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How wrong can you be? Implications of incorrect utility function specification for welfare measurement in choice experiments

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Author Info

  • Hanley, Nicholas
  • Riera, Antoni
  • Torres, Cati

Abstract

Despite the vital role of the utility function in welfare measurement, the implications of working with incorrect utility specifications have been largely neglected in the choice experiments literature. This paper addresses the importance of specification with a special emphasis on the effects of mistaken assumptions about the marginal utility of income. Monte Carlo experiments were conducted using different functional forms of utility to generate simulated choices. Multi-Nomial Logit and Mixed Logit models were then estimated on these choices under correct and incorrect assumptions about the true, underlying utility function. Estimated willingness to pay measures from these choice modelling results are then compared with the equivalent measures directly calculated from the true utility specifications. Results show that for the parameter values and functional forms considered, a continuous-quadratic or a discrete-linear attribute specification is a good option regardless of the true effects the attribute has on utility. We also find that mistaken assumptions about preferences over costs magnify attribute mis-specification effects.

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Bibliographic Info

Paper provided by University of Stirling, Division of Economics in its series Stirling Economics Discussion Papers with number 2010-12.

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Date of creation: Nov 2010
Date of revision:
Handle: RePEc:stl:stledp:2010-12

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Postal: Division of Economics, University of Stirling, Stirling, Scotland FK9 4LA
Phone: +44 (0)1786 467473
Fax: +44 (0)1786 467469
Web page: http://www.econ.stir.ac.uk/
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Related research

Keywords: Monte Carlo analysis; choice experiments; efficiency; accuracy; welfare measurement; attributes; utility specification;

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  1. Timothy Park & John B. Loomis & Michael Creel, 1991. "Confidence Intervals for Evaluating Benefits Estimates from Dichotomous Choice Contingent Valuation Studies," Land Economics, University of Wisconsin Press, vol. 67(1), pages 64-73.
  2. Fredrik Carlsson & Peter Martinsson, 2003. "Design techniques for stated preference methods in health economics," Health Economics, John Wiley & Sons, Ltd., vol. 12(4), pages 281-294.
  3. Kling, Catherine L., 1989. "Importance of Functional Form in the Estimation of Welfare (The)," Staff General Research Papers 1596, Iowa State University, Department of Economics.
  4. John M. Rose & Riccardo Scarpa, 2007. "Designs Efficiency for Non-market Valuation with Choice Modelling: How to Measure It, What to Report and Why," Working Papers in Economics 07/21, University of Waikato, Department of Economics.
  5. Kling, Catherine L., 1991. "Estimating the Precision of Welfare Measures," Staff General Research Papers 1608, Iowa State University, Department of Economics.
  6. Kling, Catherine L. & Sexton, Richard, 1990. "Bootstrapping in Applied Welfare Analysis," Staff General Research Papers 1595, Iowa State University, Department of Economics.
  7. Riccardo Scarpa & Ian Bateman, 2000. "Efficiency Gains Afforded by Improved Bid Design versus Follow-up Valuation Questions in Discrete-Choice CV Studies," Land Economics, University of Wisconsin Press, vol. 76(2), pages 299-311.
  8. Alberini Anna, 1995. "Efficiency vs Bias of Willingness-to-Pay Estimates: Bivariate and Interval-Data Models," Journal of Environmental Economics and Management, Elsevier, vol. 29(2), pages 169-180, September.
  9. Kling, Catherine L., 1988. "Reliability of Estimates of Environmental Benefits from Recreation Demand Models (The)," Staff General Research Papers 1587, Iowa State University, Department of Economics.
  10. Kling, Catherine L., 1987. "Simulation Approach to Comparing Multiple Site Recreation Demand Models Using Chesapeake Bay Survey Data (A)," Staff General Research Papers 1583, Iowa State University, Department of Economics.
  11. Herriges, Joseph A. & Kling, Catherine L., 1997. "Performance of Nested Logit Models when Welfare Estimation Is the Goal (The)," Staff General Research Papers 1480, Iowa State University, Department of Economics.
  12. Catherine L. Kling & Cynthia J. Thomson, 1996. "The Implications of Model Specification for Welfare Estimation in Nested Logit Models," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 78(1), pages 103-114.
  13. Joseph A. Herriges & Catherine L. Kling, 1997. "The Performance of Nested Logit Models When Welfare Estimation Is the Goal," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(3), pages 792-802.
  14. Ferrini, Silvia & Scarpa, Riccardo, 2007. "Designs with a priori information for nonmarket valuation with choice experiments: A Monte Carlo study," Journal of Environmental Economics and Management, Elsevier, vol. 53(3), pages 342-363, May.
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  16. Denzil G. Fiebig & Michael P. Keane & Jordan Louviere & Nada Wasi, 2010. "The Generalized Multinomial Logit Model: Accounting for Scale and Coefficient Heterogeneity," Marketing Science, INFORMS, vol. 29(3), pages 393-421, 05-06.
  17. Balcombe, Kelvin & Chalak, Ali & Fraser, Iain, 2009. "Model selection for the mixed logit with Bayesian estimation," Journal of Environmental Economics and Management, Elsevier, vol. 57(2), pages 226-237, March.
  18. Kling, Catherine L., 1989. "The Importance Of Functional Form In The Estimation Of Welfare," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 14(01), July.
  19. Jayson L. Lusk & F. Bailey Norwood, 2005. "Effect of Experimental Design on Choice-Based Conjoint Valuation Estimates," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 87(3), pages 771-785.
  20. Kling, Catherine L. & Herriges, Joseph A., 1997. "Model Performance of Nested Logit Models when Welfare Estimation is the Goal, The," Staff General Research Papers 12331, Iowa State University, Department of Economics.
  21. Kling, Catherine L., 1997. "Evaluation of the Gains from Combining Travel Cost and Contingent Valuation Data to Value Nonmarket Goods (An)," Staff General Research Papers 1598, Iowa State University, Department of Economics.
  22. Kling, Catherine L. & Thomson, Cynthia J., 1996. "Implications of Model Specification for Welfare Estimation in Nested Logit Models (The)," Staff General Research Papers 1599, Iowa State University, Department of Economics.
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Citations

RePEc Biblio mentions

As found on the RePEc Biblio, the curated bibliography for Economics:
  1. > Environmental and Natural Resource Economics > Environmental Economics > Valuation > Choice experiments and conjoint analyses
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Cited by:
  1. Tomás del Barrio Casto & William Nilsson & Andrés J. Picazo-Tadeo, 2013. "How wrong can you be, without noticing? Further evidence on speci cation errors in the Conditional Logit," Working Papers 1318, Department of Applied Economics II, Universidad de Valencia.
  2. Catalina M. Torres Figuerola & Nick Hanley & Sergio Colombo, 2011. "Incorrectly accounting for taste heterogeneity in choice experiments: Does it really matter for welfare measurement?," CRE Working Papers (Documents de treball del CRE) 2011/1, Centre de Recerca Econòmica (UIB ·"Sa Nostra").
  3. Sclen, Håkon & Kallbekken, Steffen, 2011. "A choice experiment on fuel taxation and earmarking in Norway," Ecological Economics, Elsevier, vol. 70(11), pages 2181-2190, September.
  4. Dieckhoener, Caroline & Hecking, Harald, 2012. "Greenhouse Gas Abatement Cost Curves of the Residential Heating Market – a Microeconomic Approach," EWI Working Papers 2012-16, Energiewirtschaftliches Institut an der Universitaet zu Koeln.
  5. Doherty, Edel & Campbell, Danny & Hynes, Stephen, 2012. "Exploring cost heterogeneity in recreational demand," Working Papers 148832, Socio-Economic Marine Research Unit, National University of Ireland, Galway.

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