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Three Essays on Agriculture, Food Export and Economic Growth in Thailand
|關鍵字:||Thailand;泰國;Agriculture;Economic growth;Food export;VAR;FGVDGranger causality;Cointegration;ARMA;Risk analysis;農業;經濟增長;食品出口;VAR;FGVD;Granger 因果;共整合;ARMA;風險分析||出版社:||應用經濟學系所||引用:||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). 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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.||摘要:||
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。
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.
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