近年來，全球氣候變遷問題已嚴重影響人類生活，而世界各國也逐漸意識到已開發國家和開發中國家必須共同合作以解決此問題。京都議定書中的清潔發展機制 (CDM) 即是讓已開發國家與開發中國家共同實踐減量目標的一種彈性減量機制，然而過去文獻對於其減排成效的看法並不一致。有鑒於此，本文以參與CDM計畫的20個開發中國家和16個已開發國家為研究對象，探討CDM計畫對其2003至2008年二氧化碳減量之影響。根據兩階段最小平方法之固定效果模型的實證結果顯示，CDM計畫能減少開發中國家的二氧化碳排放量，但經認證的排放減量額度 (CERs) 有被過量核發之現象；另一方面，CDM計畫對已開發國家的減排效果則無影響。 / In recent years, global climate change problem has affected humans’ life badly. Therefore, it is gradually realized that the developed countries and developing countries have to cooperate to solve the problem. Clean Development Mechanism (CDM) is one of the flexibility mechanisms defined in the Kyoto Protocol, and it allows the developed countries, in cooperation with developing countries, to fulfill the emission-reduction targets. However, the emissions abatement effects of CDM in the literatures are diverse. Accordingly, this paper uses 20 developed countries and 16 developing countries as an empirical case to examine the impact of CDM on carbon dioxide emissions abatement from 2003 to 2008. According to fixed effects two-stage least squares, CDM projects reduced the carbon dioxide emissions of developing countries, but the certified emissions reductions (CERs) were excessively issued. On the other hand, CDM projects didn’t have an impact of emissions abatement on developed countries.

近幾年針對資本結構的研究發現,在比較先進國家的企業確實有逐步調整回自己的最適資本結構的動作。本論文進一步將研究擴大到開發中國家，發現研究中的32個國家，不論是已開發或是發開中國家的企業，確實都有維持最適資本結構的動作。當資本結構偏離時，企業會逐步地調整回其最適值，然而每個國家調整回最適資本結構的調整速度則存在著差異性。本論文進一步利用國家間法律、會計、制度以及規範面的差異下去分析，發現國家發展程度以及會計制度是影響調整回最適資本結構的速度快慢的重要因子。此外，本論文亦探討融資順位理論及擇時理論的影響，發現加入融資順位理論因子後，調整速度會有相當程度的減緩，而減緩的幅度，則與國家發展程度、法律保護、公司稅率以及會計制度有顯著的關連性。 / Recent empirical literature provides evidences that firms in most developed countries do partially adjust toward their target capital structure. In this paper, we show that no only firms in developed countries, but also those in emerging countries gradually move back to their long-run equilibrium when they are away from it. But the adjustment speeds vary from country to country. We study the determinants of adjustment speeds around the world by focusing on differences in laws and regulations across countries. Our evidences show that firms in countries with common-law tradition, stronger shareholder right, or more completed accounting standards tend to move back to their optimal leverage quicker. Furthermore, we add two variables related to other two main capital structures (pecking order and market timing) in our analysis to capture their effects. Both theories add some information in explaining capital structure, but the impacts differ when applying different leverage measures. When we define leverage ratio as long-term debts dividend by net assets, we observe that pecking order factor lowers the adjustment speed a lot. And the magnitude of decrease on adjustment speed is significantly correlated with market condition, law enforcement, corporate tax rate and accounting standard. More developed countries and countries with stronger law enforcement, higher corporate tax rate, or more completed accounting standards tend to have less reduction on adjustment speed when including pecking order factor, because they have less information asymmetries.

迴歸模式的變數選取是很重要的課題，Tibshirani於1996年提出最小絕對壓縮挑選機制（Least Absolute Shrinkage and Selection Operator；簡稱Lasso），主要特色是能在估計的過程中自動完成變數選取。但因為Lasso本身並沒有牽扯到統計推論的層面，因此2014年時Lockhart et al.所提出的Lasso顯著性檢定是重要的突破。由於Lasso顯著性檢定的建構過程與傳統向前逐步迴歸相近，本研究接續Lockhart et al.(2014)對兩種變數選取方法的比較，提出以Bootstrap來改良傳統向前逐步迴歸；最後並比較Lasso、Lasso顯著性檢定、傳統向前逐步迴歸、以AIC決定變數組合的向前逐步迴歸，以及以Bootstrap改良的向前逐步迴歸等五種方法變數選取之效果。最後發現Lasso顯著性檢定雖然不容易犯型一錯誤，選取變數時卻過於保守；而以Bootstrap改良的向前逐步迴歸跟Lasso顯著性檢定一樣不容易犯型一錯誤，而選取變數上又比起Lasso顯著性檢定更大膽，因此可算是理想的方法改良結果。 / Variable selection of a regression model is an essential topic. In 1996, Tibshirani proposed a method called Lasso (Least Absolute Shrinkage and Selection Operator), which completes the matter of selecting variable set while estimating the parameters. However, the original version of Lasso does not provide a way for making inference. Therefore, the significance test for lasso proposed by Lockhart et al. in 2014 is an important breakthrough. Based on the similarity of construction of statistics between Lasso significance test and forward selection method, continuing the comparisons between the two methods from Lockhart et al. (2014), we propose an improved version of forward selection method by bootstrap. And at the second half of our research, we compare the variable selection results of Lasso, Lasso significance test, forward selection, forward selection by AIC, and forward selection by bootstrap. We find that although the Type I error probability for Lasso Significance Test is small, the testing method is too conservative for including new variables. On the other hand, the Type I error probability for forward selection by bootstrap is also small, yet it is more aggressive in including new variables. Therefore, based on our simulation results, the bootstrap improving forward selection is rather an ideal variable selecting method.

本研究的主要目的在於比較「GSP融入數學教學」與「傳統講述教學」對學生學習幾何課程之成效，並探討實驗組學生經由「GSP融入數學教學」後的態度與看法，以便可以作為將來在國中階段發展GSP輔助教學之參考。 本研究採不等組前後測準實驗研究設計，以桃園縣某國中三年級兩班共67名學生為研究對象，非隨機分派一班為實驗組，進行GSP融入數學教學；另一班為控制組，進行傳統講述教學，經由Kolb學習風格量表受測，區分為「具體經驗」及「抽象概念」兩類的學生，教學實驗為期六週共十二節課，教學內容為國三第五冊幾何單元「圓」，探究不同性別與不同學習風格之學生分別接受不同教學方法之後，在數學學習態度、學習成就與學習保留上的差異，採用二因子共變數分析統計方法驗證假設，並於實驗教學後針對實驗組做「GSP使用態度調查表」以了解學生的態度與反應。檢定分析與調查結果，得到以下結論： 一、排除前測影響後，學生在數學學習態度上的表現： (一)不同教學方法分別與不同性別、不同學習風格之間沒有交互作用。 (二)不同性別、不同學習風格均無顯著差異。 (三)不同教學方法會造成顯著差異；GSP融入數學教學優於傳統講述教學。 二、排除前測影響後，學生在數學學習成就上的表現： (一)不同教學方法分別與不同性別、不同學習風格之間沒有交互作用。 (二)不同性別、不同學習風格均無顯著差異。 (三)不同教學方法會造成顯著差異；GSP融入數學教學優於傳統講述教學。 三、排除前測影響後，學生在數學學習保留上的表現： (一)不同教學方法與不同性別之間沒有交互作用，且均無顯著差異。 (二)不同教學方法與不同學習風格之間有交互作用。 (三)以GSP融入數學教學而言，不同學習風格會造成顯著差異；抽象概念的學生優於具體經驗的學生。 (四)以抽象概念風格而言，不同教學方法會造成顯著差異；GSP融入數學教學優於傳統講述教學。 四、實驗組學生使用GSP態度分析 實驗組學生在幾何單元「圓」實施「GSP融入數學教學」後，絕大多數的學生喜歡此種教學方法，並抱持著正向及肯定的學習態度。 最後根據研究結果提出具體建議，以供學校、教師及未來研究者參考。 / The main purpose of this study is to compare the effectiveness of learning geometry using new teaching method (i.e. GSP in mathematics teaching) and traditional teaching method. For the possibilities of applying GSP to junior high school math teaching in the future, this study also analyze how students learn and react toward ‘GSP in mathematics teaching’. There are two grade 9 classes with totaled 67 students in the study. One class is assigned as the experimental group (i.e. GSP in mathematics teaching). Another class, the control group, is taught by traditional narrative teaching. All student are categorized, based on Kolb Learning Style Inventory(LSI), into two types: Concrete Experience and Abstract Conceptualization. The experiment consists of 12 classes in 6 weeks. The geometry content is ‘circle’, in book V for 9th graders. The study analyzes how students with different learning styles and genders react to these two math teaching methods. The attitudes , achievements and retentions of students learning are the main interests. The hypotheses are tested using two-way ANCOVA. Students in the experimental group are further evaluated with GSP questionnaire at the end of the experiment. The conclusions are as follow: I. For the attitude of students in learning math: 1. There is no interaction between teaching method and gender and between teaching method and style. 2. There is no significant difference between different genders and between different learning styles. 3. Different teaching methods have significant difference: GSP in math teaching is much better than traditional narrative teaching. II. For the achievement of students in learning math: 1. There is no interaction between teaching method and gender and between teaching method and style. 2. There is no significant difference between different genders and between different learning styles. 3. Different teaching methods have significant difference:GSP in math teaching is much better than traditional narrative teaching. III. For the retention of students in learning math. 1. There is no interaction between teaching method and gender. In addition , there are no significant differences between teaching method and between different gender. 2. There is interaction between teaching method and learning style. 3. Learning styles have significant difference when GSP is used in math teaching. Students categorized in Abstract Conceptualization perform better than those in Concrete Experience. 4. Among those Abstract Conceptualization students from GSP in math teaching class is significantly better than those from traditional narrative teaching. IV. For the attitude of students with GSP: Most students in experimental group are fond of GSP in math teaching, and hold a positive attitude toward learning . Finally, suggestions based on this study will be provided for school authority, teachers and other researchers. Keyword: GSP, computer-assisted instruction, learning style, mathematics learning attitude, mathematics learning achievement, mathematics learning retention, ANCOVA

本研究採用門檻迴歸模型 (Threshold Autoregression Model)，試圖找出董監事等內部人之申報轉讓比率、持股比率及質押比率等門檻值，進而分析門檻值以內及以外，指標對於代理變數：融資成長率、營收成長率以及本益比與加權指數報酬率的影響程度與方向。本研究實證結果發現： 一、在申報轉讓比率方面： 當申報轉讓比率低於門檻值，存在所謂的群聚效果。當申報轉讓比率高於門檻值時，市場動能與加權指數報酬率無顯著關係，投資人於此階段進行投資決策時應該要謹慎小心。 二、在持股比率方面： 在持股比率低於門檻值時，加權指數報酬率對於前期營收成長率表現的修正幅度較大，意謂著董監事等內部人根據其對未來營收資訊掌握的優勢，反應其對營收資訊的真實性，而藉由持股轉讓的行為，使加權指數大幅度的修正。 三、在質押比率方面： 不管高於或低於門檻值，均無法利用董監事等內部人質押比率為門檻變數來分析本益比效果對加權指數報酬率的影響。造成其檢定失效的原因，可能是樣本小且模型受到極端值的影響所造成。

本文目的在探討中國與美國股票市場的共移性。利用2005 年至2010 年的資料， 建立中國股票在紐約證券交易所的美國存託憑證投資組合及美國股票相對應產 業的投資組合，並計算它們二者間在日間以及夜間的報酬。這個分析結果顯示， 中國股市和美國股市會因為不同的市場資訊和影響規模，而有一定程度的相關性。 此外，透過建立二階段潛在變數模型，在文中進一步推論出競爭性衝擊是影響兩 國間股票市場共移性的主因。然而，市場對人民幣與美元匯率、美國國庫券利率 報酬變化的衝擊有落後效果。而此結果可以為國際投資組合的風險分散提供更細 部的訊息。 / This paper investigates stock market co-movements betweenthe the U.S. and China. We construct daytime and overnight returns for a portfolio of Chinese stocks using their NYSE-traded ADRs and an industry-matched portfolio of American stocks between 2005 and 2010. The results show that Chinese stock market is linked to American stock market through dierent sources and magnitudes of shocks. The analysis, based on the two-stage latent variables regression, further indicates that the market correlations be- tween China and the U.S. mostly come from competitive shocks. However, competitive shocks of the Yuan/Dollar foreign exchange rate and Treasury bill returns have lagged eects on the markets. The classications of shocks into competitive and global ones suggest a ner information for international risk diversication.

距離期望值4至6倍標準差以外的罕見機率電流值，是當前積體電路設計品質的關鍵之一，但隨著精確度的標準提升，實務上以蒙地卡羅方法模擬電路資料，因曠日廢時愈發不可行，而過去透過參數模型外插估計或迴歸分析方法，也因變數蒐集不易、操作電壓減小使得電流值尾端估計產生偏差，上述原因使得尾端電流值估計困難。因此本文引進統計方法改善罕見機率電流值的估計：先以Box-Cox轉換觀察值為近似常態，改善尾端分配值的估計，再以加權迴歸方法估計罕見電流值，其中迴歸解釋變數為Log或Z分數轉換的經驗累積機率，而加權方法採用Down-weight加重極值樣本資訊的重要性，此外，本研究也考慮能蒐集完整變數的情況，改以電路資料作為解釋變數進行加權迴歸。另一方面，本研究也採用極值理論作為估計方法。 本文先以電腦模擬評估各方法的優劣，假設母體分配為常態、T分配、Gamma分配，以均方誤差作為衡量指標，模擬結果驗證了加權迴歸方法的可行性。而後參考模擬結果決定篩選樣本方式進行實證研究，資料來源為新竹某科技公司，實證結果顯示加權迴歸配合Box-Cox轉換能以十萬筆樣本數，準確估計左、右尾機率10^(-4) 、10^(-5)、10^(-6)、10^(-7)極端電流值。其中右尾部分的加權迴歸解釋變數採用對數轉換，而左尾部分的加權迴歸解釋變數採用Z分數轉換，估計結果較為準確，又若能蒐集電路資訊作為解釋變數，在左尾部份可以有最準確的估計結果；而篩選樣本尾端1%和整筆資料的方式對於不同方法的估計準確度各有利弊，皆可考慮。另外，1%門檻值比例的極值理論能穩定且中等程度的估計不同電壓下的電流值，且有短程估計最準的趨勢。 / To obtain the tail distribution of current beyond 4 to 6 sigma is nowadays a key issue in integrated circuit (IC) design and computer simulation is a popular tool to estimate the tail values. Since creating rare events via simulation is time-consuming, often the linear extrapolation methods (such as regression analysis) are applied to enhance efficiency. However, it is shown from past work that the tail values is likely to behave differently if the operating voltage is getting lower. In this study, a statistical method is introduced to deal with the lower voltage case. The data are evaluated via the Box-Cox (or power) transformation and see if they need to be transformed into normally distributed data, following by weighted regression to extrapolate the tail values. In specific, the independent variable is the empirical CDF with logarithm or z-score transformation, and the weight is down-weight in order to emphasize the information of extreme values observations. In addition to regression analysis, Extreme Value Theory (EVT) is also adopted in the research. The computer simulation and data sets from a famous IC manufacturer in Hsinchu are used to evaluate the proposed method, with respect to mean squared error. In computer simulation, the data are assumed to be generated from normal, student t, or Gamma distribution. For empirical data, there are 10^8 observations and tail values with probabilities 10^(-4),10^(-5),10^(-6),10^(-7) are set to be the study goal given that only 10^5 observations are available. Comparing to the traditional methods and EVT, the proposed method has the best performance in estimating the tail probabilities. If the IC current is produced from regression equation and the information of independent variables can be provided, using the weighted regression can reach the best estimation for the left-tailed rare events. Also, using EVT can also produce accurate estimates provided that the tail probabilities to be estimated and the observations available are on the similar scale, e.g., probabilities 10^(-5)~10^(-7) vs.10^5 observations.

本文以貝氏方法估計方向距離函數，加入單調性與曲度限制，同時考慮環境變數於模型中。為了凸顯考慮非意欲產出方向距離函數的優點，本文同時估計產出面射線距離函數，並與方向距離函數模型比較。實證分析資料為1970至2010年間各國總體經濟變數，分別在有無加入限制條件與環境變數的狀況下，估計兩種距離函數，從無效率值、效率分數與技術進步率等角度分析彼此間的差異。發現射線距離函數模型由於忽略非意欲產出，傾向高估生產單位的技術效率。另一方面，其係數估計值容易違反射線距離函數的先天性質，較不具參考性。而方向距離函數模型當中，有無加入限制條件與有無考慮環境變數的模型結果各不相同，其中同時加入限制條件與環境變數的模型結果最為合理。

角色失落感、社會網路疏離感以及經濟不安全感乃老人心理的主觀傾向，在物質世界 中既看不見也摸不著。其測量之不易是顯而易見的。但是，它在主導老人生活適應上 的影響力卻又不容忽視。因此。本研究旨在探討老人在角色失落感、社會綱路疏離感 以及經濟不安全感是如何的影響老人的生活適應。 分析資料是採用問卷調查方式。以台北市65歲以上的老人為受訪對象。但由於受限於 時間及經費上的限制。樣本僅有250 個。不過樣本頒於松山、土林、古亭及雙園四層 區(請參考抽樣部分)。 整個分析過程包括兩個層次：一、為使用次數分配及百分比。用來描述背景因素的主 要特性。而有助於我們對樣本的了解；二、為利用共變數結構模型 (CSM)的分析來了 解老人角色失落感、社會綱路疏離感、經濟不安全感及其對老人生活適應等潛在變項 之因果關係。 第一部分以老人的物質(性別、年齡、省籍)、及老人角色失落感、社會綱絡疏離感、 經濟不安全感來探討樣本老人的大概情形。結果發現樣本老人中有身體體病痛者高達 69.2%(173位)。而且年齡越高這個情況越普遍。另外女性老人比男性老人在社交綱路 上有著較高的疏離感 48.7%：在省籍差異上。外省籍老人比本省籍的老人在社會綱路 疏離感及經濟不安全感上都有著較高的疏離感及不安全感。 第二部分經由共變數結構分析模型檢視的結果，老人角色失落感對老人生活適應的影 響不存在。而經濟不安全感與社會綱路疏離感的影響是存在的。不過經濟不安全感與 本研究所預期的方向不一致。

房屋貸款借款人對於其所負貸款債務的處分有兩種潛在風險行為，分別是提前清償及違約。這兩種借款人風險行為不管是對金融機構的資產管理，或是對近年在財務金融領域的不動產證券化而言，都是相當重要的探討議題，原因在於提前清償及違約帶來了利息收益與現金流量的不確定性，進而影響不動產抵押債權的價值。也就是為貸款承作機構、證券化保證機構及證券投資人帶來風險。 借款人決定提前清償及違約與否，除了與借款人自身特性及貸款條件有關外，尚受到隨時間經過而不斷變動的變數所影響，亦即許多影響因子並非維持在貸款起始點的狀態，而是會在貸款存續期間動態調整。進一步影響借款人行為，而這類變數即為時間相依變數(time –dependent variables，或time-varying variables)。因此，本研究利用便於處理時間相依變數的比例危險模型(Proportional Hazard Model)來分析借款人提前清償及違約風險行為，觀察借款人特徵、房屋型態、貸款條件及總體經濟等變數與借款人風險行為的關係。 實證結果顯示，借款人特徵部分的教育程度對提前清償及違約風險影響最為明顯，教育程度越高，越會提前清償，越低則較會違約。房屋型態則透天厝較非透天厝容易提前清償及違約。貸款條件中的貸款金額及貸款成數皆與違約為正相關，亦即利息負擔越重，借款人違約風險升高。總體經濟方面，借款人對利率變動最為敏感，反映利率代表借款人的資金成本，是驅動借款人提前清償及違約的財務動機與誘因。