for Stated Preference Surveys , 2000 .

[9]  Wiktor L. Adamowicz,et al.  Understanding Heterogeneous Preferences in Random Utility Models: The Use of Latent Class Analysis , 1999 .

[10]  John Mackenzie,et al.  A Comparison of Contingent Preference Models , 1993 .

[11]  Joffre Swait,et al.  Choice Environment, Market Complexity, and Consumer Behavior: A Theoretical and Empirical Approach for Incorporating Decision Complexity into Models of Consumer Choice , 2001 .

[12]  William H. Desvousges,et al.  Estimating Stated Preferences with Rated-Pair Data: Environmental, Health, and Employment Effects of Energy Programs , 1997 .

[13]  W. Hanemann,et al.  Welfare Analysis with Discrete Choice Models , 1996 .

[14]  Edward R. Morey,et al.  Measurement error in recreation demand models: the joint estimation of participation, site choice, and site characteristics. , 1998 .

[15]  J. Swait.  A structural equation model of latent segmentation and product choice for cross-sectional revealed preference choice data☆ , 1994 .

[16]  J. Marschak.  Binary Choice Constraints on Random Utility Indicators , 1959 .

[17]  F. Johnson,et al.  Opt-out alternatives and anglers' stated preferences , 2000 .

[18]  J. Louviere,et al.  Combining Revealed and Stated Preference Methods for Valuing Environmental Amenities , 1994 .

[19]  W. Brock,et al.  Discrete Choice with Social Interactions I: Theory , 1995 .

[20]  Thomas J. Lareau,et al.  Valuing WTP for diesel odor reductions: An application of contingent ranking technique , 1989 .

[21]  Jordan J. Louviere,et al.  Using Discrete Choice Models with Experimental Design Data to Forecast Consumer Demand for a Unique Cultural Event , 1983 .

[22]  R. Duncan Luce,et al.  Individual Choice Behavior , 1959 .

[23]  Ki-Hong Choi,et al.  Generalized extreme value model and additively separable generator function , 1997 .

[24]  S. Addelman.  Orthogonal Main-Effect Plans for Asymmetrical Factorial Experiments , 1962 .

[25]  Jordan J. Louviere,et al.  Perceptions versus Objective Measures of Environmental Quality in Combined Revealed and Stated Preference Models of Environmental Valuation , 1997 .

[26]  Paul E. Green,et al.  Model Misspecification in Multiattribute Parameter Estimation , 1981 .

[27]  William G. Cochran,et al.  Experimental Designs, 2nd Edition , 1950 .

[28]  Guy Garrod,et al.  Using Contingent Ranking to Estimate the Loss of Amenity Value for Inland Waterways from Public Utility Service Structures , 1998 .

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

[30]  K. Lancaster.  A New Approach to Consumer Theory , 1966, Journal of Political Economy.

[31]  T. F. Weaver,et al.  Evaluating Impacts from Noxious Facilities: Including Public Preferences in Current Siting Mechanisms , 1993 .

[32]  Jerry A. Hausman and Paul A. Ruud.,et al.  Specifying and Testing Econometric Models for Rank-ordered Data with an Application to the Demand for Mobile and Portable Telephones , 1986 .

[33]  Pradeep K. Chintagunta,et al.  On Using Demographic Variables to Determine Segment Membership in Logit Mixture Models , 1994 .

[34]  C. Gan,et al.  A Conjoint Analysis of Waterfowl Hunting in Louisiana , 1993, Journal of Agricultural and Applied Economics.

[35]  N. Anderson.  Functional measurement and psychophysical judgment. , 1970, Psychological review.

[36]  Jordan J. Louviere,et al.  Design and Analysis of Simulated Consumer Choice or Allocation Experiments: An Approach Based on Aggregate Data , 1983 .

[37]  Wagner A. Kamakura,et al.  Book Review: Structural Analysis of Discrete Data with Econometric Applications , 1982 .

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

[39]  Randall G. Chapaaan,et al.  Exploiting Rank Ordered Choice Set Data within the Stochastic Utility Model , 1982 .

[40]  C. Manski.  The structure of random utility models , 1977 .

[41]  P. Green,et al.  Conjoint Analysis in Consumer Research: Issues and Outlook , 1978 .

[42]  K. Train,et al.  Mixed Logit with Repeated Choices: Households' Choices of Appliance Efficiency Level , 1998, Review of Economics and Statistics.

[43]  G. W. Snedecor.  Statistical Methods , 1964 .

[44]  J. Louviere,et al.  Stated Preference Approaches for Measuring Passive Use Values: Choice Experiments and Contingent Valuation , 1998 .

[45]  Moshe Ben-Akiva,et al.  Discrete Choice Analysis: Theory and Application to Travel Demand , 1985 .

[46]  Moshe Ben-Akiva,et al.  Analysis of the reliability of preference ranking data , 1991 .

[47]  K. R. Hammond.  Probabilistic functioning and the clinical method. , 1955, Psychological review.

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

[49]  D. McFadden,et al.  MIXED MNL MODELS FOR DISCRETE RESPONSE , 2000 .

[50]  Joel Huber,et al.  Pricing environmental health risks: survey assessments of risk-risk and risk-dollar trade-offs for chronic bronchitis☆ , 1991 .

[51]  B. J. Winer.  Statistical Principles in Experimental Design , 1992 .

[52]  J. Yellott.  The relationship between Luce's Choice Axiom, Thurstone's Theory of Comparative Judgment, and the double exponential distribution , 1977 .

[53]  Kevin J. Boyle,et al.  A Comparison of Conjoint Analysis Response Formats , 2001 .

[54]  Gregory K. Leonard,et al.  A utility-consistent, combined discrete choice and count data model Assessing recreational use losses due to natural resource damage , 1995 .

[55]  Jaap Van Brakel,et al.  Foundations of measurement , 1983 .

[56]  V. Kerry Smith,et al.  Non-Market Valuation and the Household , 1998 .

[57]  Vithala R. Rao,et al.  Conjoint Measurement- for Quantifying Judgmental Data , 1971 .

[58]  Guy Garrod,et al.  The non-use benefits of enhancing forest biodiversity: A contingent ranking study , 1997 .

[59]  D. McFadden.  Econometric Models of Probabilistic Choice , 1981 .

[60]  Morris B. Holbrook,et al.  Conjoint Analysis on Objects with Environmentally Correlated Attributes: The Questionable Importance of Representative Design , 1990 .

[61]  J. Swait,et al.  The Influence of Task Complexity on Consumer Choice: A Latent Class Model of Decision Strategy Switching , 2001 .

[62]  D. Wittink,et al.  Commercial Use of Conjoint Analysis: A Survey , 1982 .

[63]  Wiktor L. Adamowicz,et al.  Modeling Recreation Site Choice: Do Hypothetical Choices Reflect Actual Behavior? , 2001 .

[64]  L. Thurstone.  A law of comparative judgment. , 1994 .

[65]  K. Train,et al.  Forecasting new product penetration with flexible substitution patterns , 1998 .

[66]  Cheng Hsiao,et al.  Analysis of Panel Data , 1987 .

[67]  Peter Martinsson,et al.  Do Hypothetical and Actual Marginal Willingness to Pay Differ in Choice Experiments?: Application to the Valuation of the Environment , 2001 .

[68]  Thomas P. Holmes,et al.  The effect of response time on conjoint analysis estimates of rainforest protection values. , 1998 .

[69]  Marisa J. Mazzotta,et al.  Decision Making When Choices Are Complex: A Test of Heiner's Hypothesis , 1995 .

[70]  N. Hanley,et al.  Using Choice Experiments to Value the Environment , 1998 .

[71]  D. McFadden.  The Choice Theory Approach to Market Research , 1986 .

[72]  D. Hensher,et al.  Stated Choice Methods: Analysis and Applications , 2000 .

[73]  D. Dillman.  Mail and telephone surveys : the total design method , 1979 .

[74]  R. Luce,et al.  Simultaneous conjoint measurement: A new type of fundamental measurement , 1964 .

[75]  Jerry A. Hausman,et al.  Assessing the potential demand for electric cars , 1981 .

[76]  Jordan J. Louviere,et al.  A comparison of stated preference methods for environmental valuation , 1996 .

[77]  Jordan J. Louviere,et al.  Introduction to Attribute-Based Stated Choice Methods , 1998 .

[78]  Paul E. Green,et al.  A General Approach to Product Design Optimization via Conjoint Analysis , 1981 .

[79]  K. Small,et al.  Applied Welfare Economics with Discrete Choice Models , 1981 .

[80]  George L. Peterson,et al.  A MODEL OF PREFERENCE: QUANTITATIVE ANALYSIS OF THE PERCEPTION OF THE VISUAL APPEARANCE OF RESIDENTIAL NEIGHBORHOODS , 1967 .

[81]  Virgil L. Anderson,et al.  Applied factorial and fractional designs , 1984 .

[82]  Joel Huber,et al.  The Impact of Inferential Beliefs on Product Evaluations , 1982 .