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題名 台灣荷蘭病現象之研究
The Study of the Dutch Disease Phenomenon in Taiwan作者 吳育齊
Wu, Yu-Chi貢獻者 黃仁德<br>蕭明福
Huang, Jen-Te<br>Shaw, Ming-Fu
吳育齊
Wu, Yu-Chi關鍵詞 荷蘭病
共整合分析
向量誤差修正模型
Dutch Disease
Cointegration
Vector Error Correction Model日期 2024 上傳時間 4-九月-2024 14:39:47 (UTC+8) 摘要 台灣的資訊電子工業從2000年後開始蓬勃發展，尤其是新冠肺炎疫情後，半導體產業出口更是成長快速，引發國人對於台灣是否存在荷蘭病現象的疑慮。本文以2008至2023年資料觀察台灣非農產業經濟結構變化，並計量分析資訊電子工業擴張對非農產業的影響。我們將產業分為工業細項產業、服務業細項產業，一共17種產業，產出占比為被解釋變數，資訊電子工業毛利率對各產業毛利率的比率、受僱人數占比、固定投資佔比為解釋變數，以共整合分析、向量誤差修正模型，探討產出占比與毛利率比率之間的長、短期關係。 共整合分析結果顯示，製造業的毛利率估計係數不是顯著為正就是不顯著，就製造業而言，我國製造業不存在荷蘭病現象。服務業中，毛利率估計係數顯著為負的有運輸及倉儲業、金融及保險業、支援服務業，其中運輸及倉儲業、金融及保險業的受僱人數占比與固定投資占比皆呈現下滑，因此就全非農產業而言，我國服務業存在荷蘭病現象。向量誤差修正模型估計結果顯示，當產出占比偏離長期均衡值時，民生工業、營建工程業、支援服務業、及藝術娛樂及休閒服務業的產出占比會向毛利率比率等解釋變數所決定的長期均衡值收斂。
The information and electronics industry in Taiwan began to flourish after 2000, especially following the COVID-19 pandemic, with rapid growth in semiconductor exports. This has led to concerns among the public about whether Taiwan is experiencing the phenomenon of Dutch Disease. This study examines changes in Taiwan’s non-agricultural economic structure from 2008 to 2023, focusing on the impact of the information electronics industry’s expansion. The analysis covers 17 industries, dividing them into detailed industrial and service sectors. The output share is the dependent variable, while the gross margin ratio of the information electronics industry, employment share, and fixed investment share are explanatory variables. Using cointegration analysis and vector error correction models (VECM), the study explores the long-term and short-term relationships between the output share and the gross margin ratio. The cointegration analysis results indicate that for the manufacturing sector, the estimated coefficients of the gross margin ratio are either significantly positive or not significant, suggesting that Taiwan’s manufacturing sector does not exhibit Dutch Disease. In the service sector, significantly negative coefficients are found in the transportation and storage, financial and insurance, and support service sectors. Both employment and fixed investment shares show a declining trend in these sectors, indicating that Taiwan’s service sector exhibits Dutch Disease symptoms. The VECM results show that when the output share deviates from its long-term equilibrium value, the output shares of the consumer goods, construction, support service, and arts, entertainment, and recreation services industries converges towards the long-run equilibrium value determined by the gross margin ratio and other explanatory variables.參考文獻 Abdlkarim, R. A., N. A. M. Naseem, and L. Slesman (2018),“Dutch Disease Effect of Oil Price on Agriculture Sector: Evidence from Panel Cointegration of Oil-Exporting Countries,”International Journal of Energy Economics and Policy, 8:5, pp. 241-250. Asiama, R. K. (2019),“Foreign Aid, Dutch Disease, and Manufacturing in African Countries,”Master’s thesis, University of Johannesburg. Corden, P. and J. P. Neary (1982),“Booming Sector and De-industrialization in a Small Open Economy,”Economic Journal, 92:368, pp. 825-848. Dagys, K., W. J. M. Heijman , L. Dries, and B. Agipar (2019),“The Mining Sector Boom in Mongolia: Did It Cause the Dutch Disease?”Post-Communist Economies, 32:5, pp. 607-642. Dornbusch, R., J. P. Neary, and S. V. Wijnbergen (1985), Exchange Rate Policy and Resource Boom: Managing the Dutch Disease. London: Palgrave Macmillan. Engle, R. F. and C. W. J. Granger (1987),“Co-integration and Error Correction: Representation, Estimation, and Testing”Econometrica, 55:2, pp. 251-276. Fardmanesh, M. (1991),“Dutch Disease Economics and Oil Syndrome: An Empirical Study,”World Development, 19:6, pp. 711-717. Granger, C. and P. Newbold (1974),“Spurious Regressions in Econometrics,”Journal of Econometrics, 2:2, pp. 111-120. Ito, K. (2017),“Dutch Disease and Russia,”International Economics, 151:2, pp. 66-70. Johansen, S. and K. Juselius (1990),“Maximum Likelihood Estimation and Inference on Cointegration—with Applications to the Demand for Money,”OxfordBulletin of Economics and Statistics, 52:2, pp. 169-210. Lütkepohl, H. (2005), New Introduction to Multiple Time Series Analysis. Berlin: Springer Science and Business Media. Melvin, J. R. (1968),“Production and Trade with Two Factors and Three Goods,”American Economic Review, 58:6, pp. 1249-1268. Neary, J. P. and D. D. Purvis (1982),“Sectoral Shocks in a Dependent Economy: Long-Run Adjustment and Short-Run Accommodation,”Scandinavian Journal of Economics, 84:2, pp. 229-253. Oomes, N. and K. Kalcheva (2007),“Diagnosing Dutch Disease: Does Russia Have the Symptoms?”IMF Working Paper, WP/07/102. Pelzl, P. and S. Poelhekke (2021),“Good Mine, Bad Mine: Natural Resource Heterogeneity and Dutch Disease in Indonesia,”Journal of International Economics, 131, No.103457. Ploeg, F. V. D. (2011),“Natural Resources: Curse or Blessing?”Journal of Economic Literature, 49:2, pp. 366-420. Safarli, U. E. (2022),“Empirical Analyses of the Dutch Disease in Azerbaijan’s Economy,”Master’s thesis, Middle East Technical University. Salter, W. (1959),“Internal and External Balance: The Role of Price and Expenditure Effects,”Economic Record, 35:71, pp. 226-238. San, G. (1990),“The Status and an Evaluation of the Electronics Industry in Taiwan,”Development Centre, OECD. Taguchi, H. and S. Khinsamone (2017),“Analysis of the “Dutch Disease” Effect: The Case of Resource—Rich ASEAN Economies,”Munich Personal RePEc Archive, MPRA Paper, No. 81010. Wijnbergen, S. (1984),“The ‘Dutch Disease’: A Disease After All?”Economic Journal, 94:373, pp. 41-55. 描述 碩士
國立政治大學
經濟學系
111258036資料來源 http://thesis.lib.nccu.edu.tw/record/#G0111258036 資料類型 thesis dc.contributor.advisor 黃仁德<br>蕭明福 zh_TW dc.contributor.advisor Huang, Jen-Te<br>Shaw, Ming-Fu en_US dc.contributor.author (作者) 吳育齊 zh_TW dc.contributor.author (作者) Wu, Yu-Chi en_US dc.creator (作者) 吳育齊 zh_TW dc.creator (作者) Wu, Yu-Chi en_US dc.date (日期) 2024 en_US dc.date.accessioned 4-九月-2024 14:39:47 (UTC+8) - dc.date.available 4-九月-2024 14:39:47 (UTC+8) - dc.date.issued (上傳時間) 4-九月-2024 14:39:47 (UTC+8) - dc.identifier (其他 識別碼) G0111258036 en_US dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/153298 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 經濟學系 zh_TW dc.description (描述) 111258036 zh_TW dc.description.abstract (摘要) 台灣的資訊電子工業從2000年後開始蓬勃發展，尤其是新冠肺炎疫情後，半導體產業出口更是成長快速，引發國人對於台灣是否存在荷蘭病現象的疑慮。本文以2008至2023年資料觀察台灣非農產業經濟結構變化，並計量分析資訊電子工業擴張對非農產業的影響。我們將產業分為工業細項產業、服務業細項產業，一共17種產業，產出占比為被解釋變數，資訊電子工業毛利率對各產業毛利率的比率、受僱人數占比、固定投資佔比為解釋變數，以共整合分析、向量誤差修正模型，探討產出占比與毛利率比率之間的長、短期關係。 共整合分析結果顯示，製造業的毛利率估計係數不是顯著為正就是不顯著，就製造業而言，我國製造業不存在荷蘭病現象。服務業中，毛利率估計係數顯著為負的有運輸及倉儲業、金融及保險業、支援服務業，其中運輸及倉儲業、金融及保險業的受僱人數占比與固定投資占比皆呈現下滑，因此就全非農產業而言，我國服務業存在荷蘭病現象。向量誤差修正模型估計結果顯示，當產出占比偏離長期均衡值時，民生工業、營建工程業、支援服務業、及藝術娛樂及休閒服務業的產出占比會向毛利率比率等解釋變數所決定的長期均衡值收斂。 zh_TW dc.description.abstract (摘要) The information and electronics industry in Taiwan began to flourish after 2000, especially following the COVID-19 pandemic, with rapid growth in semiconductor exports. This has led to concerns among the public about whether Taiwan is experiencing the phenomenon of Dutch Disease. This study examines changes in Taiwan’s non-agricultural economic structure from 2008 to 2023, focusing on the impact of the information electronics industry’s expansion. The analysis covers 17 industries, dividing them into detailed industrial and service sectors. The output share is the dependent variable, while the gross margin ratio of the information electronics industry, employment share, and fixed investment share are explanatory variables. Using cointegration analysis and vector error correction models (VECM), the study explores the long-term and short-term relationships between the output share and the gross margin ratio. The cointegration analysis results indicate that for the manufacturing sector, the estimated coefficients of the gross margin ratio are either significantly positive or not significant, suggesting that Taiwan’s manufacturing sector does not exhibit Dutch Disease. In the service sector, significantly negative coefficients are found in the transportation and storage, financial and insurance, and support service sectors. Both employment and fixed investment shares show a declining trend in these sectors, indicating that Taiwan’s service sector exhibits Dutch Disease symptoms. The VECM results show that when the output share deviates from its long-term equilibrium value, the output shares of the consumer goods, construction, support service, and arts, entertainment, and recreation services industries converges towards the long-run equilibrium value determined by the gross margin ratio and other explanatory variables. en_US dc.description.tableofcontents 第一章 緒論 1 第二章 文獻回顧 3 第三章 台灣產業結構變化 8 第四章 實證模型 17 第五章 實證過程與結果 20 第一節 資料來源 20 第二節 實證過程與結果 20 一、單根檢定 20 二、遞延期數選定 25 三、共整合迴歸分析結果 25 四、向量誤差修正模型估計結果 41 第六章 結論 49 參考文獻 51 zh_TW dc.format.extent 1409121 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0111258036 en_US dc.subject (關鍵詞) 荷蘭病 zh_TW dc.subject (關鍵詞) 共整合分析 zh_TW dc.subject (關鍵詞) 向量誤差修正模型 zh_TW dc.subject (關鍵詞) Dutch Disease en_US dc.subject (關鍵詞) Cointegration en_US dc.subject (關鍵詞) Vector Error Correction Model en_US dc.title (題名) 台灣荷蘭病現象之研究 zh_TW dc.title (題名) The Study of the Dutch Disease Phenomenon in Taiwan en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) Abdlkarim, R. A., N. A. M. Naseem, and L. Slesman (2018),“Dutch Disease Effect of Oil Price on Agriculture Sector: Evidence from Panel Cointegration of Oil-Exporting Countries,”International Journal of Energy Economics and Policy, 8:5, pp. 241-250. Asiama, R. K. (2019),“Foreign Aid, Dutch Disease, and Manufacturing in African Countries,”Master’s thesis, University of Johannesburg. Corden, P. and J. P. Neary (1982),“Booming Sector and De-industrialization in a Small Open Economy,”Economic Journal, 92:368, pp. 825-848. Dagys, K., W. J. M. Heijman , L. Dries, and B. Agipar (2019),“The Mining Sector Boom in Mongolia: Did It Cause the Dutch Disease?”Post-Communist Economies, 32:5, pp. 607-642. Dornbusch, R., J. P. Neary, and S. V. Wijnbergen (1985), Exchange Rate Policy and Resource Boom: Managing the Dutch Disease. London: Palgrave Macmillan. Engle, R. F. and C. W. J. Granger (1987),“Co-integration and Error Correction: Representation, Estimation, and Testing”Econometrica, 55:2, pp. 251-276. Fardmanesh, M. (1991),“Dutch Disease Economics and Oil Syndrome: An Empirical Study,”World Development, 19:6, pp. 711-717. Granger, C. and P. Newbold (1974),“Spurious Regressions in Econometrics,”Journal of Econometrics, 2:2, pp. 111-120. Ito, K. (2017),“Dutch Disease and Russia,”International Economics, 151:2, pp. 66-70. Johansen, S. and K. Juselius (1990),“Maximum Likelihood Estimation and Inference on Cointegration—with Applications to the Demand for Money,”OxfordBulletin of Economics and Statistics, 52:2, pp. 169-210. Lütkepohl, H. (2005), New Introduction to Multiple Time Series Analysis. Berlin: Springer Science and Business Media. Melvin, J. R. (1968),“Production and Trade with Two Factors and Three Goods,”American Economic Review, 58:6, pp. 1249-1268. Neary, J. P. and D. D. Purvis (1982),“Sectoral Shocks in a Dependent Economy: Long-Run Adjustment and Short-Run Accommodation,”Scandinavian Journal of Economics, 84:2, pp. 229-253. Oomes, N. and K. Kalcheva (2007),“Diagnosing Dutch Disease: Does Russia Have the Symptoms?”IMF Working Paper, WP/07/102. Pelzl, P. and S. Poelhekke (2021),“Good Mine, Bad Mine: Natural Resource Heterogeneity and Dutch Disease in Indonesia,”Journal of International Economics, 131, No.103457. Ploeg, F. V. D. (2011),“Natural Resources: Curse or Blessing?”Journal of Economic Literature, 49:2, pp. 366-420. Safarli, U. E. (2022),“Empirical Analyses of the Dutch Disease in Azerbaijan’s Economy,”Master’s thesis, Middle East Technical University. Salter, W. (1959),“Internal and External Balance: The Role of Price and Expenditure Effects,”Economic Record, 35:71, pp. 226-238. San, G. (1990),“The Status and an Evaluation of the Electronics Industry in Taiwan,”Development Centre, OECD. Taguchi, H. and S. Khinsamone (2017),“Analysis of the “Dutch Disease” Effect: The Case of Resource—Rich ASEAN Economies,”Munich Personal RePEc Archive, MPRA Paper, No. 81010. Wijnbergen, S. (1984),“The ‘Dutch Disease’: A Disease After All?”Economic Journal, 94:373, pp. 41-55. zh_TW
