This paper follows Ghysels, Gourieroux, and Jasiak (1998), examines the causal relation between price and volume in Taiwan Futures Market. I use high frequency intraday data of Taiwan Stock Exchange Capitalization Weighted Stock Index in Taiwan Futures Exchange; and analyze the causality between returns and volume series, which are transformed into Markov chain, with Granger’s causal tests. I analyze the data with two different time category, trading time and calendar time. In our research we find out that Taiwan futures market has a bi-directional causality between price and volume in trading time analysis, as to the calendar time analysis, only price to volume unidirectional causality exists. Unlike the unidirectional causal relation that Ghysels, Gourieroux, and Jasiak (1998) observed in French security market.

本研究針對七個國家包括：美國、加拿大、英國、法國、日本、香港、與澳洲。檢驗各國主成分為REITs商品在內的不動產證券指數，對於該國的消費者物價指數與國際原油價格是否具有正向的通貨膨脹避險效果。並比較各國的普通股價指數對該國的消費者物價指數與國際原油價格的通貨膨脹避險效果。本研究首先檢驗各國不動產證券指數/普通股價指數之月增率與消費者物價指數/原油價格之月增率之間是否具有正相關性。並將消費者物價指數/國際原油價格之月增率以HP濾波分解成永久性部分與暫時性部分，以迴歸估計消費者物價指數/國際原油價格之月增率的永久性與暫時性部分對於不動產證券指數/普通股價指數之月增率是否有正向的解釋能力。並以Granger因果關係檢定通貨膨脹像消費者物價指數或原油價格的月增率是否會Granger影響不動產價格的月增率。最後在進行單根檢定確認各數列皆為I(1)數列之後，檢驗不動產證券指數/普通股價指數與消費者物價指數/國際原油價格是否存在共整合關係，亦即代表是否具有長期的均衡狀態。 結果發現，幾乎所有國家不動產證券指數的月增率不管是對物價指數的月增率或原油價格的月增率的相關係數大多為無相關，在美國、加拿大、與澳洲甚至有些微的負相關，沒有支持通貨膨脹避險的證據。而在迴歸分析的結果，在加拿大、英國、法國，與日本，物價指數月增率的永久性部分對不動產證券指數月增率有負向影響；在美國與香港則是物價指數月增率的暫時性部分對不動產證券指數月增率有負向影響。至於原油價格月增率的暫時性部分則在美國、法國、與澳洲找到對不動產證券指數存在負向影響的證據。其他國家則無法找到支持物價指數月增率或原油價格月增率的永久性或暫時性部分對不動產證券指數月增率具有正向影響。此外Grnager因果關係檢定中，只有美國的消費者物價指數月增率Granger影響不動產證券指數月增率。 而在假設無時間趨勢的共整合檢定之中，所有國家皆有顯著證據支持不動產證券指數與該國物價指數存在共整合關係，但若假設具有時間趨勢，只有加拿大，英國，日本與香港具顯著證據支持共整合關係的存在。而不動產證券指數與原油價格的共整合關係，不論有無時間趨勢，只有在加拿大、日本與澳洲這三個國家找到共整合關係存在的證據。 而普通股股價指數與消費者物價指數或原油價格實證結果顯示，相關係數檢定與不動產證券指數檢定結果相似，大多為無相關；只有美國、法國、與澳洲有些微負相關存在。迴歸分析中，物價指數月增率的永久性部分在加拿大、法國、與日本對普通股價指數月增率有負向影響；暫時性部分則在美國與澳洲對普通股價指數月增率有負向影響。原油價格月增率的暫時性部分在美國與法國對普通股股價指數存在負向影響的證據。而Grnager因果關係檢定中，在較多國家找到顯著證據支持原油價格月增率Granger影響不動產證券指數月增率。共整合檢定中，若不考慮時間趨勢，所有國家的股價指數均對物價指數存在共整合關係，但若考慮時間趨勢，則只有日本與香港有共整合現象；至於股價指數與原油價格的共整合檢定，不論有無時間趨勢，只有在日本、香港與澳洲找到些微共整合關係存在的證據。 整體而言，並無顯著證據存在支持不動產證券指數的報酬會隨著通貨膨脹的增加而增加；或是通貨膨脹的增加可以解釋不動產證券指數的報酬。然而不動產證券指數與消費者物價指數之間的確存在共整合關係，代表長期之下，兩者會往均衡方向調整，具有部分通貨膨脹避險能力。而普通股價指數與不動產證券指數的結果相同，但在檢設具有時間趨勢的共整合檢定上，不動產證券指數在四個國家存在共整合關係，普通股價指數則只有在兩個國家找到共整合存在的證據。不動產證券指數長期而言較普通股價指數具有較好的通貨膨脹避險效果。

This thesis studies bubbles in the U.S. stock market and how they are influenced by monetary policy pursued by the FED. Using Kalman filtering, the log-real price of S&P 500 is decomposed into a market-fundamentals component and a bubble component. The market-fundamentals component depends on the expected future dividends and the required rate of return, while the bubble component is treated as an unobserved state vector in the state-space model. The results suggest that, mainly in recent decades, the bubble has accounted for a substantial portion of S&P 500 price dynamics and might have played a significant role during major bull and bear markets. The innovation of this thesis is that it goes one step further and investigates the effects of monetary policy on both estimated components of S&P 500. For this purpose, the block- restriction VAR model is employed. The findings indicate that the decreasing interest rates have a significant short-term positive effect on the market-fundamentals component but not on the bubble. On the other hand, quantitative easing seems to have a positive effect on the bubble but not on the market-fundamentals component. Finally, the results suggest that the FED has not been successful at distinguishing between stock price movements due to fundamentals or the price misalignment.

The aim of this thesis is to verify and analyse presumed relations between selected macro-fundamentals, namely USD exchange rate, production index, interbank offered rate, inflation, money supply and two exogenous indices ( Standard & Poor's 500 and EURO STOXX 50), and CEE (Austria, Czech Republic, Poland, Hungary) or SEE (Bulgaria, Croatia, Slovenia, Romania) financial markets over the period from December 1995 to December 2015. In order to test the long-run cointegration relationships between studied markets and the set of macroeconomic variables, the Engle-Granger and Johansen tests are applied. The vector error correction model is used to confirm the long-run equilibrium interlinkages and the results show similar trend tendencies between stock indices and some of the macro-fundamentals in Croatia, Czech Republic, Hungary, Poland and Romania. To verify the short-run causal linkages, the Granger causality test is employed. Based on retrieved findings, the efficiency of studied markets with respect to Efficient Market Theory is reviewed. Our findings reveal several pairwise short-run causal impacts between studied macroeconomic indicators and stock indices. The only indicator which does not impact any stock market is the interbank offered rate. Moreover, according to our results, all CEE&SEE stock...

In the literature there are mixed results on the link between credit and agricultural output growth. Some authors argue that credit leads to growth in agricultural output. Others view growth as one of the factors that influence credit supply, thus growth leads and credit follows. By and large, studies have not endeavoured to establish the short-run impact of agricultural credit on output. They are generally limited in establishing the long-run relationship between credit and agricultural output and thus present a research gap in this respect. This study contributes to the existing body of literature by focusing on the finance-growth nexus at sectoral level as a departure from extant literature that has focused on the macroeconomic level. Using South African data, the study investigated the causal relationship between the supply of credit and agricultural output as well as whether the two are cointegrated and have a short-run relationship. The study found that bank credit and agricultural output are cointegrated. Using the error correction model (ECM), the results showed that, in the short-run, bank credit has a negative impact on agricultural output, reflecting the uncertainties of institutional credit in South Africa. However, the ECM coefficient shows that the supply of agricultural credit rapidly adjusts to short-term disturbances, indicating that there is no room for tardiness in the agricultural sector. The absence of institutional credit will immediately be replaced by availability of other credit facilities from non-institutional sources. Conventional Granger causality tests show unidirectional causality from (1) bank credit to agricultural output growth, (2) agricultural output to capital formation, (3) agricultural output to labour, (4) capital formation to credit, and (5) capital formation to labour, and a bi-directional causality between credit and labour. Noteworthy and significant for South Africa is that for the agricultural sector, the direction of causality is from finance to growth, in other words supply-leading, whereas at the macroeconomic level, the direction of causality is from economic growth to finance, in other words, demand-leading. Applying a structural equation modelling approach to survey data of smallholder farmers, the positive relationship between bank credit and agricultural output observed from analysis of secondary data was confirmed. / Business Management / D. Com. (Business Management)

Der technologische Fortschritt hat in jüngster Zeit zu einer großen Zahl von Zeitreihenmessdaten über komplexe dynamische Systeme wie das Klimasystem, das Gehirn oder das globale ökonomische System geführt. Beispielsweise treten im Klimasystem Prozesse wie El Nino-Southern Oscillation (ENSO) mit dem indischen Monsun auf komplexe Art und Weise durch Telekonnektionen und Rückkopplungen in Wechselwirkung miteinander. Die Analyse der Messdaten zur Rekonstruktion der diesen Wechselwirkungen zugrunde liegenden kausalen Mechanismen ist eine Möglichkeit komplexe Systeme zu verstehen, insbesondere angesichts der unendlich-dimensionalen Komplexität der physikalischen Prozesse. Diese Dissertation verfolgt zwei Hauptfragen: (i) Wie können, ausgehend von multivariaten Zeitreihen, kausale Wechselwirkungen praktisch detektiert werden? (ii) Wie kann die Stärke kausaler Wechselwirkungen zwischen mehreren Prozessen in klar interpretierbarer Weise quantifiziert werden? Im ersten Teil der Arbeit werden die Theorie zur Detektion und Quantifikation nichtlinearer kausaler Wechselwirkungen (weiter-)entwickelt und wichtige Aspekte der Schätztheorie untersucht. Zur Quantifikation kausaler Wechselwirkungen wird ein physikalisch motivierter, informationstheoretischer Ansatz vorgeschlagen, umfangreich numerisch untersucht und durch analytische Resultate untermauert. Im zweiten Teil der Arbeit werden die entwickelten Methoden angewandt, um Hypothesen über kausale Wechselwirkungen in Klimadaten der vergangenen hundert Jahre zu testen und zu generieren. In einem zweiten, eher explorativen Schritt wird ein globaler Luftdruck-Datensatz analysiert, um wichtige treibende Prozesse in der Atmosphäre zu identifizieren. Abschließend wird aufgezeigt, wie die Quantifizierung von Wechselwirkungen Aufschluss über mögliche qualitative Veränderungen in der Klimadynamik (Kipppunkte) geben kann und wie kausal treibende Prozesse zur optimalen Vorhersage von Zeitreihen genutzt werden können. / Today''s scientific world produces a vastly growing and technology-driven abundance of time series data of such complex dynamical systems as the Earth''s climate, the brain, or the global economy. In the climate system multiple processes (e.g., El Nino-Southern Oscillation (ENSO) or the Indian Monsoon) interact in a complex, intertwined way involving teleconnections and feedback loops. Using the data to reconstruct the causal mechanisms underlying these interactions is one way to better understand such complex systems, especially given the infinite-dimensional complexity of the underlying physical equations. In this thesis, two main research questions are addressed: (i) How can general causal interactions be practically detected from multivariate time series? (ii) How can the strength of causal interactions between multiple processes be quantified in a well-interpretable way? In the first part of this thesis, the theory of detecting and quantifying general (linear and nonlinear) causal interactions is developed alongside with the important practical issues of estimation. To quantify causal interactions, a physically motivated, information-theoretic formalism is introduced. The formalism is extensively tested numerically and substantiated by rigorous mathematical results. In the second part of this thesis, the novel methods are applied to test and generate hypotheses on causal interactions in climate time series covering the 20th century up to the present. The results yield insights on an understanding of the Walker circulation and teleconnections of the ENSO system, for example with the Indian Monsoon. Further, in an exploratory way, a global surface pressure dataset is analyzed to identify key processes that drive and govern interactions in the global atmosphere. Finally, it is shown how quantifying interactions can be used to determine possible structural changes, termed tipping points, and as optimal predictors, here applied to the prediction of ENSO.

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.

本文使用 1981 年 1 月 5 日至 1997 年 5 月 31 日台灣加權股價指數以及交易股數的資料探討台灣股市的時間序列特性，並且針對政府對股市的干預政策檢定政策干預的有效性。本文採用的實證方法包含 Augmented Dickey-Fuller(ADF)單根檢定，Perron 結構性改變檢定， ARCH 效果檢定，干預分析(Intervention Analysis)以及 Granger 因果關係檢定。實證檢定的結果如下： 1、在單根檢定方面，股價指數、交易股數和股價指數變異數三個時間序列都是一階穩定序列。 2、在 Parron 結構性改變檢定方面，股價指數、交易股數和股價指數變異數三個時間序列在 1990 年 5 月到 10 月之間曾經發生明顯的結構性改變。 3、在 ARCH 效果檢定方面，股價指數和交易股數二個時間序列的殘差項都有 ARCH(1)效果存在，而股價指數變異數的殘差項不存在 ARCH(1)效果。 4、在干預分析方面，穩定基金對股價指數的干預效果不顯著。 在漲跌幅限制方面，漲跌幅限制的變動對股價指數、交易股數及股價指數變異數的干預效果都不明顯。 在證卷交易稅稅率改變的干預分析方面，證卷交易稅稅率改變對交易股數和股價指數變異數沒有影響，但是證交稅稅率變動和股價指數呈現正向的關係。 5、在 Granger 因果關係檢定方面，本研究發現漲跌幅限制改變和股價指數漲跌二者互為因果，但是股價指數對漲跌幅的影響較大。 在證卷交易稅稅率改變與股市的因果關係方面，本研究發現股價指數的漲跌是證交稅稅率改變之因，顯示主管機關的證交稅稅率政策是受股市的市場狀況所左右。 / In this paper, I examine the effectiveness of official intervention in Taiwan's equity market. I consider the security transaction tax, price limit and stabilization funds as examples. The nonstationarity and structural changes of equity index time-series process were first detected and detrended. The Autoregressive Conditional Heteroskedasticity (ARCH) model is employed to examine the intervention effectiveness, since it allows for a formal test of changes in the index mean level, index conditional variance or both, in response to the changes of security transaction tax and price limit. The results implies that policy authority adjusted security transaction tax and price limit in accordance to the change of equity index level. I also find that the imposition of security transaction tax and price limit have no significant effect on reducing the equity index volatility.

由於住宅價格變動毫無預警制度，人民往往憑著個人主觀的判斷而決定何時購屋或售屋，而此種主觀判斷住宅市場利多及利空的觀念，對住宅市場的供需會產生失衡現象，因此是否可從經濟面的訊息找到住宅價格變動的答案，使住宅價格在尚未變動前，政府即已掌握資訊，提前做好穩定住宅價格的因應對策，使民眾依其需要而購屋，則是本研究之主要目的。 　　本研究從文獻中整理出影響住宅價格變動的七個總體經濟變數，這些總體經濟變數包含工資、物價、所得、貨幣供給額、股價、匯率及利率等，並利用向量自我迴歸模式(VAR)進行實證，以便較客觀的獲得變數間的落後期數及暸解變數間雙向、單向及領先、同步、落後情形，且進一步探討住宅價格與每一個總體經濟變數間影響程度大小及影響情形，以釐清各變數之間的關係。 　　本研究利用VAR模型進行住宅價格與總體經濟變數關係的研究，經由實證，得到下列的結論： 　　一、實證結果方面 　　本研究之實證主要有因果關係檢定與分析、變異數分解之分析及衝擊反應之分析三方面，其實證結果如下所述。 　　（一）因果關係檢定與分析 　　由因果關係檢定與分析中，得到股價、物價、匯率、貨幣供給額及利率均能做為住宅價格變動的領先指標。 　　（二）變異數分解之分析 　　由住宅價格之變異數分解中，得知住宅價格自身的解釋程度僅占三分之一，另三分之二被其他的總體經濟變數所解釋，顯示住宅價格受總體經濟變數的影響相當大；而從其他總體經濟變數之變異數分解中，得知住宅價格變動會干擾到總體經濟變數，而使總體經濟變數受干擾而變動變動。 　　（三）衝擊反應之分析 　　從總體經濟變數對住宅價格的衝擊反應分析圖中可以明顯看出除工資外，其餘總體經濟變數變動對住宅價格造成的衝擊均相當明顯，但匯率及利率對住宅價格的衝擊是負向的。 　　住宅價格對所得、股價、匯率及利率的衝擊相當明顯，而其對匯率的衝擊是負向。 　　二、政策應用方面 政府的決策過程中常會有時間落後的現象，而本研究實證的目的則是要使政府能事先掌握住宅價格的變動，並提前做好穩定住宅價格的因應對策，減少政府決策過程的時間落後現象，而實證結果應用至政策方面的內容則由以下說明之。 　　（一）藉由因果關係檢定與分析的實證內容，可以縮短政府對住宅價格不合理變動問題認定落後的時間。 　　（二）從變異數分解之分析的實證內容中，可以使決策者在解決住宅價格問題時，將行動落後的時間減少。 　　（三）由衝擊反應之分析中，可以使政府在執行穩定住宅價格政策時，將衝擊落後的時間縮小。 / Since there is no alarm system in the change of housing prices, people often decide when to buy or when to sell based on personal and subjective judgement. Such concept to judge subjectively whether the housing market is bull or bear will cause unequilibrium in the supply and demend of the housing market. There it is possible to find out the answers to the change of housing prices from economic side so that the government can have enough information and can be prepared in the reaction to stabilizing the housing prices, and so that the public can buy house according to their needs is the main purpose of this project. 　　Seven variables in macroeconomics influencing the change of housing prices have been taken from reative literature, including wage, commodity price, income, money supply, stock price, exchange rate, and interest rate. VAR has been employed to verify so that the more objective lagging period among variable can be known, and the bi-directional, uni-directional, leading, contemporaneous, and lagging situation among variables can be understood. Furthermore, the degree and the status of influence of each macroeconomic variable to the housing price will be investigated to clarify the relations among the variables. 　　The present project investigate the relations between housing price and macroeconomic variables. We have the following findings: 　　I、In Empirical Study: 　　The empirical study in this project includes causal relation test and analysis, the analysis of variable decompositon, and the analysis of impact response. The results are shown in the following: 　　(I) Causality Test and Analysis 　　In the causality test and analysis, we find out that stock price, commodity price, exchange rate, money supply and interest rate all can be the leading indicators in the change of housing prices. 　　(II) The Analysis of Variable Decomposition 　　It is learned from the variable decomposition of housing prices that housing price can only explain one third of the cause in its change, the other two thirds are explained by other macroeconomic variables. It shows that housing prices are subject to the influence of macroeconomic variables greatly. 　　From the variable decomposition of other macroeconomic variables, we know that the change in housing prices will affect macroeconomic variables so that the macroeconomic variables will change. 　　(III) The Analysis of Impact Response 　　It can be obviously seen from the analysis figure of the impact response of the macroeconomics to housing prices, all macroeconomic variables will cause obvious impact to housing prices expect for wage. However, both exchange rate and interest rate have negative impact to housing prices. 　　Housing prices' impact to income, stock prices, exchange rate and interest rate is quite obvious, among which, the impact to exchange rate is negative. 　　II、Policy Application 　　It is a common phenomenon that there often will be lagging in time in government's decision making. The purise of the empirical study in this project is to let the government to know in advance the change of housing prices and to let the government to know in advance the change of housing prices and to let the government be prepared in the reaction of stabilizing the housing prices to minimize the lagging in the decision making process. The contents of application of the empirical study to policy are explained in the following: 　　(I) With the empirical results of the change of the causality test and analysis, the time for the government to recognize the unreasonable changes in housing prices can be shortened. 　　(II) With the empirical results of the analysis of variable decomposition, the decision makers' lagging in the action responding to housing pricescan be minimized. 　　(III) With the analysis in impact response, the lagging in impact will be minimized when the government executing her housing price stabilizing policy.

本文利用晚近發展出來的單根檢定法以及共積檢定法，實証分析美、日兩國二次大戰以後企業購併與總體經濟變數間之關係。其實証方法與實証結果如下：運用ADF 檢定方法對購併、股價、國民生產毛額、利率，作單根檢定，發現美日兩國之購併、股價與國民生產毛額呈一階差分恆定狀態。 此外，本文應用Engle and Granger(1987) 的共積模型分析，將同樣為一 階差分恆定的變數做共積檢定，發現美日兩國之購併與股價、國民生產之間，皆具有長期共同移動的趨勢，因此可以建立一包含長、短期關係之誤差修正模型。本文之實証結果顯示：美國的企業購併與股價水準有正向且顯著之長期穩定關係，而與國民生產毛額則有負向且顯著的長期穩定關係；日本的企業購併與股價及國民生產毛額也有長期穩定之關係，惟影響方向與美國相反。另外，因果關係檢定結果顯示，美國之股價與利率對購併呈單向因果關係，而日本之股價與購併則呈雙向因果關係。由這些實証結果可知，購併風潮之形成，實肇因於總體經濟之波動，而不同國家之企業，由於法令規章、經濟結構、社會制度之不同，因而會有不同之反應。