Hostname: page-component-cd9895bd7-8ctnn Total loading time: 0 Render date: 2024-12-25T19:49:59.910Z Has data issue: false hasContentIssue false
  • English
  • Français

Joint Estimation of Revealed and Stated Preference Data: An Application to Recreational Red Snapper Valuation

Published online by Cambridge University Press:  15 September 2016

Dhazn Gillig ,
Richard Woodward ,
Teofilo Ozuna Jr.  and
Wade L. Griffin
Dhazn Gillig
Affiliation:
Department of Agricultural Economics, Texas A&M University
Richard Woodward
Affiliation:
Department of Agricultural Economics, Texas A&M University
Teofilo Ozuna Jr.
Affiliation:
Department of Economics and Finance, University of Texas-Pan American
Wade L. Griffin
Affiliation:
Department of Agricultural Economics, Texas A&M University
Get access Rights & Permissions [Opens in a new window]

Abstract

This study extends the joint estimation of revealed and stated preference data literature by accounting for truncation in the revealed preference data. The analytical model and estimation procedure are used to estimate the value of recreational red snapper fishing in the Gulf of Mexico. This recreational red snapper valuation is decomposed into its direct and indirect components. As expected, the value of recreational red snapper fishing using the joint revealed-stated preference model proposed in this analysis is bracketed on the upper limit by the value obtained using the contingent valuation method and on the lower limit by the travel cost method. The results also indicate that the joint model improves the precision of estimated recreational red snapper valuation.

Keywords

bivariate normal distributioncontingent valuationrecreation demandtravel cost
Type
Articles
Information
Agricultural and Resource Economics Review , Volume 32 , Issue 2 , October 2003 , pp. 209 - 221
Copyright
Copyright © 2003 Northeastern Agricultural and Resource Economics Association 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Bockstael, N. E., and Kling, C. L. (1988). “Valuing Environmental Quality: Weak Complementary with Sets of Good.” American Journal of Agricultural Economics 70, 654–662.Google Scholar
Bockstael, N. E., McConnell, K. E., and Strand, I. E. (1989). “A Random Utility Model for Sportfishing: Some Preliminary Results for Florida.” Marine Resource Economics 6, 245–260.Google Scholar
Bockstael, N. E., and Strand, I. E. (1987). “The Effect of Common Sources of Regression Error on Benefit Estimates.” Land Economics 63, 11–20.Google Scholar
Bockstael, N. E, Strand, I. E., and Hanemann, W. M. (1987). “Time and the Recreational Demand Model.” American Journal of Agricultural Economics 69, 293–302.Google Scholar
Bockstael, N. E., Strand, I. E., McConnell, K. E., and Arsanjani, F. (1990). “Sample Selection Bias in the Estimation of Recreation Demand Functions: An Application to Sportfishing.” Land Economics 66, 40–49.Google Scholar
Brown, A. Jr., Bohnsack, J. A., and Harper, D. (1989). “Automated Landings Assessment for Responsive Management (ALARM): Gulf of Mexico Commercial Reef Fish Landings.” Contribution No. CRD-89/90-02, National Oceanic and Atmospheric Administration, National Marine Fisheries Service, Southeast Fisheries Center, Miami Laboratory, Miami, FL.Google Scholar
Cameron, T. A. (1992). “Combining Contingent Valuation and Travel Cost Data for the Valuation of Nonmarket Goods.” Land Economics 68, 302–317.Google Scholar
Cameron, T. A., and Quiggin, J. (1994). “Estimation Using Contingent Valuation Data from a ‘Dichotomous Choice with Follow-up’ Questionnaire.” Journal of Environmental Economics and Management 27, 218–234.Google Scholar
Carson, R. T., Flores, N. E., Martin, K. M., and Wright, J. L. (1996, February). “Contingent Valuation and Revealed Preference Methodologies: Comparing the Estimates for Quasi-Public Goods.” Land Economics 72, 80–99.Google Scholar
Cesario, F. J., and Knetsch, J. L. (1976). “Time Bias in Recreation Benefit Estimates.” Land Economics 52, 32–41.Google Scholar
Cohen, A. C. (1955). “Restriction and Selection in Samples from Bivariate Normal Distribution.” Journal of the American Statistical Association 50, 884–893.Google Scholar
Englin, J., and Cameron, T. A. (1996). “Augmenting Travel Cost Models with Contingent Behavior Data: Poisson Regression Analysis with Individual Panel Data.” Journal of Environmental Economics and Management 7, 133–147.Google Scholar
Gillig, D., Ozuna, T., and Griffin, W. L. (2000). “The Value of the Gulf of Mexico Recreational Red Snapper Fishery.” Marine Resource Economics 15, 127–139.Google Scholar
Goodyear, C. P., and Phares, P. (1990). “Status of Red Snapper Stocks of the Gulf of Mexico: Report for 1990.” Contribution No. CRD 89/90-05, National Oceanic and Atmospheric Administration, National Marine Fisheries Service, Southeast Fisheries Center, Miami Laboratory, Miami, FL.Google Scholar
Greene, G., Moss, C. B., and Spreen, T. H. (1997). “Demand for Recreational Fishing in Tampa Bay, Florida: A Random Utility Approach.” Marine Resource Economics 12, 293–306.Google Scholar
Greene, G., Moss, C. B., and Thunberg, E. M. (1994). “Estimation of Recreational Anglers’ Value of Reef-Fish in the Gulf of Mexico.” Unpublished paper, Gulf of Mexico Fishery Management Council, Socioeconomic Assessment Panel Meeting, Tampa, FL.Google Scholar
Greene, W. H. (1993). Econometric Analysis, 2nd edition. Don Mills, Ontario: Macmillan Publishing Co. Google Scholar
Gurmu, S., and Trivedi, P. K. (1992). “Overdispersion Tests for Truncated Poisson Regression Models.” Journal of Econometrics 54, 347–370.Google Scholar
Haab, T. C, Whitehead, J., and McConnell, T. (2000). “The Economic Value of Marine Recreational Fishing in the Southeast United States: 1997 Southeast Economic Data Analysis.” Report prepared for National Marine Fisheries Service, Southeast Regional Office, St. Petersburg, FL.Google Scholar
Hanemann, W. M. (1984). “Welfare Evaluations in Contingent Valuation Experiments with Discrete Responses.” American Journal of Agricultural Economics 66, 332–341.Google Scholar
Hanley, N., Shogren, J. F., and White, B. (1997). “Environmental Economics: In theory and Practice.” New York: Oxford University Press.Google Scholar
Holiman, S. G. (1999). “Economic Summary of the Gulf of Mexico Reef Fish Recreational Fishery.” Report prepared for National Oceanic and Atmospheric Administration (NOAA) Project No. SERO-ECON-00-02, National Marine Fisheries Service, Southeast Regional Office, St. Petersburg, FL.Google Scholar
Huang, J.-C., Haab, T. C., and Whitehead, J. C. (1998). “Willingness to Pay for Quality Improvements: Should Revealed and Stated Preference Data Be Combined?” Journal of Environmental Economics and Management 34, 240–255.Google Scholar
Johnson, N. L., and Kotz, S. (1972). Distributions in Statistics: Continuous Multivariate Distributions. New York: John Wiley.Google Scholar
Kling, C. L. (1997). “The Gains from Combining Travel Cost and Contingent Valuation Data to Value Nonmarket Goods.” Land Economics 73, 428–439.Google Scholar
Larson, D. M. (1991). “Recovering Weakly Complementary Preferences.” Journal of Environmental Economics and Management 21, 97–108.Google Scholar
Loomis, J. B. (1996). “Panel Estimators Useful for Analyzing Combined Revealed and Stated Preference Dichotomous Choice Data: Application to Visit and Dichotomous Choice CVM Responses for Instream Flow.” Paper presented at the 1996 AERE Workshop, Lake Tahoe, CA.Google Scholar
Loomis, J. B, Brown, T., Lucero, B., and Peterson, G. (1996). “Improving Validity Experiments of Contingent Valuation Methods: Results of Efforts to Reduce the Disparity of Hypothetical and Actual Willingness to Pay.” Land Economics 72, 450–461.Google Scholar
Maddala, G. S. (1983). Limited-Dependent and Qualitative Variables in Econometrics. New York: Cambridge University Press.Google Scholar
Mäler, K. G. (1974). Environmental Economics: A Theoretical Inquiry. Baltimore, MD: The Johns Hopkins University Press.Google Scholar
McConnell, K. E. (1975). “Some Problems in Estimating the Demand for Outdoor Recreation.” American Journal of Agricultural Economics 57, 330–334.Google Scholar
McConnell, K. E., and Strand, I. E. (1981). “Measuring the Cost of Time in Recreation Demand Analysis: An Application to Sportfishing.” American Journal of Agricultural Economics 63, 153–156.Google Scholar
Milon, J. W., Thunberg, E. M., Adams, C. M., and Lin, C. T. J. (1994). “Recreational Anglers’ Valuation of Near-Shore Marine Fisheries in Florida.” Report prepared for the Florida Marine Fisheries Commission under Contract No. C-705, Florida Department of Natural Resources, Gainesville, FL.Google Scholar
Niklitschek, M., and Leon, J. (1996). “Combining Intended Demand and Yes/No Responses in the Estimation of Contingent Valuation Models.” Journal of Environmental Economics and Management 31, 387–402.Google Scholar
Parsons, G. R., and Kealy, M. J. (1992). “Randomly Drawn Opportunity Sets in a Random Utility Model of Lake Recreation.” Land Economics 68, 93–106.Google Scholar
Varian, H. R. (1992). Microeconomic Analysis, 3rd edition. New York: W. W. Norton & Co., Inc. Google Scholar