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。 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。 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。 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。 / Ever 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. According 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. The 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. 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.

近年來由於亞洲金融風暴的肆虐，產生經濟不景氣，使得失業的問題逐漸受到社會所關注，本論文企圖以三個時間序列方法：1.單變量ARIMA模型；2.轉換函數(TF)模型；3.向量自迴歸(VAR)模型來建立台灣地區的失業率時間序列預測模型。資料則是利用台灣地區民國75年1月至民國87年12月的失業率月資料作實證預測分析，為了知道資料是否來自時間趨勢模型，測試是否經過差分消掉一部份的記憶會發生預測的誤差，所以先以多步(multi-step)預測和一步(one-step)預測的方法計算出民國88年1月至88年12月預測值，而預測評估準則則採用(1)MAPE、RMSPE、MPE及泰爾不等係數(THEIL)；(2)變化方向誤差與趨勢變化誤差兩大方向來做預測比較。最後將算出的12期預測值與行政院主計處整體統計資料庫中所得到的失業率實際值利用預測評估準則做比較，結果發現一步預測法較多步預測法準確；而向量自迴歸模型(VAR)在大部份的預測期數上有較小的MAPE、RMSPE、MPE及THEIL值，因為此VAR模型考慮了在變數之間的共整合現象，有助於模型的預測，所以有較好預測的能力；反而是較複雜的ARIMA模型及轉換模型預測能力稍差一點。 / In this thesis, we plan to construct three time series models to forecast the Taiwan unemployment Rate. These time series models are ARIMA model、transfer function (TF) model and Vector Autoregressive (VAR) model. The data set consists of monthly observations for the period 75:1-87:12 for unemployment rate. We want to know if the data came from time trend model. First, we use multi-step forecasting and one-step forecasting to calculate 12 forecasted values from 88:01-88:12. Then We compare the prediction performance of these two methods by using：(1) MAPE、RMSPE、MPE and Theil’s Inequality Coefficient (THEIL)；(2) Direction of Change Error and trend Change Error etc. It is found that one-step forecasting is more correct than multi-step forecasting and the forecasting performance of VAR model is improved by explicitly taking account of cointegration between the variables in the model，so VAR model has lower MAPE、RMSPE、MPE and THEIL for most horizons. However，the more parsimonious ARIMA and transfer function models have higher MAPE、RMSPE、MPE for most horizons.

本文是探討管理浮動匯率時期（1978年第三季至1993年第三季），台灣地區經常帳盈餘發生的原因，同時考慮匯率因素、貨幣市場及商品與勞務市場吸納的情況。利用兩個向量自迴歸模型，分別納入：(1)匯率、利率、經常帳、消費節約及貨幣供給，(2)匯率、利率、經常帳、財政盈餘及貨幣供給，藉由因果關係檢定、預測誤差分解、及衝擊反應，分析經常帳失衡的原因。 　　實証結果指出：台灣地區經常帳盈餘，深受匯率、財政盈餘及消費節約的影響，這個結論與我國低估幣值與出口拓展的政策一致。且經常帳盈餘並不能夠顯著的影響貨幣供給，這個結論與央行沖銷的措施一致，其目的無非是要隔離國外部門影響國內貨幣。足見自由化的匯率政策，不但讓匯率反應出合理的水準值，同時可追求獨立的貨幣政策，配合著獎勵投資、消費及增加公共支出，增加國內吸納，藉以減少鉅幅的經常帳盈餘。