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Recreational Demand for Equestrian Trail-Riding

Published online by Cambridge University Press:  15 September 2016

Melanie Blackwell
Affiliation:
Department of Economics at Washington University in St. Louis, Missouri
Angelos Pagoulatos
Affiliation:
Department of Agricultural Economics at the University of Kentucky in Lexington, Kentucky
Wuyang Hu
Affiliation:
Department of Agricultural Economics at the University of Kentucky in Lexington, Kentucky
Katharine Auchter
Affiliation:
Department of Agricultural Economics at the University of Kentucky in Lexington, Kentucky

Abstract

Using data collected from a combination of on-site and on-line surveys, this study examines recreational demand for equestrian trail-riding in Kentucky. A truncated, negative binomial regression is applied to analyze individuals’ visitation behavior consistent with a travel cost model. Results suggest that distance is the most significant determinant of average annual visits to a particular site. Various trail site characteristics, such as trail length, scenic overlooks, and trail markers, affect the number of visits an individual takes. Geographic information system (GIS) analysis permits the identification of equestrian population centers. Information obtained from this study offers a decision base for policymakers to use to manage existing equestrian trails and locate new ones.

Type
Contributed Papers
Copyright
Copyright © 2009 Northeastern Agricultural and Resource Economics Association 

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References

Adamowicz, W.L., Louviere, J., and Williams, M. 1994. “Combining Revealed and Stated Preference Methods for Valuing Environmental Amenities.” Journal of Environmental Economics and Management 26(3): 271292.Google Scholar
Betz, C., Bergstrom, J., and Bowker, J. 2003. “A Contingent Trip Model for Estimating Rail-Trail Demand.” Journal of Environmental Planning and Management 46(1): 7996.Google Scholar
Boxall, P., and Adamowicz, W. 2002. “Understanding Heterogeneous Preferences in Random Utility Models: A Latent Class Approach.” Environmental and Resource Economics 23(4): 421446.Google Scholar
Cameron, T.A. 1992. “Combining Contingent Valuation and Travel Cost Data for the Valuation of Nonmarket Goods.” Land Economics 68(3): 302317.Google Scholar
Cameron, A.C., and Trivedi, P. 1986. “Econometric Models Based on Count Data: Comparisons and Applications of Some Estimators and Tests.” Journal of Applied Econometrics 1(1): 2953.Google Scholar
Cesario, F., and Knetsch, J. 1976. “A Recreation Site Demand and Benefit Estimation Model.” Regional Studies 10(1): 97104.Google Scholar
DeLoitte Consulting, LLP. 2005. “The Economic Impact of the Horse Industry on the United States.” DeLoitte Consulting LLP, Louisville, KY. Available at http://horsecouncil.org/publications.php#Horsepower (accessed March 5, 2009).Google Scholar
Englin, J., and Shonkwiler, J. 1995. “Estimating Social Welfare Using Count Data Models: An Application to Long-Run Recreation Demand under Conditions of Endogenous Stratification and Truncation.” The Review of Economics and Statistics 77(1): 104112.Google Scholar
Fix, P., and Loomis, J. 1997. “The Economic Benefits of Mountain Biking at One of Its Meccas: An Application of the Travel Cost Method to Mountain Biking in Moab, Utah.Journal of Leisure Research 29(3): 342352.Google Scholar
Freeman, M. III 2003. The Measurement of Environmental and Resource Values (2nd ed.). Resources for the Future, Washington, D.C.Google Scholar
Greene, W.H. 2000. Econometric Analysis (4th ed.). Upper Saddle River, NJ: Prentice Hall.Google Scholar
Greene, W.H. 2007. LIMDEP Version 9.0, Reference Guide. Econometric Software, Inc., Plainview, NJ.Google Scholar
Grogger, J., and Carson, R. 1991. “Models for Truncated Counts.” Journal of Applied Econometrics 6(3): 225238.Google Scholar
Morey, E., and Breffle, W. 2006. “Valuing a Change in a Fishing Site without Collecting Characteristics Data on All Fishing Sites: A Complete But Minimal Model.” American Journal of Agricultural Economics 88(1): 150161.Google Scholar
Parsons, G., Jakus, P., and Tomasi, T. 1999. “A Comparison of Welfare Estimates from Four Models for Linking Seasonal Recreational Trips to Multinomial Logit Models of Site Choice.” Journal of Environmental Economics and Management 38(2): 143157.Google Scholar
Randall, A. 1994. “A Difficulty with the Travel Cost Method.” Land Economics 70(1): 8896.Google Scholar
Shaw, D. 1988. “On-Site Samples’ Regression: Problems of Non-Negative Integers, Truncation, and Endogenous Stratification.” Journal of Econometrics 37(2): 211223.Google Scholar
Shaw, D., and Jakus, P. 1996. “Travel Cost Models of the Demand for Rock Climbing.” Agricultural and Resource Economics Review 25(2): 133142.Google Scholar
Shonkwiler, D., and Shaw, J. 1996. “Hurdle Count-Data Models in Recreation Demand Analysis.” Journal of Agricultural and Resource Economics 21(2): 210219.Google Scholar
Vaughn, W., and Russell, C. 1982. “Valuing a Fishing Day: An Application of a Systematic Varying Parameter Model.” Land Economics 58(4): 450463.CrossRefGoogle Scholar
Ward, F., and Loomis, J. 1986. “The Travel Cost Demand Model as an Environmental Policy Assessment Tool: A Review of Literature.” Western Journal of Agricultural Economics 11(2): 164178.Google Scholar