1. Valuing Short Term Beach Closure in a RUM Model of Recreation Demand Using Stated Preference Data Stela Stefanova and George R. Parsons Camp Resources XV August 6 – 7, Wilmington, NC

2. Acknowledgements Funded by the National Park Service Funded by the National Oceanic and Atmospheric Administration’s Coastal Response Research Center at the University of New Hampshire Presently under consideration for a chapter in: “Preference Data for Environmental Valuation”, eds. John Whitehead, Ju-Chin Huang and Tim Haab

3. Outline Motivation Data Padre Island National Seashore Park Linked Model and Welfare Our Approach to Incorporating Delayed Trips Coefficient and Welfare estimates Conclusion

4. Motivation Random Utility Models (RUM) are well suited for valuing seasonal closures of sites However, RUM are not well suited for valuing short term closures when there is substitution across time periods within the same season Short term closures may have little impact on total visitation to the closed site People may be delaying trips, in effect substituting across time periods

5. Data 884 Texas residents living within 200 miles of the Texas Gulf Coast 2692 day trips taken to 65 Texas Gulf Coast beaches between May and September, 2001 Limited choice set to beaches within 300 miles of residence

6. Padre Island National Seashore Padre Island is located near Corpus Christi, Texas. 66 miles along the Texas Gulf Coast Accessible by car, approximately 30 minutes from Corpus Christi and approximately 2.5 hours from San Antonio. North Beach, Malaquite Beach, South Beach, Little Shell and Big Shell Beaches, Mansfield cut 14% of people visited Padre beaches - 394 trips

7. A Linked Model of Site Choice and Trip Frequency Step 1: Discrete choice site selection – Logit – Mixed Logit Step 2: Trip frequency – Negative binomial Bockstael, Hanemann, and Kling. 1987. Herriges, Kling, and Phaneuf. 1999. Parsons, Jakus, and Tomasi. 2003.

8. Beach Characteristics Number of Beaches Mean or % of Beaches Beach length (miles)5.35 Gulf accessBeach is located on the Gulf4874% State parkBeach is part of a state park46% RemoteBeach has a remote location2234% Vehicle freeVehicles not allowed on beach2640% Manual cleaningBeach is routinely manually cleaned3351% Machine cleaningBeach is routinely machined cleaned3655% Rest roomRestrooms located at beach3757% LifeguardsLifeguards at beach17 26% ConcessionConcession located at beach1523% Red tide historyBeach has a recent history of red tide1218% Advisory/Closure history Beach has a recent history of closures and/or advisories 1117%

9. Individual Characteristics Variable Mean or % of Sample (Adjusted for Stratification) Age 41 years Work Fulltime 62% Student 5% Unemployed 5% Children Under 17 49% High School 32% College 24% Graduate School 10% Retire 9% Spanish 9% Female 60% Own Boat 24% Own Pool 24% Own Coastal Property 7%

10. Three Measures of Welfare Loss Per trip Per season Loss to trip ratio

11. Strategy for Incorporating Delayed Trips Using SP These welfare measures rely on RP data Do not capture substitution across time periods in the case of a short term closure Survey questions offered the following options in case of site closure – visit another site now – stay home now but visit the closed site later to “make up” for the lost trip – stay home without making up the trip later

12. SP Data Option% of SP responses Another Beach Now 19% Padre Later 76% Stay Home 5%

13. Strategy for Incorporating Delayed Trips Using SP Two Models Padre Open Model RP data on all trips Padre Closed Model RP data on trips to Padre is replaced with SP data * Trips to other sites assumedthe same * The scaling parameter on the SP choices relative to the RP choices vanishes in estimation. Brownstone, Bunch, and Train. 2000.

14. Strategy for Incorporating Delayed Trips in Welfare Measures Using SP Padre Open (RP data) Choice set: Conventional ApproachOur Approach Padre Closed (RP)Padre Closed (RP/SP) Choice set: non Padre sites delayed trips to Padre Padre sites

15. Strategy for Incorporating Delayed Trips in Welfare Measures Using SP Padre Open (RP data) Padre Utility: Conventional Approach Our Approach Padre Closed (RP)Padre Closed (RP/SP) Padre Utility: 0

16. Strategy for Incorporating Delayed Trips in Welfare Measures Using SP Padre Open (RP data) Expected Utility: Padre Closed (RP) Padre Closed (RP/SP)

17. Strategy for Incorporating Delayed Trips in Welfare Measures Using SP Padre Closed - Conventional Approach Padre Closed - Accounting For Delayed Trips

18. Results Logit PADRE OPEN MODEL VariableMeanT stat. Travel cost-0.022-22.28 Gulf0.6304.529 Restroom0.4144.438 Lifeguard0.0890.89 State park0.3211.224 Length0.2328.214 Machine clean0.9538.52 Vehicle free0.8529.087 Remote0.1181.142 Manual clean0.3383.001 VariableMeanT stat. Concession-0.330-3.405 Red tide-1.738-5.342 Closure-0.526-2.594 Padre ASC1.4777.683 Region 21.1734.224 Region 32.1504.912 Region 41.0802.963 Region 51.6064.843 Region 60.5031.312 PADRE CLOSED MODEL Padre ASC1.1169.289

19. Results Mixed Logit PADRE OPEN MODEL Fixed parametersMeanT stat. Travel cost-0.027-15.28 Restroom0.4194.43 Lifeguard0.1111.039 State park0.3741.398 Length0.2478.437 Machine clean1.0858.860 Manual clean0.3332.893 Concession-0.407-3.906 Red tide-1.645-4.905 Closure-0.487-2.342 Padre ASC1.9118.208 Random ParametersMeanT stat.Std. Dev.T stat. Padre Closed Std. Dev. Gulf0.9042.560.8361.270.823 Vehicle free0.9268.970.0060.030.008 Remote-0.189-1.011.3093.721.299 Region 10.000Fixed0.0000.000.009 Region 21.3024.190.1810.240.136 Region 32.2184.720.0050.020.000 Region 41.1182.720.0720.070.047 Region 51.7474.581.6445.091.704 Region 60.2400.441.9513.611.787 PADRE CLOSED MODEL Padre ASC1.49910.93 Unconstrained in Padre Closed

20. Welfare Loss for Closure of All Padre Beaches (2001$) LogitMixed Logit Conventional approach: Per season10.1311.49 Per trip5.485.40 Loss to trip ratio70.6280.10 Accounting for delayed trips: Per season2.882.62 Per trip1.481.20 Loss to trip ratio83.6676.11

21. Conclusion Included the alternative of delaying a trip in a conventional RUM Estimated losses are 72% to 77% lower when delayed trips are incorporated in the model

23. References Bockstael, N., W. M. Hanemann, and C. L. Kling. 1987. Estimating the Value of Water Quality Improvements in a Recreational Demand Framework. Water Resources Research 23, no. 5: 951- 60. Parsons, G. R., P. Jakus, and T. Tomasi. 2003. A comparison of welfare estimates from four models for linking seasonal recreational trips to multinomial models of site choice,” Journal of Environmental Economics and Management 38(2): 143-157. Brownstone, D., D. S. Bunch, and K. Train. 2000. Joint mixed logit models of stated and revealed preferences for alternative fuel vehicles. Transportation Research Record B, 34.

24. Step 1: Discrete choice site selection Logit

25. Step 1: Discrete choice site selection Mixed logit

26. Step 2: Trip frequency Negative binomial model

27. Negative Binomial Results VariableCoefficientT-Stat. Intercept-2.96-3.98 Iv/beta_tc0.01 lnage0.16-0.10 female-0.09-0.25 fulltime0.15-0.03 childdm0.220.06 property0.24-0.03 ownboat0.310.14 own pool-0.17-0.36 ownsfcst0.13-0.02 spanish-0.07-0.32 gradsch0.460.17 college0.300.11 high sc.-0.23-0.42 retired-0.09-0.41 att0.290.22 Dispersion0.300.25

28. Linked model

29. Welfare in linked model