This study develops an improved method for understanding
economic production relationships in small scale
fisheries. This method postulates that gross revenue is a
function of physical input quantities, and is based upon
the transcendental logarithmic function to derive factor
share equations for each of the five inputs in the model.
The translog form was selected because of its flexibility,
non-constant elasticity of substitution, and input interaction
to give a more realistic representation of production
relationships in small scale fisheries. The model
was tested using cross-sectional data from a cost and
earning survey on the Florida reef fishery. The joint
generalized least squares procedure for seemingly uncorrelated
equations was used for the parameters estimation. A
total of 68 observations were used. The estimation
results were not very encouraging because of the poor
response of the model. This may in part be attributable
to inconsistencies shown by the data.
The translog gross revenue function, was also estimated.
The result showed good response. However, the
model was characterized by multicollinearity and sensitivity
of parameters to variable substitution. Similar
results and characteristics were obtained when the Cobb-
Douglas function was estimated. These results were also
influenced by the size and the characteristics of the data
set.
The method presented here for estimating economic
production relationships in small scale fisheries is attractive
because (1) factor share and output elasticities
are a function of the inputs and (2) it allows varying the
inputs in bundles instead of individually, which is more
realistic for policy analysis. Further testing of this
model is encouraged using a larger and more accurate data
set. / Graduation date: 1987
Identifer | oai:union.ndltd.org:ORGSU/oai:ir.library.oregonstate.edu:1957/27276 |
Date | 31 July 1986 |
Creators | Cerda, Rene |
Contributors | Smith, Frederick J. |
Source Sets | Oregon State University |
Language | en_US |
Detected Language | English |
Type | Thesis/Dissertation |
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