Adamowicz, W. L., Fletcher, J. J., & Graham-Tomasi, T. (1989). Functional form and the statistical properties of welfare measures. Amer. J. Agr. Econ. 71(2): 414-421.
Alberini, A. (1995). Efficiency vs bias of willingness-to-pay estimates: Bivariate and interval-data models. J. Environ. Econ. Manag. 29(2): 169-180.
- Ben-Akiva, M., & Lerman, S. R. (1985, p.367). Discrete choice analysis: Theory and application to travel demand. Massachussetts, The MIT Press.
Paper not yet in RePEc: Add citation now
Birol, E., Karousakis, K., & Koundouri, P. (2006). Using choice experiment to account for preference heterogeneity in wetland attributes: the case of Cheimaditita wetland in Greece. Ecological Economics 60: 145-156.
Boxall, P. C., & Adamowicz, W. (2002). Understanting heterogeneous preferences in random utility models: A latent class approach. . Environmental and Resource Economics 23: 421-446.
Carlsson, F., & Martinsson, P. (2003). Design techniques for stated preference methods in health economics. Health Econ. 12: 281-294.
Colombo, S., Hanley, N., & Louviere, J. (2009). Modeling preference heterogeneity in stated choice data: an analysis for public goods generated by agriculture. Agricultural Economics 40: 307-322.
Ferrini, S., & Scarpa, R. (2007). Designs with a priori information for nonmarket valuation with choice experiments: A Monte Carlo study. J. Environ. Econ. Manag. 53(3): 342-363.
Fiebig, D. G., Keane, M. P., Louviere, J., & Wasi, N. (2009). The generalized multinomial logit model: Accounting for scale and coefficient heterogeneity. Marketing Science. Articles in Advance: 1-29.
Green, W., & Hensher, D. (2003). A latent class model for discrete choice analysis: contrasts with mixed logit. Transportation Research Part B 37: 681-698.
Greene, W. H., & Hensher, D. A. (2010). Does scale heterogeneity across individuals matter? An empirical assessment of alternative logit models Transportation 37 (3): 413-428.
- Hanemann, W. M. (1984). Applied welfare analysis with quantitative response models. Working paper no. 241. University of California, Berkeley.
Paper not yet in RePEc: Add citation now
- Hensher, D., Rose, J., & Greene, W. (2005). Applied Choice Analysis: a primer. Cambridge, Cambridge University Press.
Paper not yet in RePEc: Add citation now
Herriges, J. A., & Kling, C. L. (1997). The performance of nested logit models when welfare estimation is the goal. Amer. J. Agr. Econ. 79(3): 792-802.
Hynes, S., Hanley, N., & 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.
Johansson, P. O. (1993). Cost-benefit analysis of environmental change. Cambridge, Cambridge University Press.
Kling, C. L. (1987). A simulation approach to comparing multiple site recreation demand models using Chesapeake Bay survey data. Marine Resource Econ. 4: 95-109.
Kling, C. L. (1988). The reliability of estimates of environmental benefits from recreation demand models. Amer. J. Agr. Econ. 70(4): 892-901.
Kling, C. L. (1989). The importance of functional form in the estimation of welfare. Western J. Agr. Econ. 14(1): 168-174.
Kling, C. L. (1997). The gains from combining travel cost and contingent valuation data to value nonmarket goods. Land Econ. 73(3): 428-439.
Kling, C. L., & Thomson, C. J. (1996). The implications of model specification for welfare estimation in nested logit models. Amer. J. Agr. Econ. 78(1): 103-114.
- Louviere, J. J., arson, R. T., Ainslie, A., Cameron, T. A., DeShazo, J. R., Hensher, D. A., Kohn, R., Marley, T., & Street, D. J. (2002). Dissecting the random component of utility. Marketing Letters 13: 177-193.
Paper not yet in RePEc: Add citation now
Louviere, J. J., Hernsher, D. A., & Swait, J. D. (2000). Stated choice methods: analysis and application. Cambridge, UK, Cambridge University Press.
- Louviere, J. J., Meyer, R. J., Bunch, D. S., Carson, R., Dellaert, B., Hanemann, W. M., Hensher, D. A., & Irwin, J. (1999). Combining sources of preference data for modelling complex decision processes. Marketing Letters 10(3): 205-217.
Paper not yet in RePEc: Add citation now
- Louviere, J., & Eagle, T. (2006). Confound it! that pesky little scale constant messes up our convenient assumptions. 2006 Sawtooth Software Conference Washington, USA, Sawtooth Software, Sequem.
Paper not yet in RePEc: Add citation now
Lusk, J. L., & Norwood, F. B. (2005). Effect of experimental design on choice-based conjoint valuation estimates. Amer. J. Agr. Econ. 87(3): 771-785.
Provencher, B., & 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: 793-810.
Scarpa, R., & Bateman, I. (2000). Efficiency gains afforded by improved bid designs versus follow-up valuation questions in discrete-choice CV studies. Land Econ. 76(2): 299-311.
Scarpa, R., & Rose, J. M. (2008). Design efficiency for non-market valuation with choice modelling: how to measure it, what to report and why. Australian J. Agr. Resource Econ. 52(3): 253-282. Torres, C. M., Hanley, N., & Riera, A. (In press). How wrong can you be? Implications of incorrect utility function specification for welfare measurement in choice experiments. Journal of Environmental Economics and Management.
Torres, C. M., Riera, A., & GarcÃa, D. (2009). Are preferences for water quality different for second-home residents? Tourism Econ. 15(3): 629-651.
Train, K. E. (1998). Recreation demand models with taste differences over people. Land Economics 74(2): 230-239.