Effect on recreation benefit estimates from correcting for on-site sampling biases and heterogeneous trip overdispersion in count data recreation demand models (STATA)

Journal of Modern Applied Statistical Methods

Volumn 7, Issue 1, 2008, Pages 331-345

  Martínez Espiñeira, Roberto ^a   Hilbe, Joseph M ^b  

^a MEMORIAL UNIVERSITY OF NEWFOUNDLAND   (Canada)

^b CALIFORNIA INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

Count data; Endogenous stratification; Heterogeneous overdispersion; On site sampling; Zero truncation

Indexed keywords

EID: 67349259773     PISSN: 15389472     EISSN: 15389472     Source Type: Journal    
DOI: 10.22237/jmasm/1209616080     Document Type: Review

References (47)

1. Alberini, A. & D. Reppas (2005). Model misspecification and endogenous on-site sampling in the travel cost method. presented at EAERE 2005 Bremen.
2. Bhat, M. G. (2003). Application of nonmarket valuation to the Florida Keys Marine Reserve Management. Journal of Environmental Management 67 (4), 315-325.
3. Bowker, J. M., D. B. K. English & J. A. Donovan (1996). Toward a value for guided rafting on southern rivers. Journal of Agricultural and Applied Economics 28 (2), 423-432.
4. Braden, J. B. & C. Kolstad (1991). Measuring the Demand for Environmental Quality. Amsterdam: Elsevier.
5. Cameron, A. C. & P. K. Trivedi (1990). Regression-based tests for overdispersion in the poisson model. Journal of Econometrics 46 (3), 347-364.
6. Cameron, A. C. & P. K. Trivedi (2001). Essentials of count data regression. In B. H. Baltagi (Ed.), A Companion to Theoretical Econometrics, pp. 331.348. Oxford, U.K.: Blackwell.
7. Cameron, C. & P. K. Trivedi (1998). Regression Analysis of Count Data. Cambridge: Cambridge University Press.
8. Creel, M. & J. B. Loomis (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.
9. Englin, J. & J. Shonkwiler (1995). Estimating social welfare using count data models: An application under conditions of endogenous stratification and truncation. Review of Economics and Statistics 77, 104-112.
10. Englin, J. E., T. P. Holmes & E. O. Sills (2003). Estimating forest recreation demand using count data models. In E. O. Sills (Ed.), Forests in a Market Economy, Chapter 19, pp. 341.359. Dordrecht, The Netherlands: Kluwer Academic Publishers.
11. Fix, P. & J. Loomis (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), 342-352.
12. Freeman III, A. M. (1993). The Measurement of Environmental and Resource Values: Theory and Methods. Washington D.C.: Resources for the Future.
13. Greene, W. H. (1995). LIMDEP Version 7.0 User.s Manual. Bellport, NY: Econometric Software, Inc.
14. Grogger, J. T. & R. T. Carson (1991). Models for truncated counts. Journal of Applied Econometrics 6 (3), 225-238.
15. Gurmu, S. & P. Trivedi (1996). Excess zeros in count models for recreational trips. Journal of Business and Economic Statistics 14, 469-477.
16. Haab, T. & K. McConnell (2002). Valuing Environmental and Natural Resources: Econometrics of Non-Market Valuation. Cheltenham, UK: Edward Elgar.
17. Hagerty, D. & K. Moeltner (2005). Specification of driving costs in models of recreation demand. Land Economics 81 (1), 127-143.
18. Hellerstein, D. & R. Mendelsohn (1993). A theoretical foundation for count data models. American Journal of Agricultural Economics 75 (3), 604-611.
19. Hesseln, H., J. B. Loomis, A. González-Cabán & S. Alexander (2003). Wildfire effects on hiking and biking demand in New Mexico: A travel cost study. Journal of Environmental Management, 69 (4), 359-368.
20. Hilbe, J. M. (2005). GNBSTRAT: Stata module to estimate generalized negative binomial with endogenous stratification. Statistical Software Components, Boston College Dept. of Economics: http://ideas.repec.org/c/boc/bocode/s456413.html.
21. Hilbe, J. M. & R. Martínez-Espiñeira (2005). NBSTRAT: Stata module to estimate negative binomial with endogenous stratification. Statistical Software Components, Boston College Department of Economics. http://econpapers.repec.org/software/bocbocode/s456414.htm.
22. Hilbe, J.M (2007). Negative Binomial Regression, Cambridge: Cambridge University Press.
23. Lambert, D. (1992). Zero-inflated poisson regression, with an application to defects in manufacturing. Technometrics 34, 1-14.
24. Liston-Heyes, C. & A. Heyes (1999). Recreational benefits from the Dartmoor National Park. Journal of Environmental Management 55 (2), 69-80.
25. Loomis, J. (2003). Travel cost demand model based river recreation benefit estimates with on-site and household surveys: Comparative results and a correction procedure. Water Resources Research 39 (4), 1105.
26. Lucas, R. C. (1963) Bias in estimating recreationists' length of stay from sample interviews. Journal of Forestry, 61(2), 912-913
27. Martínez-Espiñeira, R. (2007) "'Adopt a Hypothetical Pup': A Count Data Approach to the Valuation of Wildlife" Environmental and Resource Economics, 37(2), 335-360.
28. Martínez-Espiñeira, R. & J. Amoako-Tuffour (2008). Recreation Demand Analysis under Truncation, Overdispersion, and Endogenous Stratification: An Application to Gros Morne National Park, Journal of Environmental Management, 88(4), 1320-1332 http://ideas.repec.org/p/wpa/wuwpem/0511007.html.
29. Martínez-Espiñeira, R., J. Amoako-Tuffour & J. M. Hilbe (2006a). Travel cost demand model based river recreation benefit estimates with on-site and household surveys: Comparative results and a correction procedure: Reevaluation. Water Resources Research 42 (W10418). DOI:10.1029/2005WR004798.
30. Martínez-Espiñeira, R., J. B. Loomis, J. Amoako-Tuffour & J. M.Hilbe (2008). Comparing recreation benefits from on-site versus household surveys in count data travel cost demand models with overdispersion, Tourism Economics 14(3), 567-576
31. McConnell, K. E. & I.E.C. Inc. (1986). The damages to recreational activities from PCBs in New Bedford Harbor. Unpublished report prepared for NOAA Ocean Assessment Division. Rockville, MD: December.
32. McKean, J. R., D. Johnson & R. G. Taylor (2003). Measuring demand for.at water recreation using a Two-Stage/Disequilibrium travel cost model with adjustment for overdispersion and self-selection. Water Resources Research 39 (4), 1107.
33. McKean, J. R., D. Johnson, R. G. Taylor & R. L. Johnson (2005). Willingness to pay for non angler recreation at the Lower Snake River reservoirs. Journal of Leisure Research 37 (2), 178-191.
34. Mendes, I. & I. M. Proença (2005). Estimating the recreation value of ecosystems by using a travel cost method approach. WP 2005/08 DE/CIRIUS, Instituto Superior de Economia e Gestão, Universidade Técnica de Lisboa. http://ideas.repec.org/p/ise/isegwp/wp82005.html
35. Mullahy, J. (1986). Specification and testing of some modified count data models. Journal of Econometrics 33, 341-365.
36. Ovaskainen, V., J. Mikkola & E. Pouta (2001). Estimating recreation demand with onsite data: An application of truncated and endogenously stratified count data models. Journal of Forest Economics 7 (2), 125-144.
37. Ozuna, T. & I. A. Gomez (1995). Specification and testing of count data recreation demand functions. Empirical Economics 20 (3), 543-550.
38. Parsons, G. R. (2003). The travel cost model. In P. A. Champ, K. J. Boyle & T. C. Brown (Eds.), A Primer on Nonmarket Valuation, Chapter 9. London: Kluwer Academic Publishing.
39. Phaneuf, D. J. & V. K. Smith (2006). Recreation Demand Models. In K. G. Mäler & J. R. Vincent (Eds.) Handbook of Environmental Economics, Chapter 15. North-Holland Elsevier Vol. 2, Number 2.
40. Platt, J. 2000. "Impact of Fluctuating Reservoir Elevation on Recreation Use and Value." Technical Memorandum #: EC-2000-02, U. S. Bureau of Reclamation, Technical Service Center, Economics Group, Denver CO.
41. Sellar, C., J. Stoll & J. Chavas (1985). Validation of empirical measures of welfare change: A comparison of nonmarket techniques. Land Economics 61, 156-175.
42. Shaw, D. (1988). On-site sample regression: Problems of non-negative integers, truncation, and endogenous stratification. Journal of Econometrics 37, 211-223.
43. Shaw, W. D., E. Fadali & F. Lupi (2003). Comparing consumer's surplus estimates calculated from intercept and general survey data. Proceedings of the W-133 (U.S.D.A.) Regional Economics Group, compiled by J. Scott Shonkwiler. Las Vegas, Nevada, February.
44. Shrestha, K. R., A. F. Seidl & A. S. Moraes (2002). Value of recreational fishing in the Brazilian Pantanal: A travel cost analysis using count data models. Ecological Economics 42 (1-2), 289-299.
45. Sohngen, B., F. Lichtkoppler & M. Bielen (2000). The value of day trips to Lake Erie beaches. Technical Report TB-039, Ohio Sea Grant Extension, Columbus OH.
46. StataCorp (2005). Stata Statistical Software: Release 9.1. College Station, TX: StataCorp LP.
47. Yen, S. T. & W. L. Adamowicz (1993). Statistical properties of welfare measures from count-data models of recreation demand. Review of Agricultural Economics 15, 203-215.