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Steve NewboldU.S. Environmental Protection Agency

National Center for Environmental EconomicsOctober 2011

National Center for Environmental Economics

CHESAPEAKE BAYCOMMERCIAL FISHING

BENEFITS ANALYSIS

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OUTLINE

1. Key economic concepts for fishery benefits estimation– Consumer and producer surplus, common pool

resources, rent dissipation2. Major Chesapeake Bay fisheries 3. Proposed modeling approach– Bioeconomic framework: EwE/Atlantis + harvester

response functions for each stock– Deacon et al. (2011), illustrative example

4. Data needs and modeling challenges

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KEY CONCEPTS• Producers of commercially harvested fish will benefit

from the TMDL to the degree that the fish stocks they target become more abundant and therefore easier to catch.

• Consumers of commercially harvested fish will benefit from the TMDL to the degree that the lower harvesting costs are passed on in the form of lower prices of fish at the market.

• To estimate benefits in the commercial fishing sector, we need data on prices and quantities of harvested fish with and without the TMDL.

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KEY CONCEPTS• Economic benefits = WTP = consumer +

producer surplus change

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KEY CONCEPTS• Fish stocks are common pool resources• “Tragedy of the commons”: with no restrictions on

harvesting the stock will be over-exploited and all rents dissipated (Gordon 1954, Scott 1955)

• Large literature on fishery economics that examine alternative management approaches (Wilen 1999)

• Fisheries managed by catch shares less likely to collapse (Costello et al. 2008)

• Slope of supply curve, and therefore benefits of water quality improvements, will depend on the nature of the management regime (Freeman 1991)

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MAJOR FISHERIES IN CHES. BAY

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CHESAPEAKE BAY

Avg. landings and revenues 200-2009

"Fisheries Ecosystem Planning for Chesapeake

Bay," 2006

MT $/MT Revenue Cum. %% of Atl.

rev.Relative

abundanceRelative

exploitationBlue crab 24128 2085 50542512 49 54 low overAtlantic menhaden 178591 139 24824149 74 85 medium fullStriped bass 1965 3849 7563285 81 56 high limitedAtlantic croaker 5425 875 4746875 86 55 high mediumEastern oyster 367 11665 4281055 90 22 low overSummer flounder 1324 3077 4073948 94 17 medium overBlue crab (peelers) 650.7 4887.55 3387422 97 57 low overBlack sea bass 299 5737 1715363 99 25 low overWeakfish 290 1808 524320 99 26 high lowHorseshoe crab 238 967 230146 99 27 not est. unknownBluefish 293 639 187227 100 7 low overSpanish mackerel 51 2029 103479 100 4 moderate fullBlue crab (soft) 12 7980 100983 100 3 low overBlack drum 32 2368 75776 100 56 not est. unknownAmerican shad 39 1467 57213 100 7 low lowSpotted sea trout 13 3155 41015 100 9 not est. unknownTautog 7.1 3182 22592 100 4 low overRed drum 2.5 2747 6868 100 3 not est. over

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PREVIOUS STUDIES - GENERAL• Clark (1990)—“Bible” of bioeconomic modeling• Homans and Wilen (1997)—estimated a model of a

regulated open access fishery• Lipton and Hicks (2003)—DO and striped bass

recreational fishery in the Chesapeake Bay• Massey et al. (2006)—water quality and summer

flounder recreational fishery in MD coastal bays• Finnoff and Tschirhart (2008)—general equilibrium

bioeconomic model of an 8-species ecosystem• Smith and Crowder (2011)—transitional rents from N

reductions in open access blue crab fishery • Deacon et al. (2011)—calibrated model of capacity

constrained fisheryNational Center for Environmental Economics

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PREVIOUS STUDIES – CHES. BAY• Kahn and Kemp (1985)—fishery support by SAV in

Chesapeake Bay• Anderson (1989)—seagrass and blue crabs in VA• Lipton and Hicks – DO and recreational catch of

striped bass in the Chesapeake Bay• Mistiaen et al. (2003)—low DO and blue crabs in

tributaries of Chesapeake Bay• Sanchirico et al. (2006)—ecosystem management of

Chesapeake Bay fisheries• Kar and Chakraborty (2009)—bioeconomic model of

Chesapeake Bay oyster fishery

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OUR TASK

• We want to develop a general but relatively simple framework that can be applied to multiple species parameterized using readily available fishery statistics and results from previous studies

• Must represent management constraints and the incentive structure these constraints provide to the harvesters

• Integrate harvester and manager response functions with biological production functions to form a multi-species bioeconomic model

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PROPOSED APPROACH

Estimate (as in Homans and Wilen 1997) or calibrate (as in Deacon et al. (2011) a fishing effort production function for each stock for integration with EwE and/or Atlantis:

• Fishing mortality rate:

• Harvest:

• Profits (rents):

• Biological dynamics: ( EwE / Atlantis )National Center for

Environmental Economics

P = - -pH wLT rK

( )é ù= + -ê úë û1

1bb bF q aL a K

( )- +é ù= -ê úë û+ 1 F M TFH A eF M

( )+ = -1 ,tt tA g A H Q

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PROPOSED APPROACH

Can represent a range of management regimes:

• Open access: K increases until profits = 0

• Regulated open access (e.g., TAC): regulator closes season ( limits T ) to ensure , but with no limit on entry K still increases until profits = 0.

• Capacity constrained: K restricted to ensure s . Other inputs may expand but unless they are perfect substitutes for K then profits > 0

• Optimal management: K and L chosen to maximize profits

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£ ˆH H

£ ˆH H

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DEMAND MODEL

• Multistage Demand Model– Allocates household income to expenditure categories– Captures substitution between different commodities and

harvests from different estuaries• Changes in consumer welfare– Demand is a function of

• Income (total expenditures)• Prices of Chesapeake harvest• Prices for harvest from other regions • Price indices for other commodities

– Expenditure function is used with projections of income and prices to estimate changes in consumer surplus

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ILLUSTRATIVE EXAMPLEConsider the mythological fish “Atlantic henmaden” (similar to Atlantic menhaden, but not quite the same)• 2 life stages, B-H stock-recruitment function• Take α and M from pervious fisheries biology studies• Set H, F, p to match recent levels for Atl. menhaden• Calibrate β assuming steady-state conditions• Assume w =$40K /yr, K = 20, L = 1000, assume open access to calibrate r, guess

b = -2, and calibrate a assuming cost minimization, price elasticity = -0.3

• Suppose TMDL will increase α and β by 10%, decrease M by 5% (increase eq. A by 27%)

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¶¶

p HH p

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ILLUSTRATIVE EXAMPLEBenefits depend on the management regime:

≈ $25-75 million / yrNational Center for Environmental Economics

OpenAccess

Optimal management

Regulated open access

Capacity constrained

Base TMDL Base TMDL Base TMDL Base TMDL

A [109 fish] 2.78 2.99 4.21 4.94 4.32 5.06 3.80 4.29

K [vessels] 28 36 11 13 24 35 14 18

L [laborers] 1196 1466 536 654 1568 2373 783 1017

F [yr-1] 0.74 0.94 0.30 0.36 0.70 1.02 0.39 0.51

T [yr/yr] 1 1 1 1 0.39 0.33 1 1

H [10- fish] 11.9 15.1 8.7 12.2 9.4 13.5 10.0 14.0

[107 $/yr] 0 0 7.9 12.8 0 0 7.3 11.7

PS [107 $/yr] 0 4.94 0 4.33

CS [107 $/yr] 2.4 2.7 3.2 3.1

P

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THE MOST IMPORTANT SLIDE

1. Data on H and p from NOAA’s comm. fishery stats2. K and L (& w?) from vessel observer programs ( ? )3. w from BLS (by state, possibly county, probably not by stock)4. How to obtain data on r? (calibrate if open access)5. How to estimate, calibrate, or transfer b?6. How to characterize existing and future management

regimes in each fishery?7. How to handle spillover effects due to fish migrations?

(Massey et al. 2006)

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Data needs & modeling challenges