Please use this identifier to cite or link to this item: https://ah.lib.nccu.edu.tw/handle/140.119/33739
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dc.contributor.advisor黃智聰zh_TW
dc.contributor.advisorHuang, Jr-Tsungen_US
dc.contributor.author蔣村逢zh_TW
dc.contributor.authorChiang, Tsun-Fengen_US
dc.creator蔣村逢zh_TW
dc.creatorChiang, Tsun-Fengen_US
dc.date2003en_US
dc.date.accessioned2009-09-17T10:01:11Z-
dc.date.available2009-09-17T10:01:11Z-
dc.date.issued2009-09-17T10:01:11Z-
dc.identifierG0091260004en_US
dc.identifier.urihttps://nccur.lib.nccu.edu.tw/handle/140.119/33739-
dc.description碩士zh_TW
dc.description國立政治大學zh_TW
dc.description東亞研究所zh_TW
dc.description91260004zh_TW
dc.description92zh_TW
dc.description.abstract自從中國實施經濟改革之後,其經濟快速成長。從1978到2002年之間,中國的年平均成長率為8.07﹪。但同時期,中國的不平等卻顯示不同的變動趨勢。在1980年代,經濟改革似乎同時促進經濟成長與不平等程度的下降。然而1990年代之後,不平等卻呈現向上爬升的趨勢。本論文的研究目的,即是探討改革後,中國經濟成長與不平等間的因果關係。\n 根據之前的文獻,經濟成長和不平等之間可能相互影響,但影響方向卻不確定。本論文研究方法採用Granger因果檢定,估計成長與分配的因果關係以及影響方向。本研究採用Toda and Yamamoto (1995)所提出的向量自迴歸程序,對Granger因果模型進行卡方檢定的統計推論。Toda和Yamamoto證明,研究者能夠估計一個k+dmax階的向量自迴歸模型,其中dmax是時間數列變數最大整合階數,k為落差期數。然而,進行統計推論時,研究者只需利用卡方統計量檢驗前k階的迴歸係數是否顯著,而不需檢驗最後的dmax階迴歸係數。利用此研究方法,本論文發現以下結果:一、經濟成長會正面且顯著地影響不平等;二、不平等不會影響到經濟成長;三、實證結果是穩健的,其不因使用不同的所得不平等指數或落差期數而有所變化。\n 會產生第一種結果的主要原因,在於中央政府傾斜政策的實施。與先前文獻完全集中研究自由經濟或計畫經濟不同,中國經濟正處於轉型過程,可能是本研究不能發現所得不均等對經濟成長的主要因素。\n\n本研究的政策意涵為,由於經濟持續增長,使得不均等的情況更加惡化。因此,中央政府應該取消向東部沿海傾斜的政策,並且增加對中西部地區進行投資的意願。但是,將資源投入在中西部,使得到的收益遠遠小於投入在東部者。因此為了促進持續經濟成長,不建議採取某些能迅速降低不平等的政策,例如財政移轉。zh_TW
dc.description.abstractEver since economic reform has been carried out in China, its economic growth rate has been remarkable. Its annual growth rate of per capita GDP was about 8.07% for the period 1978-2002, but its income inequality level presented a different moving trend during this time. In the 1980s, it seemed that economic reform decreased this inequality successfully, but the situation of income distribution started to deteriorate beginning in 1990. The purpose of this study is to research if the relationship between economic growth and inequality exists in post-reform China.\nAccording to previous literature, economic growth and inequality can influence each other, but their influential directions are uncertain. This study adopts the Granger-causality test as a methodology to estimate their relationship and influential directions. This study tests Granger-Causality with the chi-square statistic, which was proposed by Toda and Yamamoto (1995). They wrote that researchers could estimate a (k+dmax)th-order VAR where dmax is the maximal order of integration. Only the first k coefficients have to be jointly tested with the chi-square statistic, and the last dmax coefficients are ignored. This study finds the following results: (i) growth positively influences inequality; (ii) inequality does not influence growth; and (iii) the results are sturdy no matter what inequality index or what lag lengths are used in the empirical test.\n\nThe result (i) can be attributed to the biased central government policy. Differencing from previous studies, which focused on democratic or undemocratic economies, this study researches a transitional economy. It could be the reason why this study finds no evidence of the effect of inequality on growth.\n The policy implications of this study are that China’s government has to give up biased policies and increase the incentives of investing in inland regions. Besides, in order to promote sustainable economic growth, some policies like fiscal transfers, which can reduce inequality quickly, are not recommended.en_US
dc.description.tableofcontentsCHAPTER 1. INTRODUCTION\n1.1 Research Background and Purpose\n1.2 Research Method and Restriction\n1.3 Research Steps and Framework\n\nCHAPTER 2. LITERATURE REVIEWS\n2.1 The Effect of Growth on Inequality\n2.2 The Effect of Inequality on Growth\n2.3 The Situation of China’s Inequality\n\nCHAPTER 3. RETROSPECTIVE OF ECONOMIC GROWTH AND\nINEQUALITY IN POST-REFORM CHINA\n3.1 Economic Growth for Period of 1978~2002\n3.2 The Evolution of Income Inequality Level\n3.3 Correlation Coefficient between Growth and Inequality\n\nCHAPTER 4. METHODOLOGY\n4.1 Traditional Granger-Causality Test\n4.2 Toda and Yamamoto’s VAR Procedure\n4.3 Empirical Model and Data Source\n\nCHAPTER 5. EMPIRICAL RESULTS\n5.1 Unit Root Test\n5.2 Granger-Causality Test\n5.3 Test of Robustness\n\nCHAPTER 6. CONCLUSIONS AND IMPLICATIONS\n\nAPPENDIX\n\nREFERENCESzh_TW
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dc.source.urihttp://thesis.lib.nccu.edu.tw/record/#G0091260004en_US
dc.subjectGranger因果檢定zh_TW
dc.subject不平等zh_TW
dc.subject中國zh_TW
dc.subject向量自迴歸zh_TW
dc.subjectChinaen_US
dc.subjectGranger-Causalityen_US
dc.subjectinequalityen_US
dc.subjectVARen_US
dc.titleThe Granger Causality between Economic Growth and Income Inequality in Post-Reform Chinazh_TW
dc.title改革後中國之所得不均等與經濟成長之間的Granger因果關係zh_TW
dc.typethesisen
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