Using partial site aggregation to reduce bias in random utility travel cost models

Water Resources Research

Volumn 34, Issue 12, 1998, Pages 3595-3603

  Lupi, Frank ^a   Feather, Peter M ^b  

^a MICHIGAN STATE UNIVERSITY   (United States)

^b ECONOMIC RESEARCH SERVICE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

MODELING; RECREATIONAL MANAGEMENT; TRAVEL BEHAVIOR;

MATHEMATICAL MODELS; WATER RESOURCES;

AGGREGATE MODEL; COMPUTATIONAL ADVANTAGES; DISAGGREGATE MODEL; MODEL CONSTRAINTS; POLICY ANALYSIS; RANDOM UTILITY MODEL; TRAVEL COSTS;

AGGREGATES;

EID: 0032408765     PISSN: 00431397     EISSN: None     Source Type: Journal    
DOI: 10.1029/98WR02740     Document Type: Article

References (24)

1. Ben-Akiva, M., and S. R. Lerman, Discrete Choice Analysis: Theory and Application to Travel Demand, MIT Press, Cambridge, Mass., 1985.
2. Bockstael, N. E., W. M. Hanemann, and C. L. Kling, Estimating the value of water quality improvements in a recreational demand framework, Water Resour. Res., 23(5), 951-960, 1987.
3. Bockstael, N. E., K. E. McConnell, and I. E. Strand, A random utility model for sportfishing: Some preliminary results for Florida, Mar. Resour. Econ., 6, 245-260, 1989.
4. Bockstael, N. E., K. E. McConnell, and I. E. Strand Jr., Recreation, in Measuring the Demand for Environmental Quality, edited by J. B. Braden and C. D. Kolstad, pp. 227-355, North-Holland, New York, 1991.
5. Carson, R. T., and W. M. Hanemann, Southcentral Alaska Sport Fishing Economic Study, report, Alaska Dep. of Fish and Game, Juneau, 1987.
6. Caulkins, P. P., R. C. Bishop, and N. W. Bouwes, The travel cost model for lake recreation: A comparison of two methods for incorporating site quality and substitution effects, Am. J. Agric. Econ., 68(2), 291-297, 1986.
7. Estenson, J., Survey of the socioeconomic aspects of Minnesota sport-fishing, Tech. Rep. 90-9, Minn. Cent, for Surv. Res., Minneapolis, 1990.
8. Feather, P. M., Sampling and aggregation issues in random utility model estimation, Am. J. Agric. Econ., 76(4), 772-780, 1994.
9. Feather, P. M., D. Hellerstein, and T. Tomasi, A discrete-count model of recreational demand, J. Environ. Econ. Manage., 29, 214-227, 1995.
10. Feenberg, D., and E. Mills, Measuring the Benefits of Water Pollution Abatement, Academic, San Diego, Calif., 1980.
11. Hanemann, W. M., A methodological and empirical study of recreation benefits of water quality improvement, Ph.D. dissertation, Harvard University, Cambridge, Mass., 1978.
12. Hanemann, W. M., Marginal welfare measures for discrete choice models, Econ. Lett., 13, 129-136, 1983.
13. Hausmann, J. A., G. K. Leonard, and D. McFadden, A utility-consistent, combined discrete choice and count data model: Assessing recreational use losses due to natural resource damage, J. Public Econ., 56, 1-30, 1995.
14. Heiskary, S., and C. B. Wilson, Minnesota Lake Water Quality Assessment Report, Program Dev. Sect., Div. of Water Qual., Minn. Pollut. Control Agency, St. Paul, 1990.
15. Jones, C. A., and Y. D. Sung, Valuation of environmental quality at Michigan recreational sites: Methodological issues and policy applications, final report, contract CR-816247-01-2, Environ. Protect. Agency, Washington, D. C., 1993.
16. Kaoru, Y., and V. K. Smith, 'Black mayonnaise' and marine recreation: Methodological issues in valuing a cleanup, Rep. QE91-02, Resour. for the Future, Washington, D. C., 1990.
17. Kaoru, Y., V. K. Smith, and J. L. Liu, Using random utility models to estimate the recreational value of estuarine resources, Am. J. Agric. Econ., 77(1), 141-151, 1995.
18. Kling, C. L., and C. Thomson, The implications of model specification for welfare estimation in nested logit models, Am. J. Agric. Econ., 78(1), 103-114, 1996.
19. Lin, P. C., R. M. Adams, and R. P. Berrens, Welfare effects of fishery policies: Native american treaty rights and recreational salmon fishing, J. Agric. Resour. Econ., 21(2), 263-276, 1996.
20. McConnell, K. E., and N. E. Bockstael, Aggregation in recreation economics: Issues of estimation and benefit measurement, Northeast. J. Agric. Resour. Econ., 13, 181-186, 1984.
21. Peters, T., W. L. Adamowitz, and P. C. Boxall, Influence of choice set considerations in modeling the benefits from improved water quality, Water Resour. Res., 31(7), 1781-1787, 1995.
22. Train, K., Qualitative Choice Analysis, MIT Press, Cambridge, 1986.
23. U.S. Environmental Protection Agency, Guidelines for Performing Regulatory Impact Analysis, Rep. EPA-230-01-84-003, Washington, D. C., 1991.
24. Waters, S. M., and K. J. Dietz, Measuring the stability of choice set randomization in discrete choice models, paper presented at Annual Meeting, Am. Agric. Econ. Assoc., San Antonio, Tex., July 31, 1996.