Abstract
In this article, we apply count-data travel-cost methods to a truncated sample of visitors to estimate the Peneda-Gerês National Park (PGNP) average consumer surplus (CS) for each day of visit. The measurement of recreation demand is highly specific because it is calculated by number of days of stay per visit. We therefore propose the application of altered truncated count-data models or truncated count-data models on grouped data to estimate a single, on-site individual recreation demand function, with the price (cost) of each recreation day per trip equal to out-of-pocket and time travel plus out-of-pocket and on-site time costs. We further check the sensitivity of coefficient estimations to alternative models and analyse the welfare measure precision by using the delta and simulation methods by Creel and Loomis. With simulated limits, CS is estimated to be €194 (range €116 to €448). This information is of use in the quest to improve government policy and PNPG management and conservation as well as promote nature-based tourism. To our knowledge, this is the first attempt to measure the average recreation net benefits of each day of stay generated by a national park by using truncated altered and truncated grouped count-data travel-cost models based on observing the individual number of days of stay.
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Bartczak A, Lindhjem H, Navrud S, Zandersen M, Zylicz T (2008) Valuing forest recreation on the national level in a transition economy: the case of Poland. Forest Policy and Economics 10:467–472
Beal DJ (1995) A travel cost analysis of the value of Carnarvon Gorge National Park for recreational use. Review of Marketing and Agricultural Economics 63:292–303
Bell F, Leeworthy VR (1990) Recreational demand by tourists for saltwater beach days. Journal of Environmental Economics and Management 18:189–205
Bhat MG (2003) Application of non-market valuation to the Florida Keys Marine Reserve Management. Journal of Environmental Management 67:315
Bockstael NE, McConnell KE (1999) The behavioral basis of non-market valuation. In: Herriges JA, Kling CL (eds) Valuing recreation and the environment: revealed preference methods in theory and practice. Edward Elgar, Cheltenham, pp 1–32
Bockstael NE, Strand IE, Hanneman WM (1987) Time and the recreational demand model. American Journal of Agricultural Economics 69:293
Bowker JM, Leeworthy VR (1998) Accounting for ethnicity in recreation demand: a flexible count-data approach. Journal of Leisure Research 30:64–78
Burt OR, Brewer D (1971) Estimation of net social benefits from outdoor recreation. Econometrica 39:813–827
Cesario FJ (1976) Value of time in recreation benefits studies. Land Economics 52:291
Cesario FJ, Knetsch JL (1970) Time bias in recreation benefit estimates. Water Resources Research 6:700
Chakraborty K, Keith JE (2000) Estimating the recreation demand and economic value of mountain biking in Moab, Utah: an application of count-data models. Journal of Environmental Planning and Management 43:461–469
Creel M, Loomis J (1990) Theoretical and empirical advantages of truncated count-data estimators for analysis of deer hunting in California. American Journal of Agricultural Economics 72:434–441
Creel M, Loomis J (1991) Confidence intervals for welfare measures with application to a problem of truncated counts. The Review of Economics and Statistics 73:370–373
Crooker JR (2004) Valuing resource access with seminonparametric techniques: an application to clear lake. Working paper 04-WP 352. Iowa State University, Centre for Agricultural ND Rural Development. http://www.card.iastate.edu/publications/DBS/PDFFiles/04wp352.pdf. Accessed August 18, 2011
Earnhart D (2004) Time is money: improved valuation of time and transportation costs. Environmental and Resource Economics 29:159
Egan K, Herriges J (2006) Multivariate count-data regression models with individual panel data from on-site sample. Journal of Environmental Economics and Management 52:567–581
Englin J, Moeltner K (2004) The value of snowfall to skiers and boarders. Environmental and Resource Economics 29:123–136
Englin J, Shonkwiler JS (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 77:104–112
Fletcher JJ, Adamowicz WL, Graham-Tomasi T (1990) The travel cost model of recreation demand. Leisure Sciences 12:119–149
Font AR (2000) Mass tourism and the demand for protected natural areas: a travel cost approach. Journal of Environmental Economics and Management 39:97–116
Freeman AM III (2003) The measurement of environmental and resource values: theory and methods. Resources for the Future, Washington, DC
Grogger J, Carson R (1991) Models for truncated counts. Journal of Applied Econometrics 6:225–238
Gurmu S (1991) Tests for detecting overdispersion in the positive Poisson regression model. Journal of Business and Economic Statistics 9:215–222
Gurmu S, Trivedi PK (1994) Recent development in event count models: a survey. Discussion paper no. 261. Thomas Jefferson Centre, Department of Economics, University of Virginia, Virginia
Gurmu S, Trivedi PK (1996) Excess zeros in count models for recreational trips. Journal of Business and Economic Statistics 14:469–477
Haab TC, McConnell KE (2002) Valuing environmental and natural resources. The econometrics of non-market valuation. Edward Elgar, Orthampton, MA
Hagerty D, Moeltner K (2005) Specification of driving costs in models of recreation demand. Land Economics 81:127–143
Hanemann WM (1999) The economic theory of WTP and WTA. In: Bateman IJ, Willis KG (eds) Valuing environmental preferences. Oxford University Press, New York, NY, pp 42–96
Heberling MT, Templeton JJ (2009) Estimating the economic value of national parks with count-data models using on-site, secondary data: the case of the Great Sand Dunes National Park and Preserve. Environmental Management 43:619–627
Hellerstein D (1991) Using count-data models in travel cost analysis with aggregated data. American Journal of Agricultural Economics 73:860–867
Hellerstein D, Mendelsohn R (1993) A theoretical foundation for count-data models, with application to a travel cost model. American Journal of Agricultural Economics 75:604–611
Hellström J (2006) A bivariate count-data model for household tourism demand. Journal of Applied Econometrics 21:213–226
Hesseln H, Loomis JB, Gonzalez-Caban A, Alexander S (2003) Wildfire effects on hiking and biking demand in New Mexico: a travel cost study. Journal of Environmental Management 69:359
Hof JG, King DA (1992) Recreational demand by tourists for saltwater beach days: comment. Journal of Environmental Economics and Management 22:281–291
Kealy MJ, Bishop RC (1986) Theoretical and empirical specifications issues in travel cost demand studies. American Journal of Agricultural Economics 68:660–667
Larson DM (1993a) Joint recreation choices and implied values of time. Land Economics 69:273–286
Larson DM (1993b) Separability and the shadow value of leisure time. American Journal of Agricultural Economics 75:572–577
Larson DM, Shaikh SL (2004) Recreation demand choices and revealed values of leisure time. Economic Enquiry 42:264–278
Liston-Heyes C, Heyes A (1999) Recreational benefits from the Dartmoor National Park. Journal of Environmental Management 55:264–278
Long JS (1997) Regression models for categorical and limited dependent variables. Sage, Thousand Oaks, CA
Loomis J (2006) A comparison of the effect of multiple destination trips on recreation benefits as estimated by travel cost and contingent valuation methods. Journal of Leisure Research 38:46–60
Mäler KG (1971) A method of estimating social benefits from pollution control. Swedish Journal of Economics 73:121–133
Mäler KG (1974) Environmental economics: a theoretical inquiry. Johns Hopkins Press, Baltimore, MD
Martínez-Espiñeira R, Amoako-Tuffour J (2008) Recreation demand analysis under truncation, overdispersion, and endogenous stratification: an application to Gros Morne National Park. Journal of Environmental Management 88:1320–1332
McConnel KE (1992) On-site time in the demand for recreation. American Journal of Agricultural Economics 74:918
McKean JR, Johnson D, Taylor RG (2003) Measuring demand for flat water recreation using a two-stage/disequilibrium travel cost model with adjustment for overdispersion and self-selection. Water Resources Research 39:1107
Meisner C, Wang H, Laplante B (2008) Welfare measurement convergence through bias adjustments in general population and on-site surveys: an application to water-based recreation at Lake Sevan, Armenia. Journal of Leisure Research 40:458–478
Morey ER (1994) What is consumer surplus per day of use, when is it a constant independent of the number of days of the number of days of use, and what does it tell us about consumer surplus? Journal of Environmental Economics and Management 26:215–303
Ovaskainen V, Mikkola J, Pouta E (2001) Estimating recreation demand with on-site data: an application of truncated and endogenously stratified count-data models. Journal of Forest Economics 7:125–142
Parsons GR (2004) The travel cost model. In: Champ PA, Boyle KJ, Brown TC (eds) A primer on non-market valuation. Kluwer, Dordrecht, the Netherlands
Randall A, Stoll JR (1980) Consumer’s surplus in commodity space. American Economic Review 70:71–83
Rockel M, Kealy J (1991) The value of nonconsumptive wildlife recreation in the United States. Land Economics 67:422–434
Santos JML (1997) Valuation and cost-benefit analysis of multi-attribute environmental changes. Doctoral thesis, Department of Town and Country Planning, University of Newcastle-Upon-Tyne, Newcastle
Santos Silva JMC (1997) Generalised Poisson regression for positive count-data. Communications in Statistics-Simulation Methods 26:423–430
Santos Silva JMC (2001) A score test for non-nested hypothesis with applications to discrete data models. Journal of Applied Econometrics 16:577–597
Sarker R, Surry I (1998) Economic value of big game hunting: the case of moose hunting in Ontario. Journal of Forest Economics 4:29–60
Sarker R, Surry I (2004) The fast decay process in outdoor recreational activities and the use of alternative count-data models. American Journal of Agricultural Economics 86:701–715
Shaw D (1988) On-site sample’s regression: problems of non-negative integers, truncation, and endogenous stratification. Journal of Econometrics 37:211–223
Shaw WD (1992) Searching for the opportunity cost of an individual’s time. Land Economics 68:107–115
Shaw WD, Feather P (1999) Possibilities for including the opportunity cost of time in recreation demand systems. Land Economics 75:592
Shonkwiler JS (1999) Recreation demand systems for multiple site count-data travel cost models. In: Herriges JA, Kling CL (eds) Valuing recreation and the environment. Edward Elgar, Cheltenham, pp 253–269
Shrestha RK, Taylor VS, Clark J (2007) Valuing nature-based recreation in public natural areas of the Apalachicola River Region, Florida. Journal of Environmental Management 85:977–985
Smith VK, Desvouges WH, McGivney MP (1983) The opportunity cost of travel time in recreation demand models. Land Economics 59:259
Vuong QH (1989) Likelihood ratio tests for model selection and non-nested hypothesis. Econometrica 57:307–333
Walsh RG (1986) Recreation economic decisions: comparing benefits and costs. Venture, Pennsylvania
Walsh RB, Johnson D, Mckean J (1988) Review of outdoor recreation economic demand studies with non-market benefit estimates 1968–1988. Technical report number 54, Colorado Water Resources Research Institute, Colorado State University, Forth Collins. http://www.cwi.colostate.edu/publications/tr/54.pdf. Accessed August 18, 2011
Ward FA, Beal D (2000) Valuing nature with travel cost models. Edward Elgar, Cheltenham
Willig RD (1976) Consumer’s surplus without apology. American Economic Review 66:589–597
Wilman EA (1980) The value of time in recreation benefit studies. Journal of Environmental Economics and Management 7:272
Wilman EA (1987) A simple repackaging model of recreational choices. American Journal of Agricultural Economics 69:603–612
Winkelmann R (2003) Econometric analysis of count-data. Springer, New York
Yen ST, Adamowicz WL (1993) Statistical properties of welfare measures from count-data models of recreation demand. Review of Agricultural Economics 15:203–215
Zawacki WT, Allan M, Bowker JM (2000) A travel cost analysis of non-consumptive wildlife-associated recreation in the United States. Forest Science 46:496–506
Acknowledgments
Financial support was received from the Fundação para a Ciência e Tecnologia, FCT/POCTI, partially funded by FEDER and is gratefully appreciated. We are especially indebted to João Santos Silva for many useful comments and suggestions preparation of this manuscript. We also thank the important editors’ and reviewers’ comments and suggestions and the efforts of our native English speakers. Any remaining errors are, of course, our own.
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Mendes, I., Proença, I. Measuring the Social Recreation Per-Day Net Benefit of the Wildlife Amenities of a National Park: A Count-Data Travel-Cost Approach. Environmental Management 48, 920–932 (2011). https://doi.org/10.1007/s00267-011-9733-1
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DOI: https://doi.org/10.1007/s00267-011-9733-1