Community-based Sectors for the New England Groundfish Fishery

Appendix B: Groundfish Price Model
Projection of revenues for groundfish sectors and permit banks requires a projection of the
TACs the sector will be allocated, an estimate of the percentage of those TACs the sector will
actually land, and an estimate of the prices sector members will receive. While sectors may
be able to realize premium prices for the fish they land by improving quality or contracting
directly with retailers or restaurants, it is difficult to project how large this premium might be.
At the same time there are other factors that are likely to affect prices, particularly changes in
overall landings of various species that result from changes in target TACs. Since some of
these species are rebuilding and TACs are expected to rise, this may create downward
pressure on prices. Secular upward trends in prices over time can also be expected and are
likely to correlate with increases in disposable income of consumers. This is likely to result in
increases in real prices independent of change in quantity landed and even greater increases
in nominal prices before adjustment for inflation. Since a primary use of these price
projections is to estimate the repayment period required for a permit bank to pay back a loan
to acquire a permit, nominal rather than real prices are modeled.
Prices are projected based on demand models for the regulated groundfish species and
monkfish estimated with landings and revenue data from the Northeast Fishery Science
Center’s commercial fisheries data for the years 1983 to 2005. Since the intent is to predict
nominal prices, nominal prices are used to estimate demand models. Per capita disposable
income (PCDI) for the New England region is used as an explanatory variable to capture
secular temporal trends in prices. For future price predictions this requires predicting PCDI
which is done on the using a simple OLS model of PCDI growth over time.
The specifications used for the individual equations were linear-log (i.e. price per kilogram is
regressed against the natural logs of the regressors). This allows for a non-linear demand
curve without imposing constant elasticity. With the exception of ocean pout, the natural log
of PCDI was used in place of an intercept. The demand equations are estimate using a
seemingly unrelated regression that includes price equations for monkfish, cod, haddock,
winter flounder, witch flounder, yellowtail flounder, plaice, sand dab, white hake, pollock,
ocean pout and redfish. In addition to own quantity landed, the models use combined
roundfish or combined flatfish landings as explanatory variables in some equations. Import
quantities and prices were not used in these models. An investigation of price relationships
with imports suggested that import quantities are driven by domestic prices and landings but
the reverse is not true.
Despite parsimonious specifications with only two or three regressors, the price equations are
highly significant. All regressors in all equations are significant at the 0.01 level with the
exception of own quantity for witch flounder which had a p-value of 0.07. First order
autocorrelation was present and corrected for in both systems of equations. The estimated
equations used to predict prices in the simulations and summary statistics for them are given
in the equations below