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Valuing Bag Limits in the NC Charter Boat Fishery with RP and SP Data

Valuing Bag Limits in the NC Charter Boat Fishery with RP and SP Data. John C. Whitehead Department of Economics Appalachian State University Boone, North Carolina 28608 Phone: (828) 262-6121 whiteheadjc@appstate.edu. Co-authors. Chris Dumas, UNCW Craig Landry, ECU Jim Herstine , UNCW.

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Valuing Bag Limits in the NC Charter Boat Fishery with RP and SP Data

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  1. Valuing Bag Limits in the NC Charter Boat Fishery with RP and SP Data John C. Whitehead Department of Economics Appalachian State University Boone, North Carolina 28608 Phone: (828) 262-6121 whiteheadjc@appstate.edu

  2. Co-authors • Chris Dumas, UNCW • Craig Landry, ECU • Jim Herstine, UNCW

  3. Motivation

  4. Outline • Background • Literature • Theory • Data • Methods • Results

  5. NC For-Hire Fleet • 750 vessels • 97% are charter trips • 431,000 passengers • 303,000 charter boat trips • 70,000 fishing trips • $65 million annually in fishing fees • $55 million annually for charter boats • 1445 captain and crew jobs

  6. Literature • Most marine recreational demand literature focuses on the private boat mode • Most charter sector literature considers economic impacts (e.g. Bohnsack et al., 2002) • Some recent studies consider bioeconomicmodelling (e.g., Abbot and Wilen, 2009)

  7. Estimating Benefits • Poor and Breece (2006) • Chesapeake Bay • Travel cost method • Water quality • WTP per angler per trip = $225 • WTP/angler/trip for quality improvement = $85 • Limitation of using the TCM is that many/most charter trips are overnight trips

  8. Value of catch • Large literature, e.g.: • Schuhman (1998) uses RUM • Whitehead and Haab (1999) use RUM • Gillig et al. (2003) use CVM and TCM for red snapper • The problem with using the value of catch rate changes for bag limits is that not all anglers are affected by bag limit.

  9. Household production model • McConnell, Strand and Blake-Hedges (1995): • HPM: q=f(x, hcr) • RUM: site selection depends on predicted q • Welfare: v(q, tc) - v(min[q,b], tc)}/Muy • Problems: data intensive • Is q related to hcr? WHHS (2010) • Is site selection related to predicted q? • Not likely to work with charter boats

  10. Stated Preference Studies • Carson, Hanemann and Steinberg (1990) use CVM for Alaskan salmon • Oh et al. (2005) use choice experiments for Texas red drum • Stoll and Ditton (2006) use CVM for NC bluefin tuna • Whitehead (2006) uses MSB-H approach with CVM

  11. Combined RP/SP data • Allows consideration of situations beyond the range of historical experience • While grounding stated behavior in revealed behavior

  12. Theory / Application $ SP with higher fees RP and SP baseline trips SP with tighter bag limits Trips

  13. 2007 NC For-Hire Survey • Dockside passenger survey produced 1204 usable surveys • Primary purpose, n = 597 • Secondary purpose, n = 607 • 84% are charter trips

  14. Locations • 20% at Roanoke Island • 29% on Outer Banks • 7% on Central Coast • 31% in New Hanover County • 14% in Brunswick County

  15. Characteristics • Most are male • Average age is 40 • Income = $75,000 • Nights away from home • Primary purpose = 3 • Secondary purpose = 6-7 • Charter trips • Primary purpose = 3 • Secondary purpose = 2

  16. Charter boat target species • Primary purpose anglers • Dolphin – 34% • Tuna – 22% • Wahoo – 17% • Secondary purpose anglers • Dolphin – 34% • Spanish mackerel – 20% • Billfish - 13% • Tuna - 13%

  17. Head boat target species • Primary purpose anglers • Snapper – 7% • Grouper – 6% • Wahoo – 17% • Secondary purpose anglers • Bluefish – 13% • Grouper – 8% • Dolphin – 7% • Snapper 5%

  18. RUM Results: Primary purpose

  19. RUM Results: Secondary Purpose

  20. Willingness to pay

  21. Follow-up telephone survey • N = 296, we use 244 anglers who plan to take a future charter trip • More likely to be primary purpose anglers (60% vs 46% of nonrespondents) • More avid • More likely to have been intercepted on the Outer Banks (4 trips vs 3 trips for nonrespondents)

  22. RP Trips (n = 296)

  23. SP Higher Fee Questions

  24. SP Bag Limit Questions

  25. SP Charter Trips (n = 244)

  26. Debriefing Questions

  27. Model

  28. Count Data Models • Y = 0, 1, 2, 3 • Poisson: • E(x) = var(x) =  • Negative binomial: • E(x) =  • Var(x) = (1 + α)

  29. Panel data models

  30. Something I haven’t read

  31. Poisson Models

  32. Negative Binomial Models

  33. Welfare estimates • Willingness to pay per trip • WTPtrip = -1/Higher fee • Willingness to pay to avoid a one fish reduction in the bag limit per trip • WTPbag = -bag /Higher fee

  34. Willingness to Pay

  35. Questions?

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