日本、南韓、台灣有著相似的經濟發展背景，同樣也經歷了二次大戰的破壞與重建，且亦都位於東亞地理位置的要衝。雖然過去三國之間彼此在經濟成長、國際貿易與技術進步的競爭關係，以為先前文獻討論。然而，這些競爭關係亦可能存在於海洋漁業中。由於中、西太平洋 (Western and the Central Pacific Ocean, WCPO) 是世界最有價值的漁場之一，於是我們便使用中西太平洋漁業委員會(Western and Central Pacific Fisheries Commission, WCPFC)的鮪魚捕獲資料，利用時間序列分析中共整合檢定與誤差修正模型，分析三個國家彼此的漁業競爭關係。本文發現日本漁獲量增加使得台灣捕獲量增加，反之亦然；南韓與台灣或日本捕獲量卻是相反的影響。此結果代表三國捕獲量互相衝擊影響。本文亦企圖找出漁業衝擊的原因和長期以及短期的競爭關係。

Japan, South Korea, and Taiwan have similar economic backgrounds, as they have undergone the aftermath of destruction and restructuring from the World Wars, and they are all situated in important locations in the East Asia region. Since there have been abundant research studies about competition in economic growth, international trade, and technology advances, however, there competition might also be competition between these countries in the fishery industry. Resulted of Western and the Central Pacific Ocean (WCPO) has been one of the most valuable fishery areas in the world, we use the tuna capture data from the Western and Central Pacific Fisheries Commission (WCPFC) and utilize a cointegration test and error correction model in a time series analysis to analyze the competitive relationship in the three countries. In our study, we found that if the Japanese captures increase, the Taiwanese captures also increase and the same cases occur in the contrasting cases. But the relationships with South Korea and Japan or with South Korea and Taiwan are negative. It represents that the capture in the three countries impact each other. We also try to find the reasons for impact and long-run and short-run competitive relationships.

目 錄
致謝.............................................................................................................i
中文摘要....................................................................................................ii
英文摘要...................................................................................................iii
1. Introduction............................................................................................1
2. Literature review.....................................................................................5
3. Empirical findings................................................................................11
3.1 Data description...........................................................................11
3.2 Unit root tests..............................................................................11
3.3 Test for Johansen’s multivariate cointegration procedure..........16
3.4 General impulse response function.............................................22
4. Conclusion............................................................................................24

參考文獻..................................................................................................35

Akaike, H.,1974. A new look at the statistical model identification. IEEE Transactions on Automatic Control 19, 716–723.
Akaike, H.,1969. Fitting autoregressions for prediction. Annals of the Institute of Statistical Mathematics 21, 243–247.
Arango, L.E. and Luis F.M., 2006. Expansions and contractions in Brazil, Colombia and Mexico: a view through non-linear models. Journal of Development Economics 80, 501-517.
Altekruse, S.F., Street, D.A., Fein, S.B., Levy, A.S., 1995. Consumer knowledge of food-borne microbial hazards and food handling practices. Journal of FoodProtection 59, 287–294.
Bergin, A., Haward, M., 1992. Japanese tuna fisheries. Marine Policy, 147-166
Bell, J.D., Kronen, M., Vunisea, A., Nash, W.J., Keeble, G., Demmke A., Pontifex, S., Andréfouët, S., 2009. Marine Policy 33, 64-76
Chang, S.K., Liu, K.Y., Song, Y.H., 2010. Distant water fisheries development and vessel monitoring system implementation in Taiwan-History and driving forces. Marine Policy 34, 541-548.
Connor, W.E., 2000. Importance of n 3 fatty acids in health and disease. American
Journal of Clinical Nutrition 71, 171–175.
Dickey, D.A., Fuller, W.A., 1979. Distribution of the estimation for an autoregressive time series with a unit root. Journal of the American Statistical Association 74, 427-431.
Emmers, R., 2010. Japan- Korea relations and the Tokdo/Takeshima dispute: The interplay of Nationalism and Nature Resoruces. S. Rajaratnm school of international studies in Singapore. No. 212.
Elliott, G., Rothenberg, T.J., Stock, J.H., 1996, Efficiency tests for an autoregressive unit root. Economics 64, 813-836.
Engle, R., Granger, C., 1987. Co-integration and error correction representation: estimation and testing. Econometrica 55, 251–267.
Granger, C. W. J.,1986. Developments in the study of cointegrated economic variables. Oxford Bulletin of Economics and Statistics 48, 213-228
Ghali, K.H., El-Sakka, M.I.T., 2004. Energy use and output growth in Canada: a multivariate cointegration analysis. Energy Economics 26, 225–238.
Hannan, E.J., Quinn, B.G., 1979. The determination of the order of an autoregression. Journal of the Royal Statistical Society, Series B 41, 190–195.
Havice, E., 2010. The structure of tuna access agreements in the Western and Central Pacific Ocean: Lessons for Vessel Day Scheme Planning. Marine Policy 34, 979-987.
Hong, S.J., 1995. Marine policy in the Republic of Korea. Marine Policy 19, 97-113.
Haward, M., Bergin, A., 2001. The political economy of Japanese distant water tuna fisheries. Marine Policy 25, 91-101.
Haward, M., Bergin, A., 2000. Taiwan’s distant water tuna fisheries. Marine Policy 24, 33-43.
Johansen, S., 1994. The role of the constant and linear terms in cointegration analysis of nonstationary variables. Econometric Reviews 13, 205–229.
Johansen, S., Juselius, L., 1990, Maximum likelihood estimation and inference on cointegration—with applica-tions to the demand for money. Oxford Bulletin of Economics and Statistics 52, 169–210.
Johansen, S.,1988. Statistical analysis of cointegration vectors. Journal of Economic Dynamics and Contral 12, 231-254.
Koop, G., Pesaran, M.H., Potter, S., 1996. Impulse response analysis in nonlinear multivariate models. Journal of Econometrics 74, 119–147.
Koo, M.G., 2005. Liberal Peace and the Scramble for the Rocks: The Dokdo/Takeshima, Senkeku/Diaoyu, and Paracel and Spratly Islands Disputes. 2005 Annual Meeting of the American Political Science Association, Washington, D.C..
Kwak, S.J., Yoo, S.H., Chang, J.I., 2005. The role of the maritime industry in the Korean national economy: an input-output analysis. Marine Policy 29, 371-383.
Kim, S., 2010. Fisheries development in northeastern Asia in conjunction with changes in climate and social systems. Marine Policy 34, 803-809.
Kinsey, S.T., Penke, B., Locke, B. L., Moerland, T. S., 1999. Diffusional anisotropy is induced by subcellular barriers in skeletal muscle. NMR Biomed. 11, 1-7.
Ljung, G.M., Box, G.E.P., 1978. On a measure of lack of fit in time series models. Biometrika 65, 297–303.
Lutkepohl, H., 1991. Introduction to Multiple Time Series Analysis. New York: pringer-Verlag.
Mentjes, T., Panten, K., 2000. Relative size and girth selectivity of cod gillnets in the Western Baltic. International Council for The Exploration of the Sea, ICES CM 2000/J:12.
Nestle, M., Wing, R., Birch, L., DiSogra, L., Drewnowsk, A., Middleton, S., Madeleine, S. G., Sobal, J., Winston, M., Economos C., 1998. Behavioral and Social Influences on Food Choice. Nutrition Reviews 56, 50-74.
Olsen, S.O., 2003. Understanding the relationship between age and seafood consumption: the mediating role of attitude, health involvement and convenience. Food Quality and Preference 14, 199-209.
Pesaran, M.H., Shin, Y., Smith, R.J., 2001. Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics 16, 289–326.
Pesaran, M.H., Shin, Y., 1998b. Generalized impulse response analysis in linear multivariate models. Economic Letters 58, 17–29.
Phillips, P.C.B., Perron, P.,1998. Testing for a unit root in the time series regression. Biometrika 75, 335-346.
Park, S.K., Ryu, J.G., 1999. New policy paradigms for Korean fisheries’ transition to responsible practice. Marine Resource Economics 14, 79-93.
Parris, H., 2010. Is the Western and Central Pacific Fisheries Commission meeting its conservation and management objectives? Ocean & Coastal Management 53, 10-26
Sims, C., 1980. Macroeconomics and reality. Econometrica 48, 1–48.
Schwarz, G.,1978. Estimating the dimension of a model. Annals of Statistics 6, 461–464.
Swartz, W., Sumaila, U.R., Watson, R., Pauly, D., 2010. Sourcing seafood for the three major markets: The EU, Japan, and the USA. Marine Policy 34, 1366-1373.
Trondsen, T., Braaten, T., Lund, E., Eggen, A.E., 2004. Health andseafood consumption patterns among women aged 45–69 years. A Norwegian seafood consumption study. Food Quality and Preference 15, 117–128.
Trondsen, T., Scholderer, J., Lund, E., Eggen, A.E., 2003. Perceived barriers to consumption of fish among Norwegian women. Appetite 41, 301-314.
The Nautical Institute, 1997, Maritime education and training: A practice guide.
Verbeke, W., Vermeir, T., Brunso, K., 2007. Consumer evaluation of fish quality as basis for fish market segmentation. Food Quality and Preference 18, 651-661.
Wu, B.,Winchester, N., 2005. Crew study of seafarers: a methodological approach to the global labour market for seafarers. Marine Policy 29, 323-330
Zivot, E., Andrews, D.W.,1992. Further evidence on the great crash, the oil-price shock, and the unit-root hypothesis. Journal of Business and Economic Statistics 10, 251-270.