• The Journal of Fisheries Business Administration
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• v.36 no.1 s.67
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• pp.81-101
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• 2005

This article is to estimate the fishing frequency function in Korean recreational fishery with respect to socio-economic characteristics of anglers. First, the study described the characteristics of the entire angler population on the view points of 9 socio-economic variables. And then, the study divided the total angler population into three groups of in-land, sea, and mixed angler populations in order to investigate the differences in their characteristics. The study could confirm the existence of differences in regions, size of regions, and educational levels between the in - land and the sea angler populations by testing heterogeneity in the frequency table. The fishing frequency function is estimated using Poisson regression model in order to accomodate the count data(non-negative discrete random variable) aspects of the fishing frequency. However, the model specification error is found due to overdispersion of data. The model exhibits the lack of goodness of fit. The negative binomial regression model is adopted to cure the overdispersion of the data as an alternative estimation methodology. Finally, the study can confirm overdispersion does not exist in the model any more and the goodness of fit improved significantly to the reasonable level. The results of estimation of fishing frequency population modeled by the negative binomial regression models are following. The three variables of region, sex, and education have effects on the decision making process of fishing frequency in the case of in-land recreation fishery. On the other hand, the three variables of sex, age, and marriage status do the same job in the case of sea angler population. Among the left-over variables, both income and use of Internet variables now affect on the process in mixed angler population. Finally, the results of whole angler population show that all of the previous variables are proven to be statistically significant due to the summation of data with all three sub-groups of angler population.

• The Journal of Fisheries Business Administration
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• v.41 no.2
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• pp.45-60
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• 2010

The objective of this article was to estimate the market size of recreational fishing in Korea. Data were collected through sample surveys of 3,081 households nationwide in 2008. The number of anglers was directly estimated by applying weights expressed as the ratio of population to the sample. Yields and expenditures were estimated based on modules developed. On the basis of the results, a total of 6,524 thousand anglers caught an estimated 643,343 thousand fish, divided 65.2% on inland lake and 34.8% on saltwater. An angler caught about 98 fish on average in 2008. A typical angler went fishing 9.6 times, divided 8.4 times on inland lake and 5.5 times on sea. An annual expenditure of 5,233.6 billion won was estimated. The total was divided 2,851.4 billion won on inland lake(54.5%) and 2,382.2billion won on saltwater(45.5%). An average angler spent 802 thousand won a year. This study also estimated volumes by various types of fish.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.58 no.1
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• pp.75-84
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• 2022

Since South Korea did not adopt the recreation fishing using right (coupon) system, there were no recreation fishing statistics. This study selected 480 fishing vessels (10.4%) of a total of 4,611 fishing vessels (as of December 2019) as a survey sample using stratified sampling. Unlike other research institutes that conducted surveys related to the amount of tide on a one-time, this survey was conducted for five months (from May to October 2020, except the month of August). The captain investigated about types of fish, size, weight, etc. to anglers. A difference from previous studies was that about 7.0 million angler population (fishing more than three times a week) had 19.4 kg of catch per person for a year while other studies showed about 25.5-52.0 kg, respectively. The total fisheries resource catch amount was analyzed to be about 95,000 tons in this study and 116,000-166,000 tons in other studies. So there was a difference of about 1.2 to 1.8 times. This study aims to lay the foundation for the development of the fishing industry by preparing accurate statistical data and securing reliable basic statistics related to the fishing industry. Also, it could be usefully used as basic policy data such as introduction of a fishing using right (coupon) system.