Emotions and decision rules in discrete choice experiments for valuing health care programmes for the elderly.

The evaluation of health care programmes is commonly approached with stated preference methods such as contingent valuation or discrete choice experiments. These methods provide useful information for policy decisions involving health regulations and infrastructures for health care. However, econometric modelling of these data usually relies on a number of maintained assumptions, such as the use of the compensatory or random utility maximization rule. On the other hand, health policy issues can raise emotional concerns among individuals, which might induce other types of choice behaviour. In this paper we consider potential deviations from the general compensatory rule, and how these deviations might be explained by the emotional state of the subject. We utilized a mixture econometric model which allows for various potential decisions rules within the sample, such as the complete ignorance, conjunctive rule and satisfactory rules. The results show that deviations from the full linear compensatory decision rule are predominant, but they are significantly less observed for those subjects with a medium emotional state about the issue of caring for the health state of the elderly. The implication is that the emotional impact of health policy issues should be taken into account when making assumptions of individual choice behaviour in health valuation methods.

[1]  Rajeev Gowda,et al.  Judgments, Decisions, and Public Policy: Commentary and Cautionary Note , 2001 .

[2]  Marsha L. Richins Measuring Emotions in the Consumption Experience , 1997 .

[3]  D. Kahneman,et al.  CHAPTER EIGHT. Fairness as a Constraint on Profit Seeking: Entitlements in the Market , 2004 .

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

[5]  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 .

[6]  J. Shanteau,et al.  The perceived strength of an implied contract: Can it withstand financial temptation? , 1991 .

[7]  Siddhartha Chib,et al.  Markov chain Monte Carlo and models of consideration set and parameter heterogeneity , 1998 .

[8]  J. Araña,et al.  Modelling unobserved heterogeneity in contingent valuation of health risks , 2006 .

[9]  J. Araña,et al.  Economic evaluation of health effects with preference imprecision. , 2006, Health economics.

[10]  A. Tversky,et al.  Prospect Theory : An Analysis of Decision under Risk Author ( s ) : , 2007 .

[11]  A. Damasio Descartes’ Error. Emotion, Reason and the Human Brain. New York (Grosset/Putnam) 1994. , 1994 .

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

[13]  Joffre Swait,et al.  Context Dependence and Aggregation in Disaggregate Choice Analysis , 2002 .

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

[15]  J. Araña,et al.  Willingness to pay for health risk reduction in the context of altruism. , 2002, Health economics.

[16]  S. Folkman,et al.  Coping as a mediator of emotion. , 1988, Journal of personality and social psychology.

[17]  Mandy Ryan,et al.  'Irrational' stated preferences: a quantitative and qualitative investigation. , 2005, Health economics.

[18]  Ellen B. Braaten,et al.  Emotional intensity: Measurement and theoretical implications , 1994 .

[19]  Greg M. Allenby,et al.  A Choice Model with Conjunctive, Disjunctive, and Compensatory Screening Rules , 2004 .

[20]  N. Klein,et al.  Context Effects on Effort and Accuracy in Choice: An Enquiry into Adaptive Decision Making , 1989 .

[21]  A. Sen,et al.  Maximization and the Act of Choice , 1997 .

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

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

[24]  R. Larsen,et al.  Affect intensity as an individual difference characteristic: A review , 1987 .

[25]  John Roberts,et al.  Development and Testing of a Model of Consideration Set Composition , 1991 .

[26]  A. Tversky,et al.  Prospect Theory. An Analysis of Decision Making Under Risk , 1977 .

[27]  Peter E. Rossi,et al.  Case Studies in Bayesian Statistics , 1998 .

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

[29]  Christopher K. Hsee,et al.  Music, Pandas, and Muggers: On the Affective Psychology of Value , 2004, Journal of experimental psychology. General.

[30]  M. Ryan,et al.  Valuing health care using willingness to pay: a comparison of the payment card and dichotomous choice methods. , 2004, Journal of health economics.

[31]  E. Diener Deindividuation, self-awareness, and disinhibition. , 1979 .

[32]  J. Baron,et al.  An Exploratory Study of Choice Rules Favored for High-Stakes Decisions , 1995 .

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

[34]  M. Ryan,et al.  'Threats' to and hopes for estimating benefits. , 2005, Health economics.

[35]  Sufficient conditions for balanced incomplete block designs to be minimal fractional combinatorial treatment designs , 2003 .

[36]  Rick L. Andrews,et al.  Studying Consideration Effects in Empirical Choice Models Using Scanner Panel Data , 1995 .

[37]  M. F. Luce,et al.  Constructive Consumer Choice Processes , 1998 .

[38]  D. Gensch A Two-Stage Disaggregate Attribute Choice Model , 1987 .

[39]  H. Simon,et al.  A Behavioral Model of Rational Choice , 1955 .

[40]  A. Tversky Elimination by aspects: A theory of choice. , 1972 .

[41]  Peter Martinsson,et al.  Design techniques for stated preference methods in health economics. , 2003, Health economics.

[42]  Julie R. Irwin,et al.  Buying/Selling Price Preference Reversals: Preference for Environmental Changes in Buying Versus Selling Modes , 1994 .

[43]  Maggie Geuens,et al.  Validity and Reliability of Scores on the Reduced Emotional Intensity Scale , 2002 .

[44]  J B Tomblin,et al.  Clinical decision making: describing the decision rules of practicing speech-language pathologists. , 1994, Journal of speech and hearing research.

[45]  Eric J. Johnson,et al.  The adaptive decision maker , 1993 .

[46]  Jordan J. Louviere,et al.  What If Consumer Experiments Impact Variances as Well as Means? Response Variability as a Behavioral Phenomenon , 2001 .

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

[48]  W. Michael Hanemann,et al.  Welfare Evaluations in Contingent Valuation Experiments with Discrete Responses , 1984 .

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

[50]  A. Damasio Descartes' error: emotion, reason, and the human brain. avon books , 1994 .

[51]  Joffre Swait,et al.  A NON-COMPENSATORY CHOICE MODEL INCORPORATING ATTRIBUTE CUTOFFS , 2001 .

[52]  J. Araña,et al.  Flexible mixture distribution modeling of dichotomous choice contingent valuation with heterogenity , 2005 .

[53]  Rosalie Viney,et al.  Empirical investigation of experimental design properties of discrete choice experiments in health care. , 2005, Health economics.

[54]  Bruce G. S. Hardie,et al.  Watching Customers Decide: Process Measures Add Insights to Choice Modeling Experiments , 1997 .

[55]  Kathryn A Phillips,et al.  An experiment on simplifying conjoint analysis designs for measuring preferences. , 2003, Health economics.

[56]  J. R. DeShazo,et al.  Designing Transactions without Framing Effects in Iterative Question Formats , 2002 .

[57]  A. Tversky,et al.  Prospect theory: analysis of decision under risk , 1979 .