為解決經濟發展過程伴隨的污染問題，常可見到政府和私部門一同投入防治工作，Pearce and Palmer (2001) 發現OECD國家隨著經濟成長，政府逐步提高公共防治支出，而且各個國家私部門的防治投入仍然佔有相當比重。Seldon and Song (1994)、Antle and Heidebrink (1995) 和Komen et al. (1997) 等實證文獻曾提出「倒U字型」EKC成立的原因可能來自環境財為奢侈財，使得經濟成長過程中公共防治投入快速增加，污染才會逐步減少。雖然Pearce and Palmer (2001) 實證OECD國家公共防治投入的所得彈性確實大於1，可是Kriström and Riera (1996) 發現許多國家對環境品質改善之願付價值的所得需求彈性值介於0到1之間，環境品質實為正常財而非奢侈財。鑒於相關實證資料的矛盾，本文從政府公共防治決策過程，了解環境品質所得需求彈性與公共防治投入所得彈性大於1的關聯，以連結環境品質所得需求彈性與EKC成立的關聯。本文證明無需奢侈財的偏好條件，而僅需環境品質偏好為正常財，以及防治技術滿足規模報酬遞增或固定，平均所得提高，消費者對環境品質的主觀願付價格高於客觀代價，模型預期政府將不斷提高防治費率，平均所得水準和防治費率同步增加，公共防治投入的所得彈性必定大於1，污染量終會減少並趨向於零。 實證研究指出並非所有種類污染物的污染水準與平均所得關係，一定呈現「倒U字型」關係，而過去理論模型單從消費者對於環境品質偏好條件，或是單從污染物防治技術是否具備規模報酬遞增，仍不能完全解釋不同污染物與所得關係的差異性。本文強調必須將經濟成長帶動所得分配變化對污染的間接效果納入，有助於釐清不同種類污染物與所得關係的差異性。首先，所得分配固定不變而平均所得提高，只要滿足環境品質偏好為正常財，以及防治技術滿足規模報酬遞增或固定，平均所得對污染的直接效果為「倒U字型」。再則平均所得固定不變時，只要消費者對環境品質的偏好為正常財(而非奢侈財)，所得分配改善，經由多數決投票決定均衡費率反而調降，污染隨之增加。考量高所得國家經濟成長帶動所得分配改善 (即顧志耐曲線存在) 的間接效果，不同污染物面對相同的所得分配變化，唯一的差異僅是防治技術的不同。防治技術之規模報酬遞增並不保證平均所得對污染的淨效果為「倒U字型」，而必須該污染物防治技術之規模報酬指數很高，直接效果大到足以抵銷間接效果，淨效果才可能為「倒U字型」。 另外，本文探討為何世界各國普遍有公私部門同時投入防治的現象，以及研究公共防治支出對私人防治投入產生排擠或排入效果的機制。模型發現無論政府和私部門的防治要素是否為互補要素 (complementary inputs) ，政府和私部門的最適防治投資都不為零。假若私部門增加設備無關乎提升公共防治設備之效能，公共防治增加，將對私人投資產生排擠效果。假若私部門增加設備可以提升公共防治設備之效能，公共防治對私部門防治投資可能產生排擠效果或排入效果，端看該國對於環境品質的重視程度。 政府環境政策制定與私部門防治投資決策的互動息息相關，環境政策的成效實有賴私部門是否願意配合投入防治設備。一旦公共支出對私人投資具排入效果，政府傾向事前宣布較高費率，期望刺激私人投入防治，待事後私人已經投入防治設備，政府則有誘因調降費率。反之，假若公共支出對私人投資具排擠效果，則政府傾向事後再調高費率。只要政府落實事前宣布政策，在符合實證支持的技術條件，污染與平均所得的關係為「倒U字型」的環境顧志耐曲線 (Environmental Kuznets Curve, 以下簡稱EKC) ，若缺乏機制督促政府落實事前宣布政策，且消費者理性預期政府背離意向，當動態一致性 (dynamically consistent) 費率低於事前宣布政策的費率，則執行動態一致性費率所對應的EKC將高於政府確實執行事前政策之EKC；若動態一致性費率高於事前宣布的費率，環境政策的動態不一致反而使得EKC降低。

本論文的研究目標是建構一個由多標記複合成的最佳疾病診斷工具，所考慮的評估準則為操作者特徵曲線在特定特異度範圍之線下面積(pAUC)。在常態分布假設下，我們推導多標記線性組合之pAUC以及最佳線性組合之必要條件。由於函數本身過於複雜使得計算困難。除此之外，我們也發現其最佳解可能不唯一，以及局部極值存在，這些情況使得現有演算法的運用受限，我們因此提出多重初始值演算法。當母體參數未知時，我們利用最大概似估計量以獲得樣本pAUC以及令其極大化之最佳線性組合，並證明樣本最佳線性組合將一致性地收斂到母體最佳線性組合。在進一步的研究中，我們針對單標記的邊際判別能力、多標記的複合判別能力以及個別標記的條件判別能力，分別提出相關統計檢定方法。這些統計檢定被運用至兩個標記選取的方法，分別是前進選擇法與後退淘汰法。我們運用這些方法以選取與疾病檢測有顯著相關的標記。本論文透過模擬研究來驗證所提出的演算法、統計檢定方法以及標記選取的方法。另外，也將這些方法運用在數組實際資料上。 / The aim of this work is to construct a composite diagnostic tool based on multiple biomarkers under the criterion of the partial area under a ROC curve (pAUC) for a predetermined specificity range. Recently several studies are interested in the optimal linear combination maximizing the whole area under a ROC curve (AUC). In this study, we focus on finding the optimal linear combination by a direct maximization of the pAUC under normal assumption. In order to find an analytic solution, the first derivative of the pAUC is derived. The form is so complicated, that a further validation on the Hessian matrix is difficult. In addition, we find that the pAUC maximizer may not be unique and sometimes, local maximizers exist. As a result, the existing algorithms, which depend on the initial-point, are inadequate to serve our needs. We propose a new algorithm by adopting several initial points at one time. In addition, when the population parameters are unknown and only a random sample data set is available, the maximizer of the sample version of the pAUC is shown to be a strong consistent estimator of its theoretical counterpart. We further focus on determining whether a biomarker set, or one specific biomarker has a significant contribution to the disease diagnosis. We propose three statistical tests for the identification of the discriminatory power. The proposed tests are applied to biomarker selection for reducing the variable number in advanced analysis. Numerical studies are performed to validate the proposed algorithm and the proposed statistical procedures.

大多數國家的中央銀行均以「穩定物價，控制通貨膨脹」視為貨幣政策的主要目標，因此本研究以 Stock and Watson (1999) 為基本架構，運用2000年1月至2015年12月台灣失業率與其他經濟指標之 Phillips 曲線模型，以遞迴迴歸 (recursive regression) 的方式進行模擬樣本外預測1個月與12個月核心消費者物價指數通貨膨脹率及消費者物價指數通貨膨脹率，及檢驗模型結構穩定性，並利用組合預測方式，進行模型預測績效比較。 其實證結果顯示：核心消費者物價指數年增率模型的預測績效優於消費者物價指數模型的預測績效，而比較失業率及其他經濟指標之 Phillips 曲線各個單一模型，在模擬樣本外預測1個月核心消費者物價指數年增率之預測績效，為營造工程物價指數 (cci) 表現最好，再者發現預測12個月核心消費者物價指數之 Rel. RMSFE 比預測1個月核心消費者物價指數之 Rel. RMSFE 來的小，另外Diebold-Mariano 檢定對於核心消費者物價指數 (cpix) 和消費者物價指數 (cpix) 做為通貨膨脹率之組合預測模型樣本外預測1個月通貨膨脹率之預測績效皆沒有改善效果，反而是部分組合預測模型在樣本外預測12個月通貨膨脹率之預測績效具有改善效果，皆顯示長期預測12個月比短期預測1個月之各個經濟變數的組合預測模型預測績效有明顯的改善，可能係在檢定預測12個月核心消費者物價指數 (cpix) 之 Phillips 曲線模型具有結構性改變影響所致。

內容大致如下： 第一章：說明本論文研究動機與目的、研究方法、研究限制等。 第二章：探討多國籍企業對外匯風險管理的兩項首要工作─匯率變動預測與外匯風險 暴露分析。 第三章：探討多國籍企業外匯風險管理的目的、動機、對風險的態度、避險策略設定 ，各種替代性避險技術之評與選擇，最後說明集權制與分權制之取捨。 第四章：首先說明我國企業對外投資現況與展望，次探討我國外匯風險管理的環境， 最後分從匯率預測、外匯風險暴露分析及其管理對策探究目前我國多籍企業外匯風險 管理之務。 第五章：結論與建議。

內容如后： 第一章：導論，說明本論文之研究目的、研究方法、研究限制及全篇論文之結構。 第二章：敘述傳統情況下損益平衡分析之假設限制條件及應用上之限制。 第三章：損益平衡分析法之最新發展。 第四章：不確定情況下之損益平衡分析、說明線性、非線性分析、討論單一產品及多 產品的常態分配模式、對數常態分配模式。 第五章：建立不確立情況下損益平衡分析之一般決策模式，將需求及利潤視為隨機變 數，以修正傳統模式，並研究兩平點之隨機分析，即假設固定成本與邊際貢獻為互變 數對數常態分配時之兩平點機率探討。 第六章：實例研究。 第七章：學習曲線在損益平衡分析上之應用。 第八章：結論。

本研究採用一項有關青少年成長與發展調適問題的長期貫時性追蹤資料(1996-1999)，試圖突破過去討論青少年憂鬱症狀發展時，所用之横斷式資料的囿限，嘗試應用潛在成長曲線模型(Latent growth curve model, LGC Model)的分析方法，加入歷史時間的縱深，捕捉青少年憂鬱症狀的「起始狀態」、與「個別的成長軌跡發展」。以不扭曲地將所有受試青少年在三年間的內化症狀變化情形，忠實地描述出來。而後，加入「改變」因素的討論，企圖尋找能影響青少年憂鬱症狀發展軌跡的關鍵機制。 此研究主要目的即在「具象化」復原力的理論觀點，企圖加入動態的時間面向，確認負向生活事件與青少年憂鬱症狀發展軌跡之間的因果關聯，並探討來自個人、與環境脈絡中的關係運作，對青少年憂鬱症狀平均數、變化方向與速率的跨時間影響。研究結果明確回答：為什麼有些青少年在受到憂鬱症狀的負向影響之後，尚能有回復機會並「表現地比預期好」的疑問。至於針對一群憂鬱症狀發展呈現改善、或惡化的少數青少年樣本，在性別、自尊、負向生活事件、家庭親子互動、學校好朋友關係等特性上的差異，本研究亦逐一說明。 在理論層次上，本項研究結合適切的研究方法，從「靜態」到「動態」地觀察青少年的身心發展、自「個人」到「家庭系統內外」討論內外在資源對青少年復原的短暫以及長久影響效果，並以一般青少年為研究對象的作法，擴增了復原力理論的推論範疇與解釋深廣。研究顯示，青少年的「改善」或「惡化」憂鬱症狀發展軌跡，確實在環境脈絡的節制之下，存在著個別差異。此外，青少年起始的憂鬱狀態並不影響憂鬱症狀軌跡發展的變化率。家庭經濟不利這項負向生活事件，對於青少年憂鬱症狀的預測，只呈現短暫的初始影響。自尊和好朋友關係皆是青少年可以主動建構與可為之舉，為兩個最重要能影響青少年憂鬱症狀變化的關鍵因素。至於學校脈絡，則可視為在家庭脈絡之外，能提供青少年憂鬱症狀改變效果的新路徑，以及讓青少年可以順利「轉大人」之雙重機會的結構因素。 / Using data derived from a panel study (1996-1999) of long-term Taiwanese adolescent development and adaptation, this study intended to break through the limitations of cross-sectional studies, which plagued past studies of adolescents’ developing depressive symptoms. By employing the Latent Growth Curve Model (LGC Model), this study mainly attempted to feature the individual initial status and the trajectory of every adolescent’s developmental depressive symptoms, which concerned about the important functions of the dynamic historical time and space on youth internalizing symptoms, for the research purpose to reflect the real resilient outcome each adolescent displayed. Besides, in order to understand the key factors that were taken as positive and effective mechanisms to influence the initial status and rates of changes on youth trajectories of depressive symptoms, several latent constructs such as self-esteem and protective factors developed from family and school contexts were taken into accounts. Further, specified characteristics were noted to highlight the basic differences gradually showed between resilient improved adolescents and worsen ones. A positive-psychological stance was taken as the leading research perspective in this study. The results shows that familial economic hardship only affects the initial status of adolescent depressive symptoms, implying that this negative event just had a short-term effect on youth’s psychological well beings. Those who were initially vulnerable to familial negative event had opportunity to become resilient over time. As to the protective factors, self-esteem and cohesive good-friendship were two crucial facets adolescents could actively construct and make efforts for further resilient performances to be better than expected. The analyzing results indicated, interestingly, that parent-child relationship early obtained in family context and adolescent’s satisfaction with parenting merely counted for the initial impact on adolescent trajectories of depressive symptoms. Concerns and cohesive relationships acquired in school contexts, especially in classes, provided dual chances for adolescents to become resilient in a long run.

2008年初，正值美國籠罩次級房貸風暴影響、全球經濟景氣趨緩、產油國地緣政治因素造成能源價格創新高…等險峻經濟狀況之際，投資銀行設計一包含 :搭配出局條款之CMS Spread雪球型利率結構商品及結合附加WTI上限、USD/JPY匯率上下限之異型選擇權的混合結構性商品提案。本文依據標的資產屬性，參考相關文獻及近期在頂級期刊發表之利率資產評價模型研究中，選用Extended BGM模型(Ting-Pin Wu, and Son-Nan Chen(2007))、遠期曲線模型及匯率評價模型為個案之基礎評價模型；以無套利觀念依取得之市場各資產相關公開報價資料估算各模型所需之參數；由於屬於雪球利率結構型商品及路徑相關特性，在目前相關文獻無封閉解的條件下，使用蒙地卡羅模擬獲得未來各資產之現金流折現值，進而計算預期理論價值。依據上述方法論評價所獲得之預期理論價格顯示，個案並非具公平價值之交易，依此結論強烈建議客戶不應該承做本交易。 個案相當於投資銀行以買入一個5年期附帶出局條件，隱含看空經濟景氣循環之CMS Spread選擇權及買入一個1年期看空WTI價格選擇權建構此混合結構性商品。為強化客戶承做意願，設立一似乎觸及機會很大，但從交易後至今從未觸及的出局條件，又透過每日數位選擇權計息方式將WTI波動度資產化，提供大於10%之相對LIBOR rate 很高，但實際是被低估之半年收息固定費率。由於雪球型利率結構型商品特性，收益不僅取決於是否達成交易付款條件，更重要因素是達成時間點之速度。 在蒙地卡羅模擬資產價格路徑中，觸及頭一次CMS Spread付款條件天數之眾數區間為125至135，貼近實際136天。從評價結果，交易之付款條件內已隱含透過兩個不同標的資產選擇權之高預期獲利相互達到避險、套利及強化收益等效益;投資銀行可以不用額外對受眾多複雜不確定因數影響之WTI價格採取避險策略，而將所有避險成本轉嫁於選擇權賣方的客戶。在資本計提規範下及確保未來預期收益之考量下，投資銀行唯一要做是以低成本尋求中介銀行進行背對背交易以強化因市場風險所衍生之信用風險。 從研究過程，不禁讚嘆個案是投資銀行設計建構在財務工程科學上的卓越藝術及策略，從它一旦出現世界上之瞬間，個人預估其價值將達34,211,458.09美元! / Early 2008 was a steep economic era when U.S. was enveloped by subprimemortgage crisis, world's economy was slowing down, and energy prices were pushed to a historical record high by oil geopolitical factors. Under this situation, an investmentbank designed a hybrid structure product, which includes a CMS Spread Snowball interest rate structured product with USD/JPY FX rate Knock out condition, a WTIoption of an additional upper limit, a USD/JPY exchange rate combined exotic option of upper and lower limits. After considering assets attributes and reviewing the relevant literature and recent research published in top journals related to the interest rate assetpricing model, Extended BGM model (Ting-Pin Wu, and Son-Nan Chen (2007)), forward curve model, and FX Rate model are selected as the basic pricing models. Tocalculate the expected theoretical value of this structured product, the unavailable model parameters of assets are estimated through the public market data based on thearbitrage-free concept, and the discounted values of the assets future cash flows are obtained by Monte Carlo simulation because of snowball interest rate structured product and path dependency characteristic and no close form solution in current relevant literature. The results of the pricing models shows that the net present value(NPV) received by customers is lower than that received by the investment bank, theconclusion is : Strongly recommend customers should not to do this trade ! In this case, the investment bank used a long position of one 5-year period CMSSpread Option with knock out condition, which implies Bearish on the economic cycle, and a short position of a 1-year period WTI option with up and low limits condition to construct this hybrid structure product. To draw customers’ attention to this proposal, the investment bank designed a knock out condition that seemed to be met very easily,but the price never touched by the article finished date. Additionally, a daily accrued digital option is used to transfer WTI volatility to a semi-annual fixed yield over 10% that, compared to LIBOR Rate, is very high but actually is underestimated. For theSnowball structure product, the total profit depends on not only when but also, more importantly, how soon to meet the payment condition. According to the asset pricing path generated by Monte Carlo simulation, the mode range which CMS Spread payment condition first met is 125 to 135 days after the contract’s value date, very close to the actually history data of 136 days. From pricing results, terms of contract implied that two different options combined to hedge risk and gain profit from each other. Hence, the investment bank does not need to make extrahedge strategy to WTI price which is impacted by more complicated risk factors.However, customer must spend hedge cost because of taking much risk as a sell option role. Under the Capital Charge regulation, to lock up the expected profit, what the investment bank needs to do is only to pay a very low cost fee, which like insurancepremium, to look for an intermediary bank to offer a back to back trade to manage thecredit risk caused by market risk! During the research of this paper, I am amazed what an excellent art and strategy that designed by the investment bank based on financial engineering science! As this structure product appeared in this world, I estimated that it would worth 34,211,458.09 USD.

近年來剖面資料的監控在統計製程控制中有很大範圍的應用。在這篇論文裡，我們針對監控無母數剖面資料提出一個實務上的操作方法。這個操作方法有下列這些重要的特色：(1)使用一個靈活且有計算效率的無母數模型B-spline來描述反應變數與解釋變數的關係；(2)一般迴歸模型中之殘差結構假設是不需要的；(3)允許剖面資料內之觀測值間具有相關性之結構。最後，我們利用一個無線偵測器的實際資料來評估所提出方法的效率。 / Profile monitoring has received increasingly attention in a wide range of applications in statistical process control (SPC). In this work, we propose a practical proposed guide which has the following important features: (i) a flexible and computationally efficient smoothing technique, called the B-spline, is employed to describe the relationship between the response variable and the explanatory variable(s); (ii) the usual structural assumptions on the residuals are not require; and (iii) the dependence structure for the within-profile observations is appropriately accommodated. Finally, a real data set from a wireless sensor is used to evaluate the efficiency of our proposed method.

醫療技術的進步以及生活品質的提升，預計人類平均壽命將持續延長，以臺灣為例，男、女性平均壽命將從2011年的75.98歲、82.65歲，增加到2060年的82.0歲、88.0歲（資料來源：行政院經濟建設委員會2012年推估）。壽命延長意謂更長的退休生活，世界各國在21世紀均面對需求日殷的老年生活照顧，包括退休金制度以及老人醫療等，這些社會福利及保險勢必增加國家財務負擔，因此壽命是否繼續延長或存有極限成為大家關心的議題。近年來，不少研究透過死亡壓縮(Mortality Compression)連結壽命議題，亦即探討死亡年齡是否將集中至更窄的範圍，但因為資料及研究方法的限制，死亡壓縮是否成立仍無定論。 本研究以統計方法、分配假設、資料品質，三個面向來探討死亡壓縮與延壽之間的關係。本研究提出三種數值優化方法：加權最小平方法(Weighted Least Squares；WLS)、非線性極值法(Nonlinear-Maximization；NM)及最大概似估計法(Maximal Likelihood Estimation；MLE)，透過電腦模擬衡量方法優劣，與過去常見的方法比較（Kannisto的SD(M+)），探討何者具有較小的均方誤差(Mean Squared Error；MSE)。其次若死亡年齡之真實死亡分配為t分配時，探討以常態假設代入計算所產生的偏誤；最後則是套入各國實際死亡資料，使用上述較佳的估計方法，檢視死亡壓縮是否存在。 研究結果顯示，NM具有不偏性質且具有較小的均方誤差，過去研究常用的SD(M+)反而有明顯偏誤，且隨著觀察值越多變異數反而增加。而若真實死亡分配若為t分配時，以原先利用常態假設所計算的年金險保費皆有低估的情形，分配的重要性可見一斑，進而探討在實務上常態分配之假設，發現與仍與實際情形有明顯之差異，不論是NM及SD(M+)在死亡壓縮的探討下，皆受到資料的限制而有待商榷。 / Due to the advance in medical technology and the change of life style, the human life expectancy has been increasing since the end of the Second World War II and it is expected to continue the pace of increment. Longer life expectancy also means a longer life after retirement. People living in the 21st century are faced with growing demand for the retirement life, such as the pension funds and medical needs to the individuals, as well as the social welfare and insurance for the elderly to the government. Thus, the issue whether the lifespan has a limit receives a lot of attention. In particular, many studies focus on the topic of mortality compression, which means that the expectancy of lifespan has a limit and variance of lifespan converge. However, due to the availability of elderly data, there is still no consensus if the mortality compression is true. In this study, we propose estimation methods to estimate modal age and variance of the age-at-death. Three types of methods are involved: weighted least squares (WLS) method, nonlinear maximization (NM) method, and maximum likelihood estimation (MLE) method, and they are compared to the method proposed by Kannisto, namely SD(M+), in 2000. We found that the NM method has a smaller MSE, and we cannot decide the mortality compression is true based on the data from Human Mortality Database. We also applied the normality and t distribution assumption to the age-at-death and compute the pure premiums for annuity products. We found that normality distribution would produce larger premiums than using the empirical mortality rates. Similarity, the bankruptcy probability would be higher if the t distribution is used.

關聯結構(Copula)這個字最早由Sklar(1959)以法文所提出，在邊際分配未知的假設下，透過關聯結構的特性，可以容易的建立聯合機率分配，所以關聯結構的觀念廣泛應用在財務領域中。對於資料在配適關聯結構的同時，要如何知道哪種關聯結構函數是最符合資料型態的分配呢?為解決這個問題，本文中參考Dobric and Schmid (2005)所提出的方法--卡方適合度檢定，來看資料配適關聯結構函數是否配適的恰當。所以本文的研究重點就是在利用卡方適合度檢定來探討各類股間日報酬率資料配適關聯結構的情形。在5種不同關聯結構(Normal關聯結構、t關聯結構、Clayton 關聯結構、Frank關聯結構、Gumbel關聯結構)，利用蒙地卡羅模擬方法，來做關聯結構在卡方適合度檢定之模擬，以及檢定力曲線。在檢定統計量、參數估計、顯著水準的估計都還不錯，只有當切割數越大時參數估計會和設定值差異較大。從檢定力曲線可看出這些檢定的檢定力都很好，代表有足夠能力能去辨別出分配的差異性。實證的部份，從台灣上市公司選取4個內需概念股報酬率的日內資料。結果可看出在Normal、Clayton、Frank、Gumbel這4個關聯結構，是不適合用來描述實際報酬的日資料。而當t關聯結構自由度較小時來描述資料型態是表現的不錯。