• The Journal of Fisheries Business Administration
• /
• v.45 no.1
• /
• pp.63-77
• /
• 2014

This study is to estimate the recent changes in total factor productivity of 15 Korean adjacent water fisheries based on Malmquist productivity indices. The study adopted both input and output oriented productivity measures utilizing a hyperbola distance function. In addition to this point, the study also calculated the 95% confidence interval for the various components of the productivities in order to access the statistical significance of estimates using 2000 times of re-sampling process through the smoothed bootstraping. The results of the study showed us that there was 18% reduction in the overall total factor productivity during the study period from 2007 to 2011, which turned out to be 5% of annual decrease in productivity. The study found that the main reason of this decrease in total productivity is about 22% downward shift of a fisheries production function due to recent conditions of a devastated fishing ground. When we evaluated the statistical significance of changes in technical efficiency combining both pure technical and scale efficiency based on the 95% confidence intervals, we could not find any evidence of changes in those components of total factor productivity. When we accessed the productivity of the each of 15 adjacent water fisheries methods, only the large danish seine fisheries showed us about 7% increase in productivity. Even though the large trawling and the large tow-boat trawling revealed no changes in productivity, all of the other 12 fisheries suffered the decreases in productivities.

• The Journal of Fisheries Business Administration
• /
• v.23 no.2
• /
• pp.91-99
• /
• 1992

It has been one of the critical issues that the researchers properly evaluate the fishing rights foregone by the coastal development activities like wetland reclamation. Particularly, estimating the productivity of concerned fishing rights is known to play a significant role in their monetary compensation. As a result, this paper attempts to develop a statistical model characterized by Cobb-Douglas production function in conjunction with the fisheries' productivity estimation. The primary hypotheses involving their statistical production function are as below : 1. The quantity of fisheries production is hypothesized to be expressed as a function of capital (K) and labor(L) put into fishing activities. 2. The estimated parameters of K and L are hypothesized to satisfy the conventional condition of production function as a form of Cobb-Douglas. These statistical tests reveal that the shellfish farming productivity heavily depends on the acre of mariculture while the input of labor force also considerably affects its productivity. In case of the fixed net fishing productivity, both the factors of capital and labor similarly affect the marginal change in its productivity. En addition, the productivity of shellfish (arming turns out to follow the increasing returns to scale, whereas that of fixed net fishing comes up with the decreasing returns to scale.

• The Journal of Fisheries Business Administration
• /
• v.43 no.2
• /
• pp.95-106
• /
• 2012

This study analyzed the changes in productivity growth of 291 regional fisheries cooperatives area from 2001 to 2010 selected as target. The productivity growth analysis of operating offices calculates Global-Malmquist productivity index. Input variables are number of the persons and the nettable area, output variables are deposit, loans and earnings. To improve the homogeneity of industry, the operating conditions were considered. Global Malmquist index of Operating offices was reduced between 2001~2010. The cause of increase and decrease of productivity are divided by efficiency change(EC) and best-practice change(BPC). Operating offices with increased productivity existed between 2001~2002 and between 2002~2003 and between 2006~2007. There were operating offices with increased productivity by EC. Global Malmquist index of Operating offices with locations was highest relatively in metropolitan. Operating offices with increased productivity existed between 2003~2004 and between 2007~2008 and between 2008~2009 in all locations. There were operating offices with decreased productivity by BPC.

• The Journal of Fisheries Business Administration
• /
• v.50 no.2
• /
• pp.41-56
• /
• 2019

The aim of this study is to analyze the productivity change of pollock enterprise by applying a mutually quadratic hyperbolic model and a bootstrapping model. This study used 20 units of pollock firms data (from 2013 to 2017). As a result of total productivity analysis of twenty pollock enterprises, total factor productivity was estimated to have decreased by 24.9% over the last five years (2013~2017). The main cause of this productivity decline was analyzed by technical change. In terms of annual productivity change, it showed decrease 3.0% in 2013~2014, 7.8% in 2014~2015, 4.5% in 2015~2016 and 4.7% in 2016~2017 respectively. In the analysis of productivity by corporation type, total factor productivity showed a significant decrease in both general corporation and external corporation, and productivity decrease (-29.3%) was larger than general corporation (-23.0%). In the productivity analysis by type of business, total factor productivity decreased significantly in the order of wholesale and commodity brokerage (-26.3%), food manufacturing (-25.1%) and fisheries (-15.3%). This decrease in productivity was caused by the technological change which indicates a downward shift in the production curve that is significant in all sectors.

• The Journal of Fisheries Business Administration
• /
• v.51 no.1
• /
• pp.19-36
• /
• 2020

The purpose of this paper is to analyze the productivity of the costal fisheries in Jeonnam Province. In this study, the operational characteristics and Cobb-Douglas production function of coastal fisheries were examined based on a research on the actual condition of costal fisheries (RACF). The statistical analysis of RACF data reveals that Cobb-Douglas production function consists of the three variables: fishing quantity per ton-age, the number of fisherman per ton-age and fishing equipment cost per ton-age. The results of this study show us that the relation and productivity between labor and capital of the operational equipment in the coastal fisheries. If extensive comparable biological and market data become available, analysis model can be widely applied to yield more accurate results.

• Korean Journal of Fisheries and Aquatic Sciences
• /
• v.43 no.5
• /
• pp.547-550
• /
• 2010

Jinhae Bay is a typical aquaculture farm with active fisheries. However, it has been contaminated by the development of a major city and industrial area, and has therefore diminished in value as a fishing ground. To preserve the continuing productivity of the ocean, we have to estimate fisheries resources. To analyze the fisheries resources in Jinhae Bay, we evaluated the Fisheries Productivity Index (FPI). The FPI is composed of the Total production ($T_p$), Total amount ($T_a$), and Production of edible protein ($E_p$), nitrogen ($N_p$) and phosphorous ($P_p$). To calculate the FPI, we used Annual statistics on cooperative sales of fishery products data from 1979 to 2004 and the Food composition table. The results of the FPI were as follows. $T_p$ ranged from 70,235 tons to 113,556 tons and $T_a$ ranged from 107,004 million won to 373,776 million won. $E_p$ ranged from 8,124 tons to 13,357 tons, $N_p$ ranged from 1,965 tons to 3,273 tons, and $P_p$ ranged from 168 tons to 276 tons. According to the FPI, maximum fisheries productivity occurred in 1994, when $T_a$, $E_p$, $N_p$ and $P_p$ were at their highest values.

• The Journal of Fisheries Business Administration
• /
• v.36 no.1 s.67
• /
• pp.1-26
• /
• 2005

This study attempts to suggest the requisites for selecting the neighboring fisheries of the same kind related to the calculation of aquaculture fisheries loss stipulated in the article 62 of enforcement ordinance of fisheries law. First of all, the requisites for the same kind of aquaculture fisheries are legally evident. The more important requisites are the factors for the neighboring fisheries of aquaculture fisheries. Here the factors we must consider are the same oceanic environment, the same fisheries management, and the same productivity of fisherman. In conclusion, the best way of selecting neighboring fisheries is picking up the adjacent fishery to the fishery because the factor of the same oceanic environment is the most important in determining the productivity of fisheries.

• Ocean and Polar Research
• /
• v.39 no.4
• /
• pp.301-318
• /
• 2017

The production of Korean offshore fisheries has been gradually decreasing due to the severe depletion of offshore fisheries resources caused by excessive fishing efforts. The production of the offshore fisheries in 2016 was the lowest since 1975. So the federal and local governments in Korea adopted and implemented various fisheries management plans and policies in order to restore fisheries resources. However, these plans and polices have not been successful in re-establishing fisheries resources. Thus, in order to accurately diagnose the situation with regard to offshore fisheries, this study sought to estimate not only the return to scale by fishing gear of offshore fisheries, but marginal productivity of individual fishing gear based on production factors derived from offshore fisheries production functions. The study was organized in the following manner. First of all, this study estimates production functions of offshore fisheries. The Cobb-Douglas and the translog production functions are adopted as offshore fisheries production functions. Specifically, the functions are estimated by crew, vessels, and offshore resource as production factors. The offshore resource is estimated by the Clarke Yoshimoto Pooley model based on the surplus production model. Secondly, the fisheries production functions are extended to the fixed-effect model and the random-effect model with panel data. Thirdly, this study analyzes the return to scale of offshore fisheries and the marginal productivity of the production factors from the estimated offshore fisheries production function. In conclusion, this study suggests plans and countermeasures for productivity improvement by group (labor intensive or technology intensive) based on the characteristics of individual offshore fishing gear.

• The Journal of Fisheries Business Administration
• /
• v.53 no.1
• /
• pp.1-16
• /
• 2022

This paper aims to propose a new systematic approach to analyze the factor productivity and to investigate those characteristics of factor productivity in operational and managerial perspectives. The Cobb-Douglas production function is adopted to estimate the labor and capital productivity. In estimating those productivities the data of The Research on the Actual Condition of Coastal Fisheries (RACF), especially those of Jeon-Nam Province are used. The statistical analysis of RACF data shows that the characteristics are a little bit different between labor and capital of the operational equipment in the coastal fisheries. The Cobb-Douglas type production function is useful in estimating the factor productivity, especially in case of 'coastal Stow-net fishery' even though the limited data is used. However, in case of 'trap fishery,' the Cobb-Douglas production function appears to have some limitations in estimation. This implies that estimating the factor productivities in fisheries employing broad perspectives and various methods are needed.

• Journal of Fisheries and Marine Sciences Education
• /
• v.28 no.1
• /
• pp.186-197
• /
• 2016

This study applied the parametric bootstrapping method to analyze whether there was a change in the production efficiency of institutions under Ministry of Oceans and Fisheries. This study used input and output oriented productivity simultaneously. In particular, the productivity was estimated through 95% confidence interval derived by 2000 times re-sampling process. The results of the study showed us a reduction in overall total factor productivity by 24% between 2009 and 2013, and 7% of decreases in productivity annually. A recent conditions of an external economic shocks brought a 28% downward shift of production function. In this study, public institutions were divided into three types, which were public, quasi-government, and other public institutions. There were approximately 13%, 1%, and 5% decreases in total factor productivity per each. In analyzing the productivity each of 14 institutions, approximately DMU4 and DMU6 had 4%, and 5% increases in productivity per each. While DMU14 showed us no changes in productivity, all of the other 10 DMUs were estimated the decreases in productivities.