Advanced SearchSearch Tips
Estimating Consumer Surplus for Recreational Sea Fishing using Individual Travel Cost Method
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
  • Journal title : Ocean and Polar Research
  • Volume 30, Issue 2,  2008, pp.141-148
  • Publisher : Korea Institute of Ocean Science & Technology
  • DOI : 10.4217/OPR.2008.30.2.141
 Title & Authors
Estimating Consumer Surplus for Recreational Sea Fishing using Individual Travel Cost Method
Pyo, Hee-Dong; Park, Cheol-Hyung; Chung, Jin-Ho;
  PDF(new window)
This paper aims at estimating consumer surplus for recreational sea fishing in Tongyeong coastal area using individual travel cost method. A Poisson model (PM), a negative binomial model (NBM), a truncated Poisson model (TPM), and a truncated negative binomial model (TNBM) are applied for individual travel cost method in order to account characteristics of count data (non-negative discrete data.) The survey was conducted for 462 inshore anglers using personal interview method in Tongyeong during July and October 2007. Respondents were asked about how often they do fishing, travel costs, catch, income, and so on. Because of over-dispersion problem in PM and TPM, NBM and TNBM were considered to be more appropriate statistically. All parameters estimated are statistically significant and theoretically valid. As the results based on TNBM, consumer surplus per trip was estimated to be 183,486 won, total consumer surplus per person and per year 3,399,658 won, and the marginal effect of consumer surplus on % changes in catch rate is 185,372 won.
individual travel cost method;Truncated Negative Binomial Model (TNBM);consumer surplus for recreational sea fishing;over-dispersion;count data;
 Cited by
통영바다목장화사업의 경제적 타당성평가,표희동;

Ocean and Polar Research, 2009. vol.31. 4, pp.305-318 crossref(new window)
유어낚시 인구, 조획량, 지출 추정 연구,이희찬;

한국수산경영학회지:수산경영론집, 2010. vol.41. 2, pp.45-60
CVM을 이용한 바다낚시 자원풍도 증가에 대한 지불의사액 추정에 관한 연구,남종오;박철형;

Ocean and Polar Research, 2016. vol.38. 3, pp.235-245 crossref(new window)
허베이 스피리트호의 기름유출에 따른 바다유어낚시어선 이용객의 경제적 손실평가연구,표희동;

Ocean and Polar Research, 2014. vol.36. 3, pp.289-302 crossref(new window)
가산자료모형을 이용한 서해 태안군 유어객의 편익추정,최종두;

자원환경경제연구, 2014. vol.23. 2, pp.331-347 crossref(new window)
TCM을 이용한 칠갑저수지의 레크리에이션 편익 분석,홍승지;김대식;

농촌계획, 2016. vol.22. 3, pp.97-106 crossref(new window)
Estimating a Total Demand Function for Sea Angling Pursuits, Ecological Economics, 2017, 134, 73  crossref(new windwow)
Evaluating the Economic Damages to Anglers of the Marine Recreational Charter due to the Herbei Spirit Vessel Oil Spill, Ocean and Polar Research, 2014, 36, 3, 289  crossref(new windwow)
Estimation of the Willingness to Payment of Sea-anglers about Increase in Abundance of Fish Resources Using CVM, Ocean and Polar Research, 2016, 38, 3, 235  crossref(new windwow)
Measuring Recreational Benefits of Chilgap Reservoir Using TCM, Journal of Korean Society of Rural Planning, 2016, 22, 3, 97  crossref(new windwow)
Assessing the Economic Feasibility of a Marine Ranching Project in Tongyoung, Ocean and Polar Research, 2009, 31, 4, 305  crossref(new windwow)
Estimating the Economic Value of Recreation Sea Fishing in the Yellow Sea: An Application of Count Data Model, Environmental and Resource Economics Review, 2014, 23, 2, 331  crossref(new windwow)
Irish coarse and game anglers’ preferences for fishing site attributes, Fisheries Research, 2017, 190, 103  crossref(new windwow)
김도훈. 2005. 여행비용모형 분석을 통한 유어 활동의 경제적 가치 추정. 수산경영논집, 36, 121-134

박철형. 2005. 유어 낚시인구의 사회경제학적 특성과 출조빈도함수의 추정에 관한 연구. 수산경영논집, 36, 81-101

소국섭, 이희찬. 2007. 절단된 포아송모형을 활용한 골프수요 영향요인연구. 한국관광학회지 관광학연구, 31, 9-27

송운강. 2004. 경포 해수욕장의 경제적 가치추정: 가산자료모형을 이용한 개인여행비용분석. 한국관광학회지 관광학연구, 28, 11-26

송운강, 류환경. 2005. TCM의 여행비용변수에 대한 논의. 관광연구저널, 19, 125-137

유승훈, 양창영. 2005. 가산자료모형을 이용한 해양오염사고 발생횟수의 분석. 해양정책연구, 20, 33-56

이희찬. 2004. 주5일 근무제가 관광수요에 미치는 영향: 가산 자료 관광수요모형의 적용. 한국관광학회지 관광학연구, 28, 43-61

이희찬, 한진영. 2004. 전시관람수요의 결정요인: 절단된 가산자료모형의 적용. 한국관광학회지 관광학연구, 28, 307-326

한상현, 조광익. 2004. 모형적합도 검정을 통한 여행비용모형 추정에 관한 연구: 역사유산 관광자원을 중심으로. 한국관광학회지 관광학연구, 28, 145-168

한상현, 조광익. 2006. 산악 국립공원의 비시장가치 추정에 관한 연구: 주왕산 국립공원에 대한 개인별 여행비용모형의 적용. 관광연구, 21, 113-129

해양경찰청. 2007. 해양경찰백서. 해양경찰청

허윤정, 이승래. 2007. 가산자료모형을 이용한 송정해수욕장의 경제적 가치추정: 비수기 해수욕장의 가치추정. 수산경영논집, 38, 79-101

Bergstrom, J.C. and H.K. Cordell. 1991. An Analysis of the demand for and value of outdoor recreation in the United States. J. Leis. Res., 23, 67-86

Cameron, A.C. and P.K. Trivedi. 1986. Econometric models based on count data: Comparisons and applications of some estimators and tests. J. Appl. Econom., 1(1), 29-53 crossref(new window)

Cameron, A.C. and P.K. Trivedi. 1998. Regression analysis of count data. Cambridge University Press, Cambridge. 411 p

Creel, M. and J. Loomis. 1993. Theoretical and empirical advantages of truncated count data estimators for analysis of deer hunting in California. Am. J. Agr. Econ., 72(2), 434-441 crossref(new window)

Curtis, J.A. 2002. Estimating the demand for salmon angling in Ireland. Econ. Social Review, 33(3), 319-332

Hagerty, D. and K. Moeltner. 2005. Specification of driving costs in models of recreation demand. Land Econ., 81(1), 127-143 crossref(new window)

Hellerstein, D. and R. Mendelsohn. 1993. A theoretical foundation for count data models. Ame. J. Agr. Econ., 75, 604-611 crossref(new window)

Loomis, J.B., R. Rosenberger, and R.K. Sjrestha. 1999. Updated estimates of recreation values for the RPAprogram by assessment region and use of meta-analysis for recreation benefit transfer. Colorado State University, Final Report for the USDA Forest Services. 66 p

O'Neil, M.F. and M.J. Faddy. 2003. Use of binary and truncated negative binomial modelling in the analysis of recreational catch data. Fish. Res., 60, 471-477 crossref(new window)

Pradhan, N.C. and P. Leung. 2006. A Poisson and negative binomial regression model of sea turtle interaction in Hawaii's longline fishery. Fish. Res., 78, 309-322 crossref(new window)

Shaw, D. 1988. On-site sample's regression: Problems of non-negative integers, truncation, and endogeneous selection. J. Econom., 37(2), 211-223 crossref(new window)

Shrestha, R.K., A.F. Seidl, and A.S. Moraes. 2002. Value of recreational fishing in the Brazilian Pantanal: A travel cost analysis using count data models. Ecol. Econ., 42, 289-299 crossref(new window)

Ward, F.A. and D.J. Beal. 2000. Valuing nature with travel cost models: A manual. Edgar Elgar, Cheltenham. 255 p

Ward, F.A. and J.B. Loomis. 1986. The travel cost demand model as an environmental policy assessment tool: A review of literature. J. Agr. Resource Econ., 11(2), 164-178

Yen, S.T. and W.L. Adamowicz. 1993. Statistical properties of welfare measures from count-data models of recreation demand. Rev. Agr. Econ., 15(2), 203-215 crossref(new window)