臺灣博碩士論文加值系統

在許多新興經濟國家中，由於與食品部門與貿易活動存在密切關係，農業重要性已逐漸增加。如何建構一個具競爭力的農業部門已經在這些國家的經濟發展中，成為一個領先策略考量。本文透過對農業與食品出口的觀點，運用時間序列分析架構，強調對於影響泰國經濟成長的關鍵因素進行分析與說明。
第一篇論文，也是本文第三章，主要在研討泰國在1961年至2009年間農業與經濟成長間的因果關係。運用Granger 因果分析與Wald 卡方係數檢定方法，以衡量並確定變數間的長期因果關係與其間的衝擊傳遞效果。
統計結果顯示，長期因果與顯著的衝擊效果單向存在於「農業產值」到「經濟成長」兩者。透過一般化變異數解析預測（FGVD）方法，顯示農業確實對經濟成長存在顯著影響，而且在長期趨勢中與之相當一致。因此即使近年來發展趨緩，決策者仍應該將農業視為對支持泰國經濟成長相當重要的部門。
在認知透過以多個部門發展為目前泰國經濟策略後，本文第四章運用「多變數自我迴歸（VAR）」模型，以1995年1月至2009年12月資料，檢視泰國出口部門中農業與食品部門的因果關係。Granger 因果分析與Johansen共整合診斷則是用以分析長期均衡與變數間的因果關係。
首先，透過共整合分析統計結果顯示，農業、食品與出口產值之間存在正向長期均衡。其次，因果檢定結果支持出口與食品產值在長短期中均會導出農業產值增加的結果，不過統計結果僅支持出口變數對於短期食品產值增加具顯著影響。此外，FGVD分析的結果亦強烈支持泰國經濟中農業產出為出口部門投入的鏈結關係。
第五章係就泰國農業一個相當重要的次部門-漁業部門進行探討。由於泰國漁產品多年來大量銷往美日等國，漁業部門對於農村地區與相關食品產業實有重大貢獻，因此本文針對其與農業與貿易的關連進行分析，並考慮因匯率波動所導致潛在風險對於產業的衝擊。多年來，超過一半的漁產品市場集中銷售於美日兩個國家，因此造成泰銖與兩國通貨間的匯率波動與該產業的發展息息相關。
本文將泰銖與兩外幣的匯率波動定義為國內漁產品出口風險的來源，並檢測該匯率波動是否引發漁產品供給的劇烈變化。透過ARMA模型的單一變數時間序列分析，本文用以預測十二月期的漁產品供給。同時，應用VAR模型以分析FGVD捕捉的未來風險。決策者可以在考量匯率波動的環境下，應用相關實證結果以降低漁產品未來供給的風險。
本文研究結果指出，決策者應該確認農業必須在產出上保持穩定，以便讓泰國這個以出口為導向經濟體的貿易與食品部門能夠同步成長。三篇論文的結論均指出，泰國應朝向制訂以貿易與食品為主體，並視農業為關鍵與基礎發展原動力的經濟政策而努力。

Agriculture has been consecutive increased its importance in many emerging economies with the closed connection to food sector and trade activities. How to construct a competitive agricultural sector is becoming a leading strategy of economic development in such countries. This study emphasizes on analyzing key factors affecting Thailand economic growth through the aspects of agriculture and food export by interpreting with the time-series analysis framework.
The aim of the first essay presented in Chapter 3 is to investigate the causal relationship between agriculture and economic growth in Thailand over 1961 to 2009. The Granger causality approach and the Wald (χ2) coefficient statistic are utilized to reveal the long-run causal relationship and impact transmission between variables.
Based on the statistical results, a long-run relationship and size impact are detected running from agriculture value to economic growth, but no responsive feedback. These findings, including with the forecast generalized variance decomposition (FGVD), show that the significant influence of agriculture on economy do exist and it consists with economic growth in the long-time period. It concludes that policy-makers should regard agriculture as an important supporting sector for Thai’s economy even with recent stable grows in agriculture.
By considering developments in several sectors as a key economic strategy for presenting Thailand, the essay in Chapter 4 exams the causality between agricultural and food products in Thailand’s export sector using a tri-variate vector autoregressive (VAR) model over the period of January 1995 to December 2009. The Granger causality test, following the Johansen cointegration diagnosis, is performed to analyze the long-run equilibrium and causal relationship between the variables.
As the statistical results show, first, a positive long-run equilibrium is existed among the product values of agriculture, food and export based on the cointegration analysis. Secondly, the causality test results confirm that export and food based on product value leads to an increase in value of agricultural output in both short- and long-term, but total export only leads to an increase in the product value of food in short run. Furthermore the results from FGVD analysis also strongly supports that products from agricultural sector are the major input for export sector in Thai economy.
The purpose of the essay in Chapter 5 focuses on the fishery industry, which is one of the key sub-agriculture sectors of Thailand. We observe its benefits to rural regions and related food industries by exporting products to the US and Japan for decades. We also try to test its connection between agriculture and trade and the potential risk attached with exchange fluctuation. High degree of trade dependence for over half of the production value makes the unexpected fluctuations in exchange rate between Thai baht and two destination currencies highly influence the development in fishery.
Fluctuations of exchange rate between Thai baht and the two currencies, US dollar and Japanese Yen, are defined as the sources of export risk for domestic seafood products. Next, this study tries to detect whether the fluctuations in exchange rate causes the supply of seafood shifts abundantly. The uni-variate time series analysis through an autoregressive moving average (ARMA) model is adopted to forecast the supply of the products in twelve month-period ahead. Next, the FGVD is utilized to capture for the future risk that is analyzed by applying the multivariate vector autoregressive (VAR) model. Policy-makers can put the implications based on these empirical findings to minimize and manage the risks of the future supply of seafood products as from the exchange rate fluctuations.
Policy-makers in Thailand may ensure that agriculture should remain stable in terms of its output as it is particularly relevant to trade and food sectors in such an export-oriented economy. As the conclusion from the three essays above, Thailand may implement economic policies which consider agriculture as a key and basic engine to support the economy in trade and food scenario.

TABLE OF CONTENTS
摘要i
ABSTRACTiii
ACKNOWLEDGEMENTv
TABLE OF CONTENTSvi
LIST OF TABLESix
LIST OF FIGURESx
CHAPTER 1 Introduction1
1.1 Motivation1
1.2 Purposes of this study4
1.3 Research processes5
1.4 Conceptual framework6
1.5 Variables and data sources7
CHAPTER 2 Overview of Agriculture in Thailand9
2.1 Overview of Thailand9
2.2 History of Thai agriculture12
2.3 Growth in agricultural sector14
2.4 Major agricultural productions and trade15
CHAPTER 3 Causality between Agriculture and Economic Development27
Summary27
3.1 Introduction27
3.2 Literature review28
3.3 Data, variables and econometrics30
3.4 Empirical results34
3.5 Conclusions and policy implications38
CHAPTER 4 Does Agricultural Expansion Lead Export Growth?
Evidence for Agricultural and Food Products39
Summary39
4.1 Introduction39
4.2 Literature review41
4.3 Data, variables and hypotheses42
4.4 Time-series econometric methodology44
4.5 Empirical results46
4.6 Conclusions and policy implications
CHAPTER 5 Assessing Supply and Risk Analysis on Seafood Products: Evidence for Export Sector54
Summary54
5.1 Introduction54
5.2 Data and variables58
5.3 Econometrics58
5.4 Empirical results61
5.5 Concluding remarks66
CHAPTER 6 Conclusions and Discussions67
REFERENCES69
APPENDIX A76
APPENDIX B77

Abu-Bader, S., Abu-Qarn, A. S. (2008). Financial development and economic growth: The Egyptian experience. Journal of Policy Modeling, 30(5), 887-898.

Apergis, N., Rezitis, A. (2003). Mean spillover effects in agricultural prices: The case of Greece. Agribusiness, 19(4), 425-437.

Awokuse, T. O. (2007). Causality between exports, imports, and economic growth: Evidence from transition economies. Economics Letters, 94(3), 389-395.

Bank of Thailand. (2010). Economic and financial statistics report. Bank of Thailand. Available at http://www.bot.or.th/Thai/Statistics/ContactPerson/Pages/Contact.aspx (Accessed data: March 2010).

Box, G. E. W., Jenkins, G. M. (1970). Time series analysis: Forecasting and control. Holden Day: San Francisco.

Bose, S., Galvan, A. (2005). Export supply of New Zealand’s live rock lobster to Japan: An empirical analysis. Japan and the World Economy, 17(1), 111-123.

Chang, T., Nieh, C. C. (2004). A note on testing the causal link between construction activity and economic growth in Taiwan. Journal of Asian Economics, 15(3), 591-598.

Department of Provincial Administration. (2011). Population in the end of 2010. Department of Provincial Administration, Ministry of Interior, Thailand. Available at http://www.dopa.go.th/ (Accessed data: March 2011).

Dickey, D., Fuller, W. A. (1979). Distributions of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74(366), 427-431.

Dickey, D., Fuller, W. A. (1981). Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica, 49(4), 1057-1072.

Elliott, G., Rothenberg, T. J., Stock, J. H. (1996). Efficient tests for an autoregressive unit root. Econometrica, 64(4), 813-836.

Enders, W. (2004). Applied econometric time series. 2nd ed. John Wiley & Sons Inc: New York.

Engle, R. F., Granger, C. W. J. (1987). Cointegration and error correction: Representation, estimation and testing. Econometrica, 55(2), 251-276.

Falvey, L. (2000). Thai agriculture: Golden cradle of millennia. Kasetsart University Press: Bangkok.

FAO. (2009). Agricultural and food commodities production. Food and Agriculture Organization of the United Nations. Available at http://faostat.fao.org/site/339/ default.aspx (Accessed data: February 2010).

Granger, C. W. J. (1969). Investigating causal relations by econometric model and cross-spectral methods. Econometrica, 37(3), 424-438.

Granger, C. W. J. (1988). Some recent developments in a concept of causality. Journal of Econometrics, 39(1-2), 199-211.

Granger, C. W. J., Newbold, P. (1974). Spurious regressions in econometrics. Journal of Econometrics, 2(2), 111-120.

Hsiao, F. S. T., Hsiao, M. C. W. (2006). FDI, exports, and GDP in East and Southeast Asia: Panel data versus time-series causality analyses. Journal of Asian Economics, 17(6), 1082-1106.

Jatuporn, C., Chien, L. H., Sukprasert, P., Thaipakdee, S. (2011). Does a long-run relationship exist between agriculture and economic growth in Thailand? International Journal of Economics and Finance, 3(3), 227-233.

Johansen, S. (1988). Statistical analysis of cointegration vectors. Journal of Economic Dynamics and Control, 12(2-3), 231-254.

Johansen, S. (1991). Estimation and hypothesis testing of cointegration vectors in Gaussian vector autoregressive models. Econometrica, 59(6), 1551-1580.

Johansen, S. (1995). Likelihood-based inference in cointegrated vector autoregressive models. Oxford University Press: Oxford.

Johansen, S., Juselius, K. (1990). Maximum likelihood estimation and inference on cointegration with application to the demand for money. Oxford Bulletin of Economics and Statistics, 52(2), 169-209.

Johansen, S., Juselius, K. (1994). Identification of the long-run and the short-run structure: An application to the IS-LM model. Journal of Econometrics, 63(1), 7-36.

Katircioglu, S. T. (2004-2005). Co-integration and Causality between GDP, agriculture, industry and service growth in North Cyprus: Evidence from time series data, 1977-2002. Review of Social, Economic and Business Studies, 5/6(Fall), 173-187.

Katircioglu, S. T. (2006). Causality between agriculture and economic growth in a small nation under political isolation: A case from North Cyprus. International Journal of Social Economics, 33(4), 331-343.

Kmenta, J. (1986). Elements of econometrics. MacMillan Publishing Co: New York.

Konya, L. (2006). Export and growth: Granger causality analysis on OECD countries with a panel data approach. Economic Modelling, 23(6), 978-992.

Konya, L., Singh, J. P. (2009). Causality between international trade and gross domestic product: The case of the Indian agricultural and manufacturing sectors. International Journal of Economics and Business Research, 1(1), 61-75.

Lamb, R. L. (2000). Food crops, exports, and short-run policy response of agriculture in Africa. Agricultural Economics, 22(3), 271-298.

LeBel, P. (2008). The role of creative innovation in economic growth: Some international comparisons. Journal of Asian Economics, 19(4), 334-347.

Lim, C., Pan, G. W. (2005). Inbound tourism developments and patterns in China. Mathematics and Computers in Simulation, 68(5-6), 499-507.

Love, J., Chandra, R. (2005). Testing export-led growth in South Asia. Journal of Economic Studies, 33(2), 132-145.

MacKinnon, J. G. (1996). Numerical distribution functions for unit root and cointegration tests. Journal of Applied Econometrics, 11(6), 601-618.

MacKinnon, J. G., Haug, A. A., Michelis, L. (1999). Numerical distribution functions of likelihood ratio tests for cointegration. Journal of Applied Econometrics, 14(5), 563-577.

Ministry of Agriculture and Cooperatives. (1992). 100 years of the Ministry of Agriculture and Cooperatives 2535 BE. Ministry of Agriculture and Cooperatives, Thailand.

Ministry of Agriculture and Cooperatives. (1996). His Majesty the king and the development of Thai agriculture. Commemorative of the golden jubilee year 2539 BE. Amarin Printing and Publishing, Co. Ltd.: Bangkok.


Ministry of Agriculture and Cooperatives. (2009). Agriculture. Ministry of Agriculture and Cooperatives of Thailand. Available at http://www.moac.go.th/builder/moac/article update_eng.php?id=28 (Accessed data: November 2009).

Ministry of Commerce. (2011). MENUCOM: Principle exports. Available at http://www2. ops3.moc.go.th/infor/thaitrade/ (Accessed data: March 2011).

Ministry of Foreign Affairs. (2010). Thailand in the 2000’s: Agriculture. Ministry of Foreign Affairs of Thailand. Available at http://www.mfa.go.th/multimedia/ E_Book/b5.pdf (Accessed data: February 2010).

(van) Mulekom, L., Axelsson, A. Batungbacal, E. P., Baxter, D., Siregar, R. de la Torre, I., (2006). Trade and export orientation of fisheries in Southeast Asia: Under-priced export at the expense of domestic food security and local economies. Ocean & Coastal Management, 49(9-10), 546-561.

Office of Agricultural Economics. (2004). Agriculture in Thailand. Office of Agricultural Economics, Ministry of Agriculture and Cooperatives, Thailand.

ONESDB. (2010). Quarterly gross domestic products. The Office of the National Economic and Social Development Board of Thailand. Available at http://www. nesdb.go.th/Default. aspx?tabid=95 (Accessed data: March 2010).

ONESDB. (2011). Quarterly gross domestic products. The Office of the National Economic and Social Development Board of Thailand. Available at http://www.nesdb.go.th/ Default. aspx?tabid=95 (Accessed data: March 2011).

Pesaran, M. H., & Shin, Y. (1998). Generalized impulse response analysis in linear multivariate models. Economics Letters, 58(1), 17-29.

Phillips, P. C. B., Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335-346.

Ramos, F. F. R. (2001). Exports, imports, and economic growth in Portugal: Evidence from causality and cointegration analysis. Economic Modelling, 18(4), 613-623.

Tiffin, R., Irz X. (2006). Is agriculture the engine of growth? Agricultural Economics, 35(1), 79-89.

Thornton, J. (1996). Co-integration, causality and export-led growth in Mexico, 1895-1992. Economics Letters, 50(3), 413-416.

Thornton, J. (1997). Export and economic growth: Evidence from 19th Century Europe. Economics Letters, 55(2), 235-240.

Thungsuwan, S., Thompson, H. (2003). Exports and economic growth in Thailand: An empirical analysis. BU Academic Review, 2(1), 10-13.

Toda, H. Y., Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated process. Journal of Econometrics, 66(1-2), 225-250.

Ullah, S., Zaman, B., Farooq, M., Javid, A. (2009). Cointegration and causality between exports and economic growth in Pakistan. European Journal of Social Sciences, 10(2), 264-272.

Vohra, R. (2006), Export and economic growth: Further time series evidence from less-developed countries. International Advances in Economic Research, 7(3), 345-350.