歐元的問世，代表的是從1970年代固定匯率被打破以來，世界金融體系最大一次的變革，其對全球之金融及社會文化有很深遠的意義；因此，有關美國與歐元區間之匯率、利率及物價關係的探討遂成為國際金融市場所關心的焦點之一；本文以Frankel (1992)所提出衡量國際間資本移動性的三種利率平價說：拋補利率平價說(Covered Interest Parity，CIP) 、無拋補利率平價說 (Uncovered Interest Parity，UIP)、實質利率平價說 (Real Interest Parity，RIP)為基礎，來檢驗此三種利率平價說是否成立。在實證方法上，本文以Dickey & Fuller (1979,1981)之ADF單根檢定來確定變數之數列特性，再採Johansen (1988)之最大概似估計法，對CIP、UIP與RIP進行實證分析。實證結果發現，於1999 年 1 月至 2004 年 7 月期間，美國與歐元區間 CIP 與 UIP 同時成立，表示當兩國資產報酬率有差異時，可以經由國際間資本的移動，使得報酬率最後有趨於相等的傾向；並且接受遠期匯率為未來即期匯率的不偏估計值之虛無假設，顯示歐元與美元間外匯市場具有效率性。另外，本文之實證結果並不支持 RIP 的成立，其有可能歐元區與美國在編制物價指數時，所使用的物價項目和比重情況不同而異，因此難以表示出公正之匯價；再者由於現實之貨幣、商品市場之不完全，與人民不一定能完全預期及存在貨幣幻覺等許許多多未考慮因素下，故在諸多驗證 RIP之文獻中，亦大多顯示無法找到其均衡之平價關係。 / The emergence of Eurodollar exemplified a significant reformation in the world financial system since the fixed rate had been broken in 1970, which brings far-reaching significance to the global finance and social culture. Therefore some discussions on exchange rate, interest rate and price relationship in the range of US Dollar and Eurodollar are one of focuses the international financial market concerns; On the basis of the three kinds of interest rate parity Frankel brought forward (1992) including Covered Interest Parity (CIP), Uncovered Interest Parity (UIP) and Real Interest Parity (RIP), this research mainly proves their feasibility. For the empirical methods, the Dickey & Fuller (1979, 1981)’s ADF unit root test was used to confirm the characteristics of variable series in this research; additionally, Johansen’s maximum likelihood method (1988) was adopted to do the empirical analysis on CIP, UIP and RIP. Based on the empirical results, we found out that the CIP and UIP are tenable simultaneously in the range of tenable US Dollar and Eurodollar from 1999 January to 2004 July. That means when return on asserts between two counties has some differences, it would become towards equality lastly on the basis of international capital mobility. And the null hypothesis that the forward rate is an unbiased predictor of the future spot rate can be employed, revealing the foreign exchange market in the range of Eurodollar and US Dollar has certain efficiency. Additionally, The empirical results of this research do not support the RIP, because it would vary with different prices and proportion used while making the price index in the range of Eurodollar and US Dollar, and cannot present equitable exchange rate; furthermore, because of imperfect current currency and commodity markets, and many unconsidered factors such as people’ incompletely anticipation and money illusion, most researches for validating RIP fail to find out its balanced parity relation.

選舉事件在台灣一直是屬於重大事件，民眾對於選舉事務都非常關心。根據童振源等人(2009)和Forsythe, Rietz and Ross(1999)，透過預測市場的機制來預測選舉結果非常準確，所以近年來預測市場也變得越來越熱門，新聞媒體也開始大幅報導未來事件交易所的預測結果。本論文將透過實證的方式探討除了價格之外，加入與未平倉相關的資訊是否能夠幫助我們更有效地預測選舉結果，並以此建議未來事件交易所揭露網站內的期貨未平倉合約量這項資訊，以提供交易人參考。 本論文使用資料為未來事件交易所中關於2008年總統選舉、立委選舉以及2010年五都市長選舉的資料，資料期間皆為各選舉的最後兩個交易日的資料，採用的變數有最後交易日的合約加權平均價格、最後交易日的合約未平倉量、最後交易日的合約成交量和最後交易日之價格漲跌及未平倉量增減的相乘項，並利用羅吉斯迴歸來幫助預測分析。 研究結果顯示：(一)與過去的研究結果相符合，未來事件交易所中選舉期貨合約的價格能有效幫助預測選舉的結果；(二)未平倉量和成交量均無法幫助預測選舉結果，這可能是由於未來事件交易所使用虛擬貨幣進行交易以及保證金制度，使得部分交易人在交易成交後不再關注自己的部位或是損益所導致；(三)利用最後交易日價格漲跌及未平倉量增減所得到的相乘項對於預測選情有顯著的幫助，當相乘項越大的時候，候選人當選的機率也隨之越小。 一般期貨交易中，透過未平倉合約量這項資訊可幫助交易人得到更多的資訊。而未來事件交易所的選舉期貨合約之未平倉量雖然無法提供額外的資訊，但是仍然建議可以將這項資訊揭露以供交易人參考。此外，相乘項在預測選情時能提供顯著的幫助，因此在交易上或是預測上都可以參考這項資訊以做出更佳的判斷。

本文為探討天津市政府所轄各區縣之地方效率，並找出影響該地方效率之因素為何，首先針對有關天津政府效率之評估指標、財政分權程度之衡量及天津政府效率相關政策之文獻進行回顧，同時整理天津市所轄各區縣可能影響效率相關因素之發展現況，藉以取得適當變數，接著本研究將設計實證模型並進行假設，包含各項資料蒐集與整理，在利用資料包絡分析法(DEA)加以評估獲得天津市所轄各區縣之地方政府效率值後，並以TOBIT迴歸模型衡量相關因素對其效率之影響情況。 最後，本研究發現，對於天津市政府所轄各區縣之地方政府效率影響，其中以物價上漲程度、時間趨勢變數均屬負向變數。而財政分權程度、地方政府規模、經濟發展程度、開放程度則均為正向變數。而財政分權程度、地方政府規模均非屬單調性變數，表達該變數所影響效率狀態將非必然為單向相關，當程度或規模有所變化，其影響也可能將隨之化作反向影響。另外，就天津市所轄各區縣在2008至2010年政府效率之表現，以和平、河東、河西、南開、河北、北辰、濱海新區等7區有較高之政府效率，可期未來將更有突出發展。

銀行在面對借款人以不動產申請抵押貸款時，產生對住宅擔保品估價之需求，以為債權之確保。然銀行的估價過程與一般估價最大不同，肇因於其估價前，擔保品本身已先產生一組買賣契約價格。過去研究指出，估價會嘗試以某些較易取得的價格資訊作為定錨點(anchor)，藉以調整並成為最後的價格。而我國不動產交易價格資訊不透明，契約價格往往由借款人提供的情況下，銀行內部估價人員可能因資訊不易取得、定錨效果，在擔保品的鑑估結果上受到契約價格影響，倘有心人士欲藉此獲得高額貸款、牟取不法利益，將損及銀行債權，即使採用自動估價系統降低人為影響因素，因資料來源不佳，只會產生所謂「garbage in garbage out」的結果。據此，如何分辨契約價格是否具有參考力變成為關鍵，亦為本文欲補足的研究缺口。 本文採用國內某銀行臺北市不動產擔保品8,348筆估價資料為樣本，建立以挑選契約價格是否具有參考力的機率預測模型，尋求影響能判定契約價格是否具有參考力的主要因素，並研究在最適的機率界限下，篩選出具有參考力的契約價格樣本。而研究結果所建立的模型，其預測並篩選出的契約價格樣本均較未經模型篩選者，對擔保品價格之估計有顯著提升。因此本研究所建立的契約價格篩選模型確能提升銀行估價準確性，使不動產擔保品鑑估價格的形成過程中，獲得更多可靠的參考資訊，降低人為操縱的空間，並在成交價格資訊不足的情況下，提升估價人員對契約價格的辨識能力。 / In the face of the borrower to apply for a mortgage of real estate, financial institutions have estimated the price of the collateral requirements to protect the debt claim. However, the biggest difference with the general valuation and that of financial institutions, valuation of its causes before the collateral itself has produced a first sale contract price. In the past research that one attempts to estimate the price of some greater access to information act to anchor in order to adjust and become the final price. Because financial institutions are not easy to obtain price information on real estate transactions in Taiwan, price information is often provided by the borrower. A small number of loans borrower deliberate fraud to forgery or false irrigation Contract price sale and purchase agreement in order to obtain high credit. Even with the automatic valuation system to reduce the human impact factor, due to poor data sources, it will only produce so-called "garbage in garbage out" of the results. Accordingly, how to tell whether the contract price to a reference force becomes critical, and also in this article want to complement the research gap. We adopt 8,348 estate collateral valuation data in Taipei City of a domestic bank for the sample to establish a binary logistic regression model. And we try to seek the main factors that determine whether the contract price of the reference force, and find out the optimal cutoff point, filter out of a sample of the contract price of the reference force. The results confirm the model in this paper. The selected samples of the contract price is estimated that the price of collateral significantly improved compared with those without filtering. Therefore, the model established in this study can really improve the accuracy of bank valuation. Enhance the recognition ability of the bank's internal appraisers on the contract price in the lack of transaction price information.

大眾捷運系統帶來之快捷與便利，使其成為許多都會區民眾依賴之交通工具。捷運系統對鄰近不動產交通可及性提升，所伴隨之便利性將透過資本化效果反映於其價格之上，帶動周邊不動產價格上漲，過去不論國內外關於捷運對周邊房價影響之研究，實證結果亦多支持捷運對於房價有正面影響，且該影響隨著與捷運車站距離增加而遞減。捷運房價效果的區位差異與類型差異過去雖已有研究論及，但對捷運房價效果差異與其變化趨勢未能有明確細緻描述。此外，該等研究均忽略空間相關因素，將影響其估計結果。 　　本文使用國內某金融機構2007、2008年間台北都會區內台北捷運初期路網沿線車站周邊住宅為實證對象，應用空間迴歸模型檢視捷運系統對鄰近住宅價格之影響效果。實證結果顯示，就整體樣本而言捷運對房價確有正向影響但並不如想像之大，且該影響隨區位與類型之不同確有差異。 / Many previous studies have showed that metro system has a positive impact on the property values due to its accessibility benefits and the effect should decline as distance increases. While the pattern of the change and its difference between stations located in different locations has yet not been fully discussed, most of the studies failed to allow for spatial autocorrelation over space. This research uses spatial econometrics to estimate a residential housing model that considers spatial autocorrelation. The empirical results show the difference in the price effect of metro stations between urban and suburban areas does exist. The effect tends to get stronger in certain area, the closer the property lies within to the suburban area the greater the effect is. Also, we find price gaps between different metro station categories. Generally, underground stations and transfer stations have greater positive effect on residential property values.

華人社會傳承了儒家文化思想的價值觀，但是在社會環境、政治體制及人口結構等因素的差異之下，衍生出各種文化特性的差異。本研究使用世界價值觀調查（World Values Survey，WVS）資料，比較不同社會中的華人在文化特性方面的差異，並分析文化特性及其他因素對主觀福祉（subjective well-being）的影響。 本研究採用世界價值觀調查所建立之社會價值觀（societal values），加入其他文化特徵、社會態度及個人生活觀衡量文化特性。本研究使用之計量模型為排序羅吉特迴歸（ordered logit regression）模型，分析上述變數對華人生活滿意度（life satisfaction）與快樂程度（happiness）的影響。本研究之目的在於找出影響華人主觀福祉之重要決定因素，並探討文化因素在收入與主觀福祉之間是否存在調節效果（moderating effect）。 實證結果顯示，文化會影響華人主觀福祉，並在收入與主觀福祉之間造成調節效果。而華人在各個社會中所衍生出的文化特性差異，也使得各個社會中華人主觀福祉的重要決定因素有所差異。 / Chinese societies inherited the values of Confucianism. However, these societies vary in their social environment, political system and demographic structure, thus result in differences in their cultural characteristics. This study uses the data from World Values Survey, to explore the differences among Chinese in different societies, and to analyze the determining factors of Chinese subjective well-being. In this study, the societal values established by the World Values Survey are used to represent the cultural properties. We also added other cultural traits, social attitudes and individual viewpoints for our analysis. In this study, we use ordered logit regression model to find out the important determinants of Chinese subjective well-being in different societies, and discuss whether there exists a cultural moderating effect between income and subjective well-being. Empirical results show that culture has a significant impact on subjective well-being of Chinese, and the effect of income on Chinese subjective well-being are also moderated by cultural properties. The differences between these Chinese societies also result in divergences of important determinants of Chinese subjective well-being between societies.

主要章節為：第一章是緒論，第二章是市場結構與利潤率的主要概念，第三章是台灣 製造業的市場結構與利潤率的一般觀察，第四章是台灣製造業的市場結構與利潤率的 一般關係，第五章是開放經濟下市場結構與利潤率的關係，第六章是摘要及結論。 市場結構的概念來自個體經濟學，是由完全競爭、寡占、完全壟斷的理論，來觀察經 濟體系中的市場是處於那一種結構狀態。由此探尋這些市場結構的決定因素，以及其 對廠商、產業、整個經濟體系的影響。第二章中除討論上述概念外，並介紹各國研究 的結果。 第三章中將利用六十五年工商普查資料及中華徵信所各年出版的最大民營企業統計， 台灣地區工商財務總分析；就第二章的概念，對台灣製造業作實證觀察。 第四章中將利用單一方程式的複迴歸模型，對六十五年製造業產業利潤率及廠商利潤 率，與市場結構的關係作橫斷面的分析。 第五章中將討論開放經濟下，進口競爭，對國外市場依存度，外人投資，（關稅）保 護等因素對國內市場結構的影響。並利用第四章的方法，對六十五年製造業產業利潤 率與市場結構的關係作進一步的探討。最後一章為結論。

本文主旨在研究線性回歸模式中，若殘差之變異數並非一致時，如何作估計？同時如 何檢定母體是否具有不等變異性，其結構如下： 第一章：緒論。 第二章：估計之一般理論。第一節–基本定義。第二節－不偏性。第三節－一致性。 第四節－有效性。 第三章: 估計。第一節－迴歸係數之估計。第二節－殘差變異之估計。 第四章：檢定。第一節–巴萊特檢定。第二節–高、肯氏（GOLDFELD–QUANDT）檢定 。第三節–葛氏（GLEJSER ）檢定。 第五章：結論。

本論文主要目地是在研究財務比率對上市公司發生下市事件之預測。我們運用歷史事件研究法和Cox迴歸模型去研究上市公司發生下市事件之原因。同時，我們也針對Cox迴歸模型和Logit模型在發現對下市事件有顯著影響的財務比率作比較。 / This study applies the event history analysis and the Cox regression model to examine the causes of firm delisting, and also compares the performance of the Cox regression model with that of the logit model in detecting factors that have a statistically significant impact on the delisting event. The empirical results show that the hazard rate of firm delisting increases with the ratio of current liabilities to current assets, a binary variable indicating if the total liabilities of a firm is greater than its total assets, and a binary variable indicating if the net income of a firm was negative for the last two quarters, while the hazard rate of firm delisting decreases with increases in the firm size and the ratio of funds provided by operations to total liabilities.

本文旨在檢定台電公司現行季節電價月份劃分之合理性，並探討影響用戶別售電量與電費收入之經濟因素。為達成此目的，本文先就負載觀點與成本觀點進行群集分析，以檢定季節電價是否具統計意義之正當性；其次建立經濟計量模型，分別採用戶別之總售電量與總電費收入做為被解釋變數，運用民國88年1月至民國91年12月之月資料進行實證分析。本文建立之經濟模型有二，分別為時間序列以及複迴歸方程式模型。經檢定分析後，本文就各實證參數之經濟意涵加以闡示，最後並提出結論以及未來研究之方向。 本文透過月資料之群集分析，顯示夏月相對於非夏月之群集差異與台電公司現行季節電價夏月與非夏月之月份相一致，證實台電公司季節電價月份劃分之合理性。其次，透過ARIMA時間序列建立之短期電力需求預測模型，經實證結果顯示：電燈與電力用戶別之售電量均逐年增加，預測民國93年1月至民國99年12月，電燈用戶之年售電量平均成長率為3.33%、電力用戶為3.23%。再者，利用複迴歸模型進行實證分析之結果發現：(一)影響售電量之主要變數為溫度。惟因電燈用戶每隔兩月抄表一次，與電力用戶按月抄表之作業方式不同，故電燈用戶每月售電量係受前期(月)溫度影響，而電力用戶則受當期(月)溫度影響。(二)各用戶別之總電費收入與售電量有明顯相關，且經估算出各月售電量之電費收入彈性顯示：電燈用戶約為0.5，電力用戶約為1。由於總電費收入為總售電量與平均電價之乘積，故電燈用戶之電費收入增加1% 時，其售電量僅增加0.5%，顯示總電費的收入增加係有部分來自於平均電價的提高；換言之，就電燈用戶別而言，其電費收入增減變化之百分比除了會受到售電量增減幅度之影響外，亦反映了平均電價變化的情形。同理，對電力用戶來說，其各月售電量之電費收入彈性接近於1，表示電費收入變化1% 時，售電量亦增加1%，即電費收入之增減變化比例主要受到售電量之同向等幅變化所影響。 至於各用戶別之電費收入方面，電燈與電力兩類用戶自民國88年初至91年底四年期間均有逐年增加之趨勢，惟電力用戶之年增加幅度有隨時間遞減之現象，且歷年大抵以7-10月份較高，2月份最低。此外，影響用戶別電費收入之解釋變數中，各類用戶之售電量最為顯著，其參數值係隱示每增加一度售電量對其電費收入之影響。其中，電燈用戶之估計參數值為2.69，而電力用戶則為1.35。再者，由其電費收入之售電量彈性係數可以發現：電燈用戶約為1.2，電力用戶約為0.7，顯示電燈用戶總售電量增加1%時，總電費收入增加的幅度大於1%，而電力用戶則相反。推估電力用戶此一彈性係數較電燈用戶低之原因在於：電力用戶與電燈用戶之電價結構不同，前者係採需量電費與能量電費之兩部電價制，而後者僅包含流動電費之一部電價。最後，實證結果亦顯示電力系統之尖峰負載與負載率會影響電費收入，惟其影響幅度不大。 / A Study on Customer-by-Category Energy Sales and Power Sales Revenue Model: The Case of Taiwan Power Company Abstract The main purposes of this study are to examine the rationality of the seasonal pricing scheme defined by summer and non-summer months and to identify economic factors influencing customer-by-category energy sales and power sales revenue, utilizing the data of Taiwan Power Company (Taipower) as an empirical case. In order to achieve this objective, the cluster analysis from the perspective of load pattern and cost pattern are examined respectively to see if the seasonal pricing scheme has statistical meaning in its pattern differences in terms of summer vs. non-summer season. Second, two economic models including time-series analysis and multiple regression equations are formulated for the empirical case study. The subtotal energy sales and the subtotal power sales revenue by different type of customer categories, i.e. lighting and industrial customers, are set to be the explained variables. Data from January 1999 to December 2002 are collected for modeling simulation tests. The economic meanings and policy implications of the modeling results are elaborated on. And conclusions with directions for further research are presented. Through the cluster analysis utilizing monthly data within the time frame mentioned above, empirical research results on the grouping cluster of summer vs. non-summer months shows a consistent trend with those defined by Taipower’s present seasonal pricing scheme. Second, the empirical results of ARIMA time-series model show that the forecasted energy sales of both lighting and industrial customers will be gradually increasing through January 2004 to December 2010, and the average annual growth rate of energy sales for the lighting customer is 3.33%, and for the industrial customer is 3.23%. On the other hand, the empirical research results through the multiple regression equations show that the main factor affecting the energy sales is temperature. Due to the different time schedules for reading electricity meters between the lighting customer and the industrial customer, i.e. the time interval for reading the meter of lighting customers is every two months and for industrial customers is every month, the monthly energy sales of the lighting customer are directly related to the temperature of the previous month, while the monthly sales of the industrial customer are directly related to the temperature of the present month. In addition, for each type of customers, there is an obvious correlation between the total power sales revenue and the total energy sales. Furthermore, the estimated elasticity of the total power sales revenue versus total energy sales is about 0.5 for the lighting customer, and about 1 for the industrial customer. Since the total power sales revenue is the product of total energy sales times the average electricity price, when the total power sales revenue increases 1% with the total energy sales only increases 0.5%, it implies that the increase of total power sales revenue not just only comes from the increase of energy sales, but also partially affected by the increase of average electricity price. Similarly, for the industrial customer, when the elasticity of their monthly total power sales revenue versus total energy sales is close to 1, it implies that when the total power sales revenue increases 1%, the total energy sales also increase about 1%. In other words, the change of percentage of the total power sales revenue is mostly attributed to the variation of total energy sales, not because of the average electricity price. As for the simulation results of the total power sales revenue, those of the lighting and industrial customers are both gradually increasing between the years 1999 to 2002. However, the increasing pace of the industrial customer tended to slow down. Moreover, both types of the customers possess a similar trend that their total power sales are higher in statistical meaning for the months from July to October, and lower for February, for those above three years. Besides, among the variables affecting each type of customer’s power sales revenue, the energy sales is the most significant one, its parameter implies that whenever the total energy sales increases one unit, i.e. one kwh, it would affect the total power sales revenue by that amount equivalent to the figure of the parameter. According to the empirical results, the estimated parameter mentioned-above of the lighting customer is 2.69, and 1.35 of the industrial customer respectively. That implies one kwh unit price for the lighting customer is 2.69 N.T. dollars, and 1.35 N.T. dollars for the industrial customer. Moreover, from the elasticity of the total energy sales versus the total power sales revenue, it shows that the elasticity of the lighting customer is around 1.2, and the elasticity of the industrial customer is around 0.7. The underlining reason of the difference between the two figures could be that the electricity pricing structure of the lighting and industrial customers are quite different. The industrial customer is charged by two-part tariff including a demand charge for the capacity use and an energy charge for the kwh use. While the lighting customer is charged simply by a single rate, i.e. the energy use. Finally, the empirical results also show that the magnitude of the peak load and the load factor of the whole electricity system also affect the total power sales revenue of each type of the customer, though with much less effect.