Paper Number: 2017-02

Document Date: 7/2017

Author(s):  David M. Massey; Chris Moore; Stephen C. Newbold; Tom Ihde; Howard Townsend

Subject Area(s): Biodiversity, Fisheries, Recreation/Travel Demand, Valuation Methods

JEL Classification:

Q22 - Fishery; Aquaculture
Q26 - Recreational Aspects of Natural Resources
Q51 - Valuation of Environmental Effects
Q57 - Ecological Economics: Ecosystem Services; Biodiversity Conservation; Bioeconomics; Industrial Ecology

Keywords: Chesapeake Bay, water quality, TMDL, hypoxia, commercial fisheries, recreational fisheries, outdoor recreation demand model, inverse demand system, bioeconomic model

Abstract: 

We estimated the economic benefits of the Chesapeake Bay TMDL to commercial fish harvesters and consumers, recreational anglers, and other outdoor recreators. To forecast the impacts of the TMDL on harvested fish and shellfish stocks in the bay and connected Atlantic coast waters, we used a summary of judgments from an expert panel and a multi-species model of Chesapeake Bay fisheries. We estimated benefits to consumers in commercial fish markets using a multi-stage inverse demand system, which models price as a function of exogenous supply and accounts for substitution possibilities between 13 different species and as many as five regions. Models were estimated using monthly harvest data from the years 1991 to 2011. The estimated parameters of the inverse demand systems were then used to calculate compensating and equivalent variation from the changes in harvests between the baseline and TMDL scenarios. To estimate producer surplus changes, we assumed that fishing effort will remain fixed at recent levels in each fishery, so harvesting costs do not increase due to the TMDL. The resulting estimates of commercial fishing benefits range between $3 and $26 million per year. We also examined the implications of alternative assumptions about the management regime in each fishery, including fixed effort, open access, and maximum sustainable surplus.

We calculated benefits to recreational anglers using a linked participation and site-choice recreation demand model. The model was estimated using angler intercept survey data from the Marine Recreational Fisheries Statistics Survey (MRFSS). Catch rates were calculated using historic reported catch from the MRFSS. We accounted for the sample selection bias caused by the non-random intercept survey sampling design using weights based on historic visitation frequencies at each intercept site. The intercept data were used to estimate a random utility site-choice model, and counts of trips from respondent zip codes were used to estimate a negative binomial participation model conditional on the inclusive value of all sites as estimated by the site-choice model. The resulting estimates of recreational fishing benefits range between $5 and $59 million per year.

We used a separate recreation demand model to estimate the benefits associated with other outdoor recreation activities. The model was estimated using aggregate data on the total number of visitors to national and state parks in Maryland, Virginia, and Delaware. The aggregate visitation data alone are insufficient to estimate all parameters of the model, so these data were supplemented with survey data on the number of recreation trips taken to the Chesapeake Bay collected from a random sample of individuals in the study area. The marginal effects of water quality on recreators’ site choices were estimated in a second-stage regression, using estimates of site-specific constants from the first-stage site-choice model as the dependent variable and measures of average water quality conditions and other fixed site attributes as explanatory variables. The central estimates of the outdoor recreation benefits (exclusive of recreational fishing) are between $105 to $280 million per year.

This paper is part of the Environmental Economics Working Paper Series.

• Commercial Fishing and Outdoor Recreation Benefits of Water Quality Improvements in the Chesapeake Bay (PDF)(179 pp, 4 MB, 07/31/2017)