本篇探討在2002年起的原物料多頭浪潮至2011年3月期間，以原物料指數：高盛綜合商品指數(GSCI)、農商品指數(GSCI AG)與股市、匯市為研究對象，利用共整合檢定與向量自我迴歸(VAR)還有向量誤差修正模型(VECM)模型等實證方法，在九個國家中，探討變數間的關聯性。 實證結果顯示，在股、匯市與GSCI的模型中，美國、印度與俄國具有共整合關係；在股、匯與GSCI AG的模型中，美國、澳洲與台灣具有共整合關係。表示這幾個國家變數間存在長期穩定關係。VAR與VECM結果顯示，不管是原物料出口國或是進口國，對於各國股市的影響，皆為顯著正向影響，在Granger 因果檢定上，除了日本以外，所有國家的股市皆具有Granger領先原物料變數的關係，而原物料會Granger領先於股市的國家有日本與俄羅斯，其中俄國股市與原物料GSCI具有雙向因果關係股市也顯著領先原物料指數。在農糧物料部分，股市會Granger領先農糧指數的國家比起綜合商品指數來說大幅減少許多，僅剩中國，印度兩國。在匯率部分，除了美國因為大多商品以美金計價，使得美元貶值與商品價格上漲有著顯著的關係外，其他國家貨幣因為是對美元匯率，所以一致呈現出當原物料價格上漲該國貨幣就會升值的影響。在原物料輸出大國，加拿大與澳洲特別明顯。另外在匯市上，原物料指數對大多數國家匯市具有Granger領先關係，而其中匯市Granger領先股市的國家有台灣與韓國，表示此兩國匯市與原物料具有雙向因果關係。在農糧物料方面，農商指數對大多數國家匯市仍具有Granger領先關係，而其中匯市Granger領先股市的國家僅有俄國，表示此國匯市與原物料具有雙向因果關係。

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.

價量關係研究於金融市場甚豐，然於台灣之住宅新推個案市場則相當匱乏，因此本研究關注台灣住宅新推個案市場之價量關係，考量住宅空間次市場差異，區分為內部關係─價量關係，以及外部關係─價／量波及效果。研究以全國及五大都會區為（台北市、台北縣、桃竹地區、台中都會區及南高都會區）為空間範圍；1996年第1季至2009第4季之可能成交價、成交量資料，運用時間序列分析方法，釐清住宅空間次市場內部之價量關係是否存在差異，以及次市場間成交價／量是否存在相互影響的效果，以提供預測市場價量趨勢之參考。 研究結果顯示台北市之成交量領先成交價3期，價量交互影響程度較其他地區大，可知台北市住宅市場之成交量變動在住宅市場趨勢預測中更為關鍵；南高都會區之價量存在共整合關係，表示價量調整具長期均衡，背離程度有限；台北縣、桃竹地區及台中都會之價量則無明顯領先落後關係，價量關係相對薄弱。波及效果之研究結果顯示成交價之波及效果主要由台北都會區擴散至其他都會區，影響方向為單向且範圍較大；成交量則以相對鄰近之都會區為影響範圍，影響主要為雙向，但範圍較小。本研究認為台灣住宅市場過度關注價格訊息，然而更應重視成交量變化的掌握，並關注住宅空間次市場基本結構之差異，避免使消息面造成的過度預期成為主導市場的力量。 / There are numerous researches in stock markets and finance, but few in Taiwan newly construction and pre-sale housing markets. Using the Cathay Real Estate Index Quarterly Reports for the period 1996-2009 and applying Granger causality test, the thesis examines price and volume relationship in five metropolises (Taipei City, Taipei County, Taoyuan-Hsinchu, Taichung Metropolis and Tainan-Kaohsiung) in Taiwan. And with the concern of the differences of housing submarkets, the price and volume relationship is classified as intra-relationship and inter-relationship. The former is price and volume relationship in a certain metropolis, the later is the ripple effects of housing price or trading volume between metropolises. The result of intra-relationship shows that housing price Granger-cause the trading volume in Taipei city. That is, volume provides useful information to predict future price. And there is a long-run relationship in Tainan-Kaohsiung metropolis. From the aspect of inter-relationship, housing price changes first in Taipei City and Taipei County; trading volumes have mutual ripple effect between two neighboring metropolises. The results of the research are useful for housing market participants: We should keep an eye on the changes of trading volume. Also the structure of the submarket is fundamental to form the investment strategies.

封閉型基金的掛牌買賣價格，與其投資標的淨資產價值（NAV, net asset value）間，總是存在一定程度的差距，且幾乎為10%~20%的折價現象，被視為財務學上的一種異常（anomaly）。早期研究學者們由經濟理性的角度解釋此種現象，認為是基金管理的績效表現、投資標的流動性或是稅制上的差異等等角度來解釋此一現象，但並沒有獲得一致的結論。 近期以來，有學者嘗試從行為財務學的角度，認為封閉型基金的折溢價現象及其幅度的變化，是由於投資人情緒（investor sentiment）的波動所造成。除了傳統的迴歸模式，更有不少學者以嚴謹的計量方式分析，例如財務時間序列的許多技巧。本研究即以時間序列之單根檢定（unit root test）、共整合現象檢定（co-integration test）及Granger因果關係檢定（Granger Causality test）等等方式，分析封閉型基金折溢價現象是否由投資人情緒所造成，及其兩者間是否有共整合現象。 雖然已有部分文獻探討類似議題，但跨國比較分析通常僅限於英、美兩國，且英、美兩國市場連動程度太高，可能影響分析結果的正確性；除此之外，樣本分析期間亦通常不超過十年。本研究以1991-2005年英國掛牌之封閉型基金為研究樣本，並包含投資標的為日本的封閉型基金，進行英國、日本之間的跨國性比較；不但有更足夠的樣本時間長度，亦能驗證是否不同跨國分析亦會有相同結論。 共整合現象檢定及Granger因果關係檢定大致支持行為財務學的角度。但英國、日本跨國比較的結果，似乎並不完全等同於前述英、美跨國比較的結果。建議後續可從掛牌國與投資標的區域連動程度較低的封閉型基金作為研究方向。 / The closed-end funds discounts have been an interesting phenomenon for a long period. Some theories based on economic rationale try to solve the puzzle but fail to get consistent conclusions. Recently some theories based on behavioral finance, such as the investor sentiment hypothesis, have been proposed to solve this puzzle. This study examines the investor sentiment hypothesis based on various time-series tests and finds some interesting results. Briefly, our conclusions are as follows: 1. The discounts can vary widely between funds and seem to be persistent in our sample period. 2. The local market indices are cointegrated with the domestic closed-end funds discounts and the information is flowed from the market to the closed-end funds, which support the investor sentiment hypothesis. 3. The causality relationship between the foreign closed-end funds and the local indices is not obvious. Based on this, the market segmentation hypothesis seems to hold in our sample, which indicates that investing in the foreign funds provide investors with the benefit of diversification. For future researches, we suggest that more the foreign funds should be included in the sample and the classification of the degree of investor sentiment and the categories of funds can also be improved.

近十年來，因投機需求、游資充斥等原因使台灣房價成長之上升趨勢明顯高於許多國家，房屋交易方面則呈現明顯起伏不定之走勢，台灣政府單位為達成物價穩定、金融穩定與經濟成長等目標並且避免金融危機再度發生，透過制定及執行貸款管制政策，期能有效抑制假性需求與房價上漲趨勢。 然而，貸款管制是否能有效抑制房價，過去未有文獻針對購屋貸款管制工具與房價及住宅交易量觀察長期趨勢關係並缺乏整體性探討，故本研究欲藉由探究貸款成數與購屋貸款餘額占國內生產毛額比率與住宅市場間是否存在長期、短期影響或其間因果關係，以得知是否政策的投入能夠確切影響標的、達成目標。 本文嘗試以 2000 年第一季至2016 年第二季之貸款管制工具變數及總體經變數資料，運用 ARDL Bounds Test、ARDL-ECM 模型及Toda and Yamamoto 因果檢定探究購屋貸款管制變數對於台灣住宅市場間之長期與短期動態關係及因果關係。研究結果顯示，購屋貸款管制變數對於房價及交易量有顯著之影響，尤其對於住宅交易量方面具有較為明顯之效果，因此，期望透過本研究對於台灣未來金融、房市政策規劃提出建議。 / Over the past decade, an abundance of money and speculative demand from the Quantitative Easing (QE) monetary policy drove the housing price in Taiwan to rise sharply, and the volume of housing market is unstable. To stabilize the financial markets, the government have formulated policies on housing markets and mortgage control to curb rising housing prices. In order to understand the effect of mortgage control on curbing housing price, this study examines the long-run and short-run relationship and causality effect among loan-to-value ratio and mortgage-to-GDP ratio and housing markets. This study used ARDL model, bounds test and Toda and Yamamoto causality to analyze quarterly data over the period 2000-Q1 to 2016-Q2. Empirical results show that mortgage control has significant effects on the housing market. Results further shown that the influence on the volume is more obvious than on the price. Results of this study provide precious policy implications for future housing financial sectors.

論文摘要 本文主要是檢定內生成長模型之下，政府的國防以及教育支出行為與經濟成長的關係。我們發覺以往的文獻探討，對於教育對經濟成長關係的探討大多著重在人力資本對經濟成長之影響，而多持正面的看法；學者對國防支出有持正面；亦有持負面之看法。根據本文所做的實證檢定則發現，長期之下，我們所欲檢定之變數，國民所得、教育支出以及國防支出皆具有單根之關係，顯示三個數列在長期之下，不具有穩定之狀態；亦即是呈現一個隨機漫步的情形，此正和我國經濟成長、國防支出、教育支出不斷增加的事實相吻合。而教育支出和國民所得亦有具有共整合的關係存在，這顯示了在長期之下，國民所得和教育支出的一階差分會呈一穩定的線性關係，即長期之下，國民所得和教育支出會有相同成長趨勢，而國民所得和國防支出間，因為國防預算支出的比例不斷降低，所以我們無法得出該支出與國民所得有共整合關係，顯示國民所得和國防支出長期下並無相同的成長趨勢。 而就因果關係檢定之結果來看，我們發現，國民所得對教育支出有一領先的關係，解釋了長期之下，國民所得的資訊可以用來預測教育支出成長的事實，同時也可以說明我國符合華格納法則中所提到之現象。 而就國防支出和國民所得而言，本文得出國民所得和國防支出存在雙向因果關係。當以國民所得作為被解釋變數時，可能因國防支出使用的效率，或者國防的支出確實提高有效需求並促進現代化，因而使國防支出對國民所得有顯著之影響。至於國民所得對國防支出的影響方面，我們就國防支出需求面來看國防預算的制定，是必須考慮所得的經濟因素。且依據華格納法則，隨著我國國民所得不斷增加，對於政府國防支出的需求，亦會相對提升。因此，吾人可以說國民所得增加會影響國防支出。 　目　　　　錄 第一章 緒論……………………………………………… 1 第一節 經濟成長與政府支出……………………….. 1 第二節 研究方向……………………………………….. 5 第三節 本文架構……………………………………….. 6 第二章 相關探討及文獻回顧…………………………… 8 第一節 相關公共支出對經濟成長的文獻回顧……… 8 第二節 教育投資、支出及國防支出對經濟成長之影響… 11 第三節 國民所得對政府支出的影響………………… 23 第三章 計量方法………………………………………….. 29 第一節 單根檢定………………………………………… 29 第二節 共整合檢定………………………………………... 32 第三節 修正誤差模型…………………………………….. 34 第四節 因果關係檢定………………………………… 36 第四章 模型設定及實證結果…………………… . 41 第一節 模型的設定…………………………………… 41 第二節 單根和共整合檢定…………………………… . 42 第三節 修正誤差及因果檢定………………………….…. 47 第四節 實證結果之探討…………………………………. 55 第五章 結論與建議……………………………………… . 63 第一節 本文結論……………………………………….… 63 第二節 本文之建議…………………………………….…. 65 參考文獻……………………………………………………. 70 / We are going to dicuss the long-run relationship between income and govnernment's education and national defense expenditure in Taiwan.We start at testing wheather income ,education expenditure ,and national defense have unit or not. We find all the series have the characteristic of unit root.It shows that they are not stationary.Then we use Granger's cointegration test,and see that the series of income and education got the relationship of cointegration,instead that of income and national defense. Finally,we test long- run relationship by Granger causality.Due to the existence of cointegration between income and education expenditure,we can use two-steps OLS to test whether there exist Granger causality between them,and we find income will affect education expenditure ,however education expenditure will not affect income.And we use F test to find the Granger causality between income and nation defenseand we get the conclusion that there exists a bilateral Granger causality.It means that they will affect each other.

本篇探討在2010年4月16日滬深300股指期貨正式上市到2012年9月18日止的連續近月每日收盤日資料，進行區域內金融期貨市場連動關係的研究，試圖發現兩岸三地之股價指數期貨市場在亞太地區的金融主導地位，以作為國內外投資者在區域內的投資決策參考。 實證結果顯示，從共整合及向量誤差修正模型檢定發現，兩岸三地股指期貨具有長期均衡及短期的互動關係，因此可以視此三地為單一區域市場。在Granger因果檢定上，台股指數期貨雖無法預測恆生指數期貨，但仍明顯領先滬深300股指期貨且程度大於恆生指數期貨，或可推測兩岸因ECFA的簽訂使實體經濟的關聯性更為緊密，至於恆生指數期貨大多以金融、地產股為其主要成分，與大陸主要以實體經濟為主的金融市場，其Granger預測滬深300股指期貨的能力因此相對較弱。另由衝擊反應檢定得知恆生指數期貨為一獨立的市場，不受台灣及大陸指數期貨市場衝擊的影響；滬深300指數期貨因大陸金融市場逐漸開放，也會受到香港及台灣金融期貨市場之衝擊而產生影響；至於台股指數期貨則在兩岸三地，最易受到其他市場影響。最後由預測變異數分解檢定發現，台股指數期貨及滬深300股指期貨的波動皆易受到恆生股價指數期貨變異的影響，而恆生指數期貨在兩岸三地間之解釋能力最強，於兩岸三地間具金融主導地位。至於台股指數期貨對大陸金融期貨的影響也有突出的表現，因此若政府有心推展亞太金融中心之營運，勢必得加強區域間整合的力度，提出有利吸引外資之最政策，以增加台灣股市於國際間之競爭力。 / This study conducts analysis of regional linkage between financial futures market by examining consecutive daily closing information from April 16, 2010 (the official list date of CSI 300 index futures) to September 18, 2012. This study tries to find the financial dominance of these index futures market in the Asia Pacific region and hopefully it may be used as an investment decision reference for domestic and foreign investors. The empirical results show that from the total integration and vector error correction model tests and three places all indicate long-run equilibrium stock index futures and short-term interaction. Therefore, these three places can be viewed as a single regional market. In the Granger causality test on the TAIEX futures and Hang Seng Index futures, in spite of TAIEX futures can’t predict Hang Seng Index futures, it is significantly ahead of the CSI 300 index futures. TAIEX futures on the CSI 300 index futures even more impact than the Hang Seng Index Futures. It can explain that the ECFA has been signed and results show closely-related economy. Since the Hang Seng Index futures are mainly from financial and real estate stocks while the mainland-based financial market is mainly from the real economy, Granger predicts ability of CSI 300 index futures is relatively weak. Another test on the impulse response shows that (1) Hang Seng Index Futures is an independent market and is not affected by shocks from Taiwan and the mainland index futures markets, (2) CSI 300 index futures is affected by shocks from Hong Kong and Taiwan because of the gradually open financial markets, and (3) TAIEX futures can be seen as a potential Taiwanese dish economy because it is most vulnerable to other market influences among the three places. To sum up, the forecast variance decomposition tests show that TAIEX futures and the CSI 300 stock index futures are vulnerable to fluctuations in the Hang Seng index futures. In order words, the Hang Seng Index futures have the strongest explanatory power among the three places and shows financial dominance. The TAIEX futures also show its significant impact on the mainland China financial futures index. If the Government decides to promote the operation of the Asia-Pacific financial center and to increase competitiveness of Taiwan stock market, it will inevitably have to strengthen inter-regional integration efforts and make the most favorable policies to attract foreign investment.