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The implications of incorrect utility function specification for welfare measurement in choice experiments

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Author Info
Catalina M. Torres Figuerola () (Centre de Recerca Econòmica (UIB · Sa Nostra))
Nick Hanley () (Department of Economics, University of Stirling)
Antoni Riera Font () (Centre de Recerca Econòmica (UIB · Sa Nostra))

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Abstract

Despite the vital role of utility functional form in welfare measurement, the implications of working with incorrect utility specifications have not been examined in the choice experiments literature. This paper addresses the importance of the specification of both non-monetary attributes and the marginal utility of income. Monte Carlo experiments have been conducted wherein different attribute specifications and assumptions for the Cost parameter -that is, different functional forms of utility- have been assumed to generate simulated choices on which Multi-Nomial Logit and Mixed Logit models have been estimated under correct and incorrect assumptions about the true, underlying utility function. The inferred values have been compared with the true ones directly calculated from the true utility specifications. Results show that working with simple experimental designs and continuous-linear specifications makes attribute specification irrelevant for measuring attribute marginal values regardless of the true effects the attribute has on utility.

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Paper provided by Centre de Recerca Econòmica (UIB ·"Sa Nostra") in its series CRE Working Papers (Documents de treball del CRE) with number 2008/6.

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Length: 22 pages
Date of creation: 2008
Date of revision:
Publication status: Published in 'Documents de Treball CRE', 2008, pages 1-22
Handle: RePEc:pdm:wpaper:2008/6

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Web page: http://www.cre.sanostra.es

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Related research
Keywords: Utility specification; attributes; welfare measurement; accuracy; efficiency; choice experiments; Monte Carlo analysis;

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  1. 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. [Downloadable!]
  2. 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. [Downloadable!] (restricted)
  3. 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. [Downloadable!] (restricted)
  4. Kling, Catherine L., 1987. "A Simulation Approach to Comparing Multiple Site Recreation Demand Models Using Chesapeake Bay Survey Data," Marine Resource Economics, Marine Resources Foundation, vol. 4(2). [Downloadable!]
  5. Kling, Catherine L., 1991. "Estimating the precision of welfare measures," Journal of Environmental Economics and Management, Elsevier, vol. 21(3), pages 244-259, November. [Downloadable!] (restricted)
  6. 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. [Downloadable!]
  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. [Downloadable!] (restricted)
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