Incorrectly accounting for preference heterogeneity in choice experiments: Implications for welfare measurement
The impact of the approach used to describe preference heterogeneity on welfare measures has been widely studied by the academic community. However, the question as to the degree of error in welfare estimation from an inappropriate choice of empirical approach has not been addressed yet. In this paper, we use Monte Carlo analysis to investigate this issue. Our overall conclusion is that, when analysts have difficulties in choosing the best approach relying on available statistical tests, smaller errors in welfare measures are likely to come from use of a latent class model.
Adamowicz, W.L., Fletcher, J.J. and Graham-Tomasi, T. (1989). “Functional form and the statistical properties of welfare measures”. American Journal of Agricultural Economics, 71(2): 414-421. http://doi.org/bdk737.
Alberini, A. (1995). “Efficiency vs. bias of willingness-to-pay estimates: Bivariate and interval-data models”. Journal of Environmental Economics and Management,29(2): 169-180. http://doi.org/ckn6v8.
Balcombe, K., Chalak, A. and Fraser, I. (2009). “Model selection for the mixed logit with Bayesian estimation”. Journal of Environmental Economics and Management, 57(2): 226-237. http://doi.org/fdxdvx.
Beharry-Borg, N., Hensher, D.A. and Scarpa, R. (2009). “An analytical framework for joint vs. separate decisions by couples in choice experiments. The case of coastal water quality in Tobago”. Environmental and Resource Economics, 43(1): 95-117. http://doi.org/cggkxh.
Beharry-Borg, N. and Scarpa, R. (2010). “Valuing quality changes in Caribbean coastal waters for heterogeneous beach visitors”. Ecological Economics, 69(5): 1124-1139. http://doi.org/dzmktr.
Ben-Akiva, M. and Lerman, S.R. (1985). Discrete choice analysis: Theory and application to travel demand. The MIT Press, Massachusetts.
Bhat, C.R. (1997). “An endogenous segmentation mode choice model with an application to intercity travel”. Transportation Science, 31(1): 34-48. http://doi.org/dh8p4g.
Birol, E., Karousakis, K. and Koundouri, P. (2006). “Using a choice experiment to account for preference heterogeneity in wetland attributes: The case of Cheimaditida wetland in Greece”. Ecological Economics, 60(1): 145-156. http://doi.org/bggvm6.
Boxall, P.C. and Adamowicz, W. (2002). “Understanding heterogeneous preferences in random utility models: A latent class approach”. Environmental and Resource Economics, 23(4): 421-446. http://doi.org/bjmwmd.
Broch, S.W. and Vedel, S.E. (2012). “Using Choice Experiments to Investigate the Policy Relevance of Heterogeneity in Farmer Agri-Environmental Contract Preferences”. Environmental and Resource Economics, 51(4): 561-581. http://doi.org/d4mbcw.
Bujosa, A., Riera, A. and Hicks, R.L. (2010). “Combining discrete and continuous representations of preference heterogeneity: A latent class approach”. Environmental and Resource Economics, 47(4): 477-493. http://doi.org/d4344m.
Burton, M. and Rigby, D. (2009). “Hurdle and latent class approaches to serial non-participation in choice models”. Environmental and Resource Economics, 42(2): 211-226. http://doi.org/dfgvcz.
Carlsson, F. and Martinsson, P. (2003). “Design techniques for stated preference methods in health economics”. Health Economics, 12(4): 281-294. http://doi.org/bnj6wk.
Claassen J., Hellerstein, D. and Kim, S.G. (2013). “Using mixed logit in land use models: can expectation-maximization (EM) algorithms facilitate estimation?” American Journal of Agricultural Economics, 95(2): 419-425. http://doi.org/wv6.
Colombo, S., Calatrava-Requena, J. and Hanley, N. (2007). “Testing choice experiments for benefit transfer with preference heterogeneity”. American Journal of Agricultural Economics, 89(1): 135-151. http://doi.org/d6cc6v.
Colombo, S., Hanley, N., and Louviere, J.J. (2009). “Modeling preference heterogeneity in stated choice data: An analysis for public goods generated by agriculture”. Agricultural Economics, 40(3): 307-322. http://doi.org/dh93m2.
Daly, A.J., Hess, S. and Train, K. (2012). “Assuring finite moments for willingness to pay in random coefficients models”. Transportation, 39(1): 19-31. http://doi.org/bx9xm2.
Ferrini, S. and Scarpa, R. (2007). “Designs with a priori information for nonmarket valuation with choice experiments: A Monte Carlo study”. Journal of Environmental Economics and Management, 53(3): 342-363. http://doi.org/cn2m7f.
Fiebig, D.G., Keane, M.P., Louviere, J.J. and Wasi, N. (2010). “The generalized multinomial logit model: Accounting for scale and coefficient heterogeneity”. Marketing Science, 29(3): 393-421. http://doi.org/bh69k9.
Flynn, T.N., Louviere, J.J., Peters, T.J. and Coast, J. (2010). “Using discrete choice experiments to understand preferences for quality of life. Variance-scale heterogeneity matters”. Social Science and Medicine, 70(12): 1957-1965. http://doi.org/d4qgsv.
Foster, V. and Mourato, S. (2003). “Elicitation format and sensitivity to scope. Do contingent valuation and choice experiments give the same results?” Environmental and Resource Economics, 24(2): 141-160. http://doi.org/b4xm5c.
Frondel, M. and Vance, C. (2013). “Heterogeneity in the effect of home energy audits: Theory and evidence”. Environmental and Resource Economics, 55(3): 407-418. http://doi.org/wv7.
Greene, W.H. and Hensher, D.A. (2003). “A latent class model for discrete choice analysis: Contrasts with mixed logit”. Transportation Research Part B: Methodological, 37(8): 681-698. http://doi.org/dnjsrm.
Greene, W.H. and Hensher, D.A. (2010). “Does scale heterogeneity across individuals matter? An empirical assessment of alternative logit models”. Transportation, 37(3): 413-428. http://doi.org/fw29z2.
Greene, W.H. and Hensher, D.A. (2013). “Revealing additional dimensions of preference heterogeneity in a latent class mixed multinomial logit model”. Applied Economics, 45(14): 1897-1902. http://doi.org/fxxjtf.
Hanemann, W.M. (1984). Applied welfare analysis with quantitative response models. Working Paper 241. University of California, Berkeley.
Hanley, N. and Barbier, E.B. (2009). Pricing Nature: Cost-Benefit Analysis and Environmental Policy Making. Edward Elgar, Cheltenham.
Hensher, D.A. and Greene, W.H. (2003). “The mixed logit model: The state of practice”. Transportation, 30 (2): 133-176. http://doi.org/bbj7x9.
Hensher, D.A., Rose, J. and Greene, W.H. (2005a). Applied Choice Analysis: A primer. Cambridge University Press, Cambridge.
Hensher, D.A., Shore, N. and Train, K. (2005b). “Household’s willingness to pay for water service attributes”. Environmental and Resource Economics, 32(4): 509-531. http://doi.org/bq452p.
Herriges, J.A. and Kling, C.L. (1997). “The performance of nested logit models when welfare estimation is the goal”. American Journal of Agricultural Economics, 79(3): 792-802. http://doi.org/b2647t.
Hess, S. and Beharry-Borg, N. (2012). “Accounting for latent attitudes in willingness-to-pay studies: The case of coastal water quality improvements in Tobago. Environmental and Resource Economics, 52(1): 109-131. http://doi.org/bwpsd9.
Hess, S. and Rose, J. (2012). “Can scale and coefficient heterogeneity be separated in random coefficients models?” Transportation, 39(6): 1225-1239. http://doi.org/wv8.
Hynes, S., Hanley, N. and Scarpa, R. (2008). “Effects on welfare measures of alternative means of accounting for preference heterogeneity in recreational demand models”. American Journal of Agricultural Economics, 90(4): 1011-1027. http://doi.org/bt825m.
Johansson, P.O. (1993). Cost-benefit analysis of environmental change. Cambridge University Press, Cambridge.
Kipperberg, G. and Larson, D.M. (2012). “Heterogeneous preferences for community recycling programs”. Environmental and Resource Economics, 53(4): 577-604. http://doi.org/wv9.
Kling, C.L. (1987). “A simulation approach to comparing multiple site recreation demand models using Chesapeake Bay survey data”. Marine Resource Economics, 4(2): 95-109.
Kling, C.L. (1988). “The reliability of estimates of environmental benefits from recreation demand models”. American Journal of Agricultural Economics, 70(4): 892-901. http://doi.org/fdgr7z.
Kling, C.L. (1989). “The importance of functional form in the estimation of welfare”. Western Journal of Agricultural Economics, 14(1): 168-174.
Kling, C.L. (1997). “The gains from combining travel cost and contingent valuation data to value nonmarket goods”. Land Economics, 73(3): 428-439.
Kling, C.L. and Thomson, C.J. (1996). “The implications of model specification for welfare estimation in nested logit models”. American Journal of Agricultural Economics, 78(1): 103-114. http://doi.org/bg8kh5.
Lanz, B. and Provins, A. (2013). “Valuing local environmental amenity with discrete choice experiments: Spatial scope sensitivity and heterogeneous marginal utility of income”. Environmental and Resource Economics, 56(1): 105-130. http://doi.org/wwb.
Louviere, J.J. and Eagle, T. (2006). “Confound it! That pesky little scale constant messes up our convenient assumptions”. Paper presented at the Sawtooth Software Conference, Washington.
Louviere, J.J., Meyer, R.J., Bunch, D.S., Carson, R., Dellaert, B., Hanemann, W.M., Hensher, D. and Irwin, J. (1999). “Combining sources of preference data for modelling complex decision processes”. Marketing Letters, 10(3): 205-217. http://doi.org/c7zcdc.
Louviere, J.J., Street, D., Burgess, L., Wasi, N., Islam, T. and Marley, A.A.J. (2008). “Modeling the choices of individual decision makers by combining eficient choice experiment designs with extra preference information”. Journal of Choice Modelling, 1(1): 128-164. http://doi.org/wwc.
Louviere, J.J., Street, D., Carson, R., Ainslie, A., Deshazo, J.R., Cameron, T., Hensher, D.A., Kohn, R. and Marley, T. (2002). “Dissecting the random component of utility”. Marketing Letters, 13(3): 177-193. http://doi.org/dds2db.
Louviere, J.J., Hensher, D.A. and Swait, J.D. (2000). Stated choice methods: Analysis and application. Cambridge University Press, Cambridge.
Lusk, J.L. and Norwood, F.B. (2005). “Effect of experimental design on choice-based conjoint valuation estimates”. American Journal of Agricultural Economics, 87(3): 771-785. http://doi.org/cgnkq6.
Massey, D.M., Newbold, S.C. and Gentner, B. (2006). “Valuing water quality changes using a bioeconomic model of a coastal recreational fishery”. Journal of EnvironmentalEconomics and Management, 52(1): 482-500. http://doi.org/dmd937.
Meyer, R.J. (2007). “Formal choice models of informal choices: What choice modelling research can (and can’t) learn from behavioural theory”. In Malhotra, N.K. (Ed.): Review of Marketing Research. Emerald Group Publishing Limited, New York: 3-32. http://doi.org/d6g3wv.
Milon, J.W. and Scrogin, D. (2006). “Latent preferences and valuation of wetland ecosystem restoration”. Ecological Economics, 56(2): 162-175. http://doi.org/bmn9h6.
Moeltner, K. and Shonkwiler, J.S. (2005). “Correcting for on-site sampling in random utility models”. American Journal of Agricultural Economics, 87(2): 327-339. http://doi.org/d86xxw.
Murdock, J. (2006). “Handling unobserved site characteristics in random utility models of recreation demand”. Journal of Environmental Economics and Management, 51(1): 1-25. http://doi.org/bqxqkk.
Olsen, S.B. (2009). “Choosing between internet and mail survey modes for choice experiments surveys considering non-market goods”. Environmental and Resource Economics, 44(4): 591-610. http://doi.org/b89d2r.
Olsen, S.B., Lundhede, T.H., Jacobsen, J.B. and Thorsen, B.J. (2011). “Tough and easy choices: Testing the influence of utility difference on stated certainty-in-choice in choice experiments”. Environmental and Resource Economics, 49(4): 491-510. http://doi.org/dw8rhh.
Ouma, E., Abdulai, A. and Drucker, A. (2007). “Measuring heterogeneous preferences for cattle traits among cattle-keeping households in East Africa”. American Journal of Agricultural Economics, 89(4): 1005-1019. http://doi.org/fhvb36.
Provencher, B., Baerenklau, K.A. and Bishop, R.C. (2002). “A finite mixture logit model of recreational angling with serially correlated random utility”. American Journal of Agricultural Economics, 84(4): 1066-1075. http://doi.org/cz5dg8.
Provencher, B. and Bishop, R. (2004). “Does accounting for preference heterogeneity improve the forecasting of a random utility model? A case study”. Journal of Environmental Economics and Management, 48(1): 793-810. http://doi.org/fjgtw4.
Rigby, D., Balcombe, K. and Burton, M. (2009). “Mixed logit model performance and distributional assumptions: Preferences and GM foods”. Environmental and Resource Economics, 42(3): 279-295. http://doi.org/fb69zf.
Rolfe, J. and Windle, J. (2013). “Distance decay functions for iconic assets: Assessing national values to protect the health of the Great Barrier Reef in Australia”. Environmental and Resource Economics, 53(3): 347-365. http://doi.org/wwd.
Sagebiel, J. (2011). “Comparing the latent class model with the random parameters logit. A choice experiment analysis of highly heterogeneous electricity consumers in Hyderabad, India”. Paper presented at the II International Choice Modeling Conference, Leeds.
Scarpa, R. and Bateman, I. (2000). “Efficiency gains afforded by improved bid designs versus follow-up valuation questions in discrete-choice CV studies”. Land Economics, 76(2): 299-311.
Scarpa, R., Gilbride, T., Campbell, D. and Hensher, D. (2009). “Modelling attribute non-attendance in choice experiments for rural landscape valuation”. European Review of Agricultural Economics, 36(2): 151-174. http://doi.org/bbjxjh.
Scarpa, R. and Rose, J. (2008). “Design efficiency for non-market valuation with choice modelling: How to measure it, what to report and why”. Australian Journal of Agricultural and Resource Economics, 52(3): 253-282. http://doi.org/cqm586.
Scarpa, R. and Thiene, M. (2005). “Destination choice models for rock climbing in the Northeastern Alps: A latent class approach based on intensity of preferences”. Land Economics, 81(3): 426-444.
Shen, J. and Saijo, T. (2009). “Does an energy efficiency label alter consumers’ purchasing decisions? A latent class approach based on a stated choice experiment in Shanghai.” Journal of Environmental Management, 90(11): 3561-3573. http://doi.org/ch22hr.
Strazzera, E., Contu, D. and Ferrini, S. (2013). “Check it out! A Monte Carlo analysis of the performance of selection criteria and tests for Choice Experiments models”. Paper presented at International Choice Modelling Conference, Sydney.
Torres, C., Hanley, N. and Riera, A. (2011). “How wrong can you be? Implications of incorrect utility function specification for welfare measurement in choice experiments”. Journal of Environmental Economics and Management, 62(1): 111-121. http://doi.org/chz3tf.
Torres, C., Riera, A. and García, D. (2009). “Are preferences for water quality different for second-home residents?” Tourism Economics, 15(3): 629-651. http://doi.org/fnmvpw.
Train, K.E. (1998). “Recreation demand models with taste differences over people”. Land Economics, 74(2): 230-239.
Train, K.E. (2009). Discrete Choice Methods with Simulation. Cambridge University Press (Second edition), Cambridge.
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