annotated bibliography of fisheries economics literature - Office of ...

used for this purpose are data envelopment analysis (DEA) and stochastic
frontier (SF) production functions. Although both methods can be used to
estimate a production frontier, their underlying assumptions and method of
solving for the frontier are quite different. Once substantial difference is
how each model handles noisy data. An understanding of the implications of
this difference is important because random variation is likely to exist in
commercial fishery catch data. This research uses Monte Carlo simulations to
investigate possible finite sample biases attributable to this type of noise.
The results suggest that the mean bias associated with noisy data is often
substantially larger for DEA than SF. However, the frequency distributions of
the biases from each method show a wide variation in some cases.
Lee, T.C., G.G. Judge, and A. Zellner (1968). "Maximum Likelihood and
Bayesian Estimation of Transition Probabilities." American
Statistical Association Journal, December:1162-1179.
In this paper, maximum likelihood and bayesian methods are presented for
estimating transition probabilities when data in the form of aggregated
proportions are available. The probability function for the observed
proportions is assumed to have a multinomial distribution under the Lexis
scheme. The multivariate beta distribution is used as the prior probability
density function in formulating the Bayesian estimator. The results of some
Monte Carlo experiments provide some evidence on the sampling properties of
several alternative estimators.
Lee, T.C., G.G. Judge, and A. Zellner (1970). Estimating the Parameters
of the Markov Probability Model from Aggregate Time Series Data.
North-Holland Publishing Company, Amsterdam.
This book (1) summarizes and evaluates the initial results of markov
chain models as appropriate probability model for time series data when the
observation at any point in time is the state or category into which the unit
being observed falls, (2) develops alternative macro transition probability
estimators and the corresponding computer routines, and (3) evaluates the
finite sample properties of these various estimators by a limited sampling
experiment. Although the results reported apply primarily to aggregate data
generated from a stationary first order Markov process, the extension of the
results to areas concerned with the estimation of transition probabilities
that are not time constant and the general problem of estimation when
proportion data are used are considered in appendices.
Leeworthy, Vernon R. (1990). "An Economic Allocation of Fishery Stocks
Between Recreational and Commercial Fishermen: The Case of King
Mackerel." Ph.D. Dissertation, Department of Economics, Florida
State University.
The economic value and the economic impact were estimated for Florida's
east and west coast recreational and commercial king mackerel fisheries using
1986 data. In 1986, king mackerel fisheries in Florida were economically more
important to both the nation and to the state of Florida's economy than the
commercial king mackerel fisheries in Florida. These conclusions held even
assuming large errors in estimation. Separate reviews are included that
contest the authors conclusions of theoretical and empirical grounds.
Leeworthy, Vernon R. and Peter C. Wiley (1996). Importance and Satisfaction
Ratings By Recreating Visitors to the Florida Keys/Key West. Linking
the Economy and Environment of Florida Keys/Florida Bay, Strategic
Environmental Assessments Division, Office of Ocean Resources
Conservation and Assessment, National Ocean Service, National Oceanic
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