• Journal of Soil and Groundwater Environment
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• v.9 no.2
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• pp.54-63
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• 2004

For the purpose of finding out the distributions of groundwater uses, the effect of facilities on the parameter and the correlations among measurements, various statistical analysis were carried out with the data of groundwater quality measurements from January to December in 2002. (1) The rates of groundwater for drinking water were 10.5% in Yungcheon-Gu, 10.2% in Kangdong-Gu, and 9.9% in Eunpyung-Gu. The rates of other uses of groundwater were shown to be 58.1 %(786 wells) for civil defense emergency, 22.1% (299 wells) for contamination-concerning, 9.8%(133 wells) for water quality monitoring, consisting of 90% of all groundwater. (2) The 52.6% of groundwater for drinking were demonstrated to be appropriate while 91.9% for other uses-domestic, industrial, agricultural uses- were shown to be proper. (3) For drinking water, the maximum values of colar, turbidity, NH3-N, F, and Fe were 766.9 degree, 69.16NTU, 860.0 mg/l, 5.6 mg/l and 49.87 mg/l respectively. (4) Comparision of skewness and kurtosis for Seoul groundwater, pH was found to be 0.022 and -0.524, but the T.colony, color, turbidity, NH$_3$-N, NO$_3$-N, Fe and Mn respectively fumed out to be 11.641 and 174.324, 8.501 and 80.260, 5.675 and 32.821, 19.507 and 380.994, 3.323 and 17.436, 10.544 and 134.093 and 5.979 and 39.124. (5) In cases of drinking water wells for emergency, the results of statistical analysis showed that building year of the wells, depth and pumping rate didn't affect on whether it was proper for that use or not. It were shown that there were linear correlations between depth and NO3-N(-0.171) and F(0.332) while the correlation coefficients were 0.381 and -0.169 between the building year of well and depth and pumping rate respectively.

• The Journal of Fisheries Business Administration
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• v.40 no.2
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• pp.49-70
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• 2009

This study proviedes GARCH model(Bollerslev, 1986) to analyze the structural characteristics of price volatility in domestic aquacultural fish market of Korea. As a case study, flatfish and rock-fish are analyzed as major species with relatively high portion in an aspect of production volume among fish captured in Korea. For analyzing, this study uses daily market data (dating from Jan 1 2000 to June 30, 2008) published by the Noryangjin Fisheries Wholesale Market which is located in Seoul of Korea. This study performs normality test on trading volume and price volatility of flatfish and rock-fish as an advanced empirical approach. The normality test adopted is Jarque-Bera test statistic. As a result, first, a null hypothesis that "an empirical distribution follows normal distribution" was rejected in both fishes. The distribution of daily market data of them were not only biased toward positive(+) direction in terms of kurtosis and skewness, but also characterized by leptokurtic distribution with long right tail. Secondly, serial correlations were found in data on market trading volume and price volatility of two species during very long period. Thirdly, the results of unit root test and ARCH-LM test showed that all data of time series were very stationary and demonstrated effects of ARCH. These statistical characteristics can be explained as a reasonable ground for supporting the fitness of GARCH model in order to estimate conditional variances that reveal price volatility in empirical analysis. From empirical data analysis above, this study drew the following conclusions. First of all, from an empirical analysis on potential effects of seasonality and the day of week on price volatility of aquacultural fish, Monday effects were found in both species and Thursday and Friday effects were also found in flatfish. This indicates that Monday is effective in expanding price volatility of aquacultural fish market and also Monday has higher effects upon the price volatility of fish than other days of week have since it has more new information for weekend. Secondly, the empirical analysis led to a common conclusion that there was very high price volatility of flatfish and rock-fish. This points out that the persistency parameter($\lambda$), an index of possibility for current volatility to sustain similarly in the future, was higher than 0.8-equivalently nearly to 1-in both flatfish and rock-fish, which presents volatility clustering. Also, this study estimated and compared and model that hypothesized normal distributions in order to determine fitness of respective models. As a result, the fitness of GARCH(1, 1)-t model was better than model where the distribution of error term was hypothesized through-distribution due to characteristics of fat-tailed distribution, was also better than model, as described in the results of basic statistic analysis. In conclusion, this study has an important mean in that it was introduced firstly in Korea to investigate in price volatility of Korean aquacultural fishery products, although there was partially a limited of official statistic data. Therefore, it is expected that the results of this study will be useful as a reference material for making and assessing governmental policies. Also, it is looked forward that the results will be helpful to build a fishery business plan as and aspect of producer, and also to take timely measures to potential price fluctuations of fishery products in market. Hence, it is advisable that further studies related to such price volatility in fishery market will extend and evolve into a wider variety of articles and issues in near future.