Environmental and Resource Economics

, Volume 49, Issue 3, pp 311–325 | Cite as

Heterogeneous Response to Marine Reserve Formation: A Sorting Model approach

Open Access
Article

Abstract

The bioeconomic impacts of spatial fisheries management hinge on how fishing vessels reallocate their effort over space. However, empirical studies face two challenges: heterogeneous behavioral responses and unobservable resource abundance. This paper addresses these two problems simultaneously by using an unusual data set and an estimation technique developed in the industrial organization literature. We apply the methods to location and species choices in the Gulf of Mexico reef-fish fishery. The models are used to explore spatial effort substitution in response to two marine reserves. Individual attributes from a survey of vessel captains are linked to each fisherman’s observed daily trip information to control for observable heterogeneity. Some unobservable abundance information is captured by location- and species-specific constants and estimated by contraction mapping. The empirical results confirm that there is significant heterogeneity in fishermen’s response to the formation of marine reserves. They also show that ignoring unobservable abundance information will lead to significant bias in predicting spatial fishing effort.

Keywords

Marine reserves Locational sorting Heterogeneous behavior Survey 

JEL Classification

Q22 C35 

References

  1. Abbott JK, Wilen JE (2010) Voluntary cooperation in the commons? evaluating the sea state program with reduced form and structural models. Land Econ 86(1): 131–154Google Scholar
  2. Bayer P, Timmins C (2005) On the equilibrium properties of locational sorting models. J Urban Econ 57(3): 462–477CrossRefGoogle Scholar
  3. Bayer P, Timmins C (2007) Estimating equilibrium models of sorting across locations. Econ J 117(518): 353–374CrossRefGoogle Scholar
  4. Berman M (2006) Modeling spatial choice in ocean fisheries. Mar Resour Econ 21(4): 121–125Google Scholar
  5. Berman M, Gregr E, Ishamura G, Sumaila UR, Haley S, Kim H (1997) Estimating net benefits of reallocation: discrete choice models of sport and commercial fishing. Mar Resour Econ 14: 307–327Google Scholar
  6. Berman M, Gregr E, Ishamura G, Sumaila UR (2007) Spatial fisheries values in the north pacific. In: Selected paper. Forum of the North American Association of Fisheries Economists. Merida, MXGoogle Scholar
  7. Berry ST (1994) Estimating discrete-choice models of product differentiation. RAND J Econ 225(2): 242–262CrossRefGoogle Scholar
  8. Berry S, Levinsohn J, Pakes A (1995) Automobile prices in market equilibrium. Econometrica 63(4): 841–890CrossRefGoogle Scholar
  9. Bockstael NE, Opaluch JJ (1983) Discrete modeling of supply response under uncertainty—the case of the fishery. J Environ Econ Manage 10(2): 125–137CrossRefGoogle Scholar
  10. Coleman FC, Koenig CC, Collins LA (1996) Reproductive styles of shallow-water groupers (Pisces: Serranidae) in the eastern Gulf of Mexico and the consequences of fishing spawning aggregations. Environ Biol Fishes 47(2): 129–141CrossRefGoogle Scholar
  11. Costello C, Polasky S (2008) Optimal harvesting of stochastic spatial resources. J Environ Econ Manage 56(1): 1–18CrossRefGoogle Scholar
  12. Curtis R, Hicks RL (2000) The cost of sea turtle preservation: the case of Hawaii’s pelagic longliners. Am J Agric Econ 82(5): 1191–1197CrossRefGoogle Scholar
  13. Dillman DA (2000) Mail and internet surveys: the tailored design method. 2nd ed. Wiley, New YorkGoogle Scholar
  14. Dupont DP (1993) Price uncertainty, expectations formation and fishers’ location choices. Mar Resour Econ 8: 219–247Google Scholar
  15. Eales J, Wilen JE (1986) An examination of fishing location choice in the pink shrimp fishery. Mar Resour Econ 2: 331–351Google Scholar
  16. Eggert H, Tveteras R (2004) Stochastic production and heterogeneous risk preferences: commercial fishers’ gear choices. Am J Agric Econ 86(1): 199–212CrossRefGoogle Scholar
  17. Hannesson R (1998) Marine reserves: what would they accomplish?. Mar Resour Econ 13(3): 159–170Google Scholar
  18. Haynie AC, Layton DF (2010) An expected profit model for monetizing fishing location choices. J Environ Econ Manage 59(2): 165–176CrossRefGoogle Scholar
  19. Hicks RL, Schnier KE (2006) Dynamic random utility modeling: a Monte Carlo analysis. Am J Agric Econ 88(4): 816–835CrossRefGoogle Scholar
  20. Holland DS (2004) Spatial fishery rights and marine zoning: a discussion with reference to management of marine resources in New England. Mar Resour Econ 19(1): 21–40Google Scholar
  21. Holland DS, Sutinen JG (2000) Location choice in New England trawl fisheries: old habits die hard. Land Econ 76(1): 133–150CrossRefGoogle Scholar
  22. Kahui V, Alexander WRJ (2008) A bioeconomic analysis of marine reserves for Paua (Abalone) management at Stewart Island, New Zealand. Environ Resour Econ 40(3): 339–367CrossRefGoogle Scholar
  23. Larson DM, Sutton WR, Terry JM (1999) Toward behavioral modeling of Alaska groundfish fisheries: a discrete choice approach to Bering Sea Aleutian Islands trawl fisheries. Contemp Econ Policy 17(2): 267–277CrossRefGoogle Scholar
  24. McFadden D, Train K (2000) Mixed MNL models for discrete response. J Appl Econom 15(5): 447–470CrossRefGoogle Scholar
  25. Mistiaen JA, Strand IE (2000) Location choice of commercial fishermen with heterogeneous risk preferences. Am J Agric Econ 82(5): 1184–1190CrossRefGoogle Scholar
  26. Murdock J (2006) Handling unobserved site characteristics in random utility models of recreation demand. J Environ Econ Manage 51(1): 1–25CrossRefGoogle Scholar
  27. Smith MD (2002) Two econometric approaches for predicting the spatial behavior of renewable resource harvesters. Land Econ 78(4): 522–538CrossRefGoogle Scholar
  28. Sanchirico JN, Wilen JE (2001) A bioeconomic model of marine reserve creation. J Environ Econ Manage 42(3): 257–276CrossRefGoogle Scholar
  29. Smith MD (2005) State dependence and heterogeneity in fishing location choice. J Environ Econ Manage 50(2): 319–340CrossRefGoogle Scholar
  30. Smith MD, Wilen JE (2003) Economic impacts of marine reserves: the importance of spatial behavior. J Environ Econ Manage 46(2): 183–206CrossRefGoogle Scholar
  31. Smith MD, Wilen JE (2004) Marine reserves with endogenous ports: empirical bioeconomics of the California sea urchin fishery. Mar Resour Econ 19(1): 85–112Google Scholar
  32. Smith MD, Wilen JE (2005) Heterogeneous and correlated risk preferences in commercial fishermen: the perfect storm dilemma. J Risk Uncertain 31(1): 53–71CrossRefGoogle Scholar
  33. Smith MD, Wilen JE, Zhang J, Coleman FC (2006) Effectiveness of marine reserves for large-scale fisheries management. Can J Fish Aquat Sci 63(1): 153–164CrossRefGoogle Scholar
  34. Smith MD, Wilen JE, Zhang J, Coleman FC (2007) Structural modeling of marine reserves with Bayesian estimation. Mar Resour Econ 22(2): 121–136Google Scholar
  35. Strand IE (2004) Spatial variation in risk preferences among Atlantic and Gulf of Mexico longline fishermen. Mar Resour Econ 19: 145–160Google Scholar
  36. Timmins C, Murdock J (2007) A revealed preference approach to the measurement of congestion in travel cost models. J Environ Econ Manage 53(2): 230–249CrossRefGoogle Scholar
  37. Ward JM, Sutinen JG (1994) Vessel entry-exit behavior in the Gulf-of-Mexico Shrimp fishery. Am J Agric Econ 76(4): 916–923CrossRefGoogle Scholar
  38. Weninger Q, Waters JR (2003) Economic benefits of management reform in the northern Gulf of Mexico reef fish fishery. J Environ Econ Manage 46(2): 207–230CrossRefGoogle Scholar
  39. Wilen JE, Smith MD, Lockwood D, Botsford L (2002) Avoiding surprises: incorporating fishermen behavior into management models. Bull Mar Sci 70: 553–575Google Scholar

Copyright information

© The Author(s) 2010

Authors and Affiliations

  1. 1.School of International Relations & Pacific StudiesUniversity of CaliforniaSan DiegoUSA
  2. 2.Nicholas School of the Environment and Department of EconomicsDuke UniversityDurhamUSA

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