金控銀行和獨立銀行在傳統在做績效評估時，可能都只考慮相同的技術水準，如此可能無法正確來衡量不同群體的的差異，而忽略其潛在的效率改善指標。因此，本文將先採用隨機邊界模型(SFA)，估出兩體系的隨機邊界模型，接著，再運用Rao (2006)所提出的共同邊界模型(metafrontier)，來進行兩個體系的銀行效率評估。 本研究運用了民國91年到民國97年期間，13家金控銀行與24家獨立銀行的資料為樣本，去分析此兩個群體的效率比較，可得以下結論： 1.在金控銀行與獨立銀行的個別隨機邊界中，兩個群體在於技術效率的表現上差異不大。 2.金控銀行的技術效率變動有越來越小的趨勢；而獨立銀行術效率沒有明顯的縮小的趨勢。 3.獨立銀行的技術缺口比TGR有顯著的大於金控銀行的TGR。 4.在共同邊界的技術效率中，獨立銀行的技術效率顯著的大於金控銀行 / Most of traditional banking performance evaluation analyses assume both financial holding banks and independent banks share the same level of technology, thus it may not able to identify the managerial efficiency difference of different groups correctly . In this research, a SFA model (Battese and Coelli, 1995) is used first to estimate the technologies and inefficiency factors for both systems. Then a deterministic linear programming metafrontier (Rao, 2006) is adopted to evaluate the technology gap ratio between two bank systems. We collect data of 13 financial holding banks and 24 independentbanks from 2001~2008. After analyzing two systems and making comparison, the main conclusions are as follows: 1.Two bank systems have a minor difference in SFA. 2.The variance on technical efficiency becomes smaller with time in financial holding banks, but not in independent banks. 3.Independentbanks’ TGR is significantly larger than financial holding banks’. 4.In metafrontier, technical efficiency of independent banks is significantly larger than financial holding Bbnks.

本研究的目的是針對退休金的長期負債以資產負債管理的方式提出有效的投資避險策略建議。在過去，傳統精算的資產負債管理大多採用確定投資模型（Deterministic Model），即以過去的經驗設立「精算假設」，但是這樣的假設無法精確的呈現未來的趨勢，所以本文的第一部份，便是根據過去的台灣總體經濟資料，建構一個退休基金的隨機投資模型（Stochastic Investment Model）。首先，我們以ECM（Error Correlation Model）模式建構出第一個投資模型，之後在精簡參數的考量下，建構第二個以因果關係為基礎的Causality投資模型，再以模型配適能力與預測能力比較兩模型，結果顯示Causality投資模型優於ECM投資模型。 　　有了投資模型，我們設定不同的退休金負債形式，如固定成長型負債MF、隨通貨膨脹成長M^R負債及隨max{固定成長比例，通貨膨脹}而成長的退休金負債M^L，以靜態避險的方式去求得各資產的最適配適比例。從模擬的結果中發現隨著到期日的增長，投資在風險性高報酬率佳的投資標的物上的比例也越來越高。另外，隨著負債固定成長比例f的增加，其M^L負債之期初資產配置額便越接近M^F負債之期初資產配置額。整體而言，我們由模擬中可得出，使用投資組合的投資方式優於單一資產投資的結論。 / In this study, we investigate the hedging strategies for pension liabilities by using Asset-Liability Management method. In the past, the traditional actuarial valuation usually does not take account of market value for both assets and liabilities. Most of the traditional actuarial valuation adopted the Deterministic Model, that is, setting the assumptions based on the experiences. However, it can not exactly show the trend in the future. In part one of this study, we build a stochastic investment model for the pension funds based on Taiwan Market data. First, we apply the first model : ECM( Error Correlation Model ). And then, we apply the second model : Causality Model under considering parsimonious parameterization. Finally, we compare the results of ECM with Causality Model on fitting and forecasting efficiency, and we find that Causality Model is better than ECM. With the investment model, we set some formulas of pension liabilities calculated to obtain the best fit proportion of each valuation by the static hedging. This involves finding optimal static hedging strategies to minimize riskiness of the investment portfolio relative to the liability. Overall, from the simulation results, for static hedging in these kinds of liabilities, investing in all three assets is a better strategy than investing in a single asset class. This confirms that the more assets we use, the more effectively we can hedge.

人類經濟活動重心之變革推動著產業競爭的樣貌，於二十一世紀的今日，知識已成為經濟活動中最主要之價值驅力，與之相應的，產業中智慧財產層面的競爭也逐漸受到重視，發展至今，智慧財產已深入產業鏈且細化為各種以智慧財產運用為中心以創造獲利之企業。 半導體產業於台灣經濟發展之推進中佔有關鍵性之地位，隨著台灣廠商在全球產業鏈中扮演的角色重要性與日俱增，難以避免必須因應半導體產業中由智慧財產所造就的新興商業模式，其中，智慧財產研發公司拋棄舊有以生產製造為主之商業模式，開創以知識為本的競爭場域，並挾其智慧財產進行全球化的授權以及訴訟，扮演著遊戲規則的創造者，尤其記憶體產業之兩大智慧財產研發公司Rambus Inc.以及Tessera Technology Inc.，自2000年起不斷於全球提起專利訴訟，對整體產業乃至於台灣廠商帶來無法忽視之影響。 本研究試圖建立分析智慧財產研發公司之架構，亦即由該等公司之策略演進出發，宏觀的了解其於變動的競爭環境中如何發揮企業優勢；其次，以公司策略定位為基礎，進一步推動資源投入之分配，並形塑商業模式的產生；最後，本研究萃取智慧財產研發公司商業模式中較具特色且影響廣泛之訴訟階段，藉由記憶體產業中之個案分析比較之方式進行深入之實證研究，以管窺該等公司之專利運用模式，期能透過提升對於智慧財產研發公司策略定位、商業模式以及訴訟模式之了解，活化企業智慧財產之管理，並提供台灣廠商面對專利授權與訴訟時因應之基礎。 / The revolution of economic activities of human beings has been the force behind the changing format of competition among industries. In the contemporary 21st century, knowledge has become one of the most valuable forces in economic activities; correspondently, the competition strategy of intellectual property also seized much attention. As of today, intellectual property has already been integrated in each and every industry chains and developed into various enterprises which earn profits by operating it. Semi-conductor industry played an important role in the process of Taiwan’s economic development. As Taiwanese companies claim more crucial roles in the global industry chain, they are inevitably forced to deal with the new business model established by the creation of intellectual properties. Among them, intellectual property development companies have withdrawn from old business model of production and manufacturing and create a new competition field on the basis of intellectually properties. Intellectual property development companies engage in global wide license and litigation, acting as the rule-maker within the new frame of competition. Rambus Inc. and Tessera Technology Inc. are the two leading intellectual property development companies which brought lawsuits internationally since 2000, creating serious impacts on both the entire industry and Taiwanese companies. This research aims to establish an analytical framework to observe intellectually property development companies, starting from the progress of strategy, try to understand how to exercise their advantages in the ever-changing competitive business world; furthermore, based on business strategies, this research look further into the distribution of resources and the creation of business models; lastly, this research closely examines the litigation phase of the business model of intellectual property development companies by comparative case studies, in order to conclude the operation pattern of patents of such companies. With further exploration on the strategic positioning, business model and litigation pattern of intellectual property development companies, this research provides not only a deeper understanding on the management of IPRs but also a framework for Taiwanese companies to cope with patent licenses and litigations.

在現今生物醫學領域中，一重要課題為透過基因實驗所獲得的量化資料，來研究與分析基因與外顯表型變數(phenotype)的相關性。已知多數已發展的方法皆屬於單基因分析法，無法適當的考慮基因之間的相關性。本研究主要針對基因組分析(gene set analysis)問題，提出統計檢定方法來驗證特定基因組的顯著性。為了能盡其所能的捕捉整體基因組與外顯表型變數的關係，我們結合了傳統的檢定方法與分類方法，提出以隨機森林分類方法(Random Forests)的測試組分類誤差值(test error)作為檢定統計量(test statistic)，並以其排列顯著值(permutation-based p-value)來獲得統計結論。我們透過模擬研究將本研究方法和其他七種基因組分析方法做比較，可發現本方法在型一誤差率(type I error rate)和檢定力(power)上皆有優異表現。最後，我們運用本方法在數個實際基因資料組的分析上，並深入探討所獲得結果。 / Nowadays microarray data analysis has become an important issue in biomedical research. One major goal is to explore the relationship between gene expressions and some specific phenotypes. So far in literatures many developed methods are single gene-based methods, which use solely the information of individual genes and cannot appropriately take into account the relationship among genes. This research focuses on the gene set analysis, which carries out the statistical test for the significance of a set of genes to a phenotype. In order to capture the relationship between a gene set and the phenotype, we propose the use of performance of a complex classifier in the statistical test: The test error rate of a Random Forests classification is adopted as the test statistic, and the statistical conclusion is drawn according to its permutation-based p-value. We compare our test with other seven existing gene set analyses through simulation studies. It’s found that our method has leading performance in terms of having a controlled type I error rate and a high power. Finally, this method is applied in several real examples and brief discussions on the results are provided.

現今世界趨勢已朝向全球整合的方向邁進，隨著科技日新，世界各國跨越地域隔閡，不論是在政治、經濟、科技、文化等各方面往來接觸愈來愈頻繁，中國大陸近年來與世界經貿關係連結更為緊密，同時亦對外開放直接投資，使跨國企業逐漸擴大進軍中國大陸之版圖，享受中國大陸豐沛之廉價勞動力。 然而，開放外人直接投資(Foreign Direct Investment, FDI)勢必為中國大陸相關之產業或總體經濟帶來某種程度之影響，儘管外人直接投資可帶來充沛之資本及先進之技術，但亦有可能加劇國內市場競爭，不利於本土廠商。 本文運用1998-2006 年「中國工業企業統計數據庫」中之電子業廠商，建構追蹤資料模型(Panel Data)，並運用隨機邊界法（stochastic frontier approach）估計中國大陸本資、台港澳資及外資企業生產效率，藉以衡量FDI之外溢效果。根據實證結果我們發現：中國大陸電子業之外人直接投資存在正向外溢效果及正向之技術移轉，顯示FDI之進入將有助於提升中國大陸電子業本土廠商之生產力。此外，我們同時發現FDI集中投資的結果將可能造成外溢效果的減低，除此之外，經濟區位亦是影響外人直接投資所帶來之外溢效果及技術移轉效果之重要因子之一。 / Global integration is the world trend nowadays. With the breakthrough of technology, the geographical barriers no longer exist. It would be much closer with other countries in many fields, such as politics, economics, technology and culture. In recent years, China has a closer economics and trades linkage with the world. As the results of openness to foreign direct investments, more and more multinational enterprises enter to China, expanding their scale and being benefited from the low-cost labor of China. China is benefited from the plentiful capital and advanced technologies of foreign direct investments; however, the openness to FDI might cause the competition which can aggravate in domestic market and hurt the domestic firms. The research uses the data of electronic firms from Chinese Industrial Enterprises Database. We apply panel data model and stochastic frontier approach to estimate the production efficiency of Chinese, Taiwanese, Hong Kong, Macanese and Other foreign enterprises. According to the empirical results, we discover that there are positive spill-over effects and technology transformation from foreign direct investments in Chinese electronic industry. These results indicate the entry of FDI will promote the productivity of Chinese electronic firms. Beside the positive results, we also discover the negative deduction stem in concentrated investments; furthermore, the spill-over effects and the technology transformation effects are affected by the economic location.

本文針對附保證年金型投資商品進行評價，其中被保險人脫退因素除受到死亡解約因素之外，對經濟環境影響因素產生解約問題，如利率攀升、經濟成長率、失業率等亦須考慮。附保證年金型投資商品公帄價值為保險公司販賣投資型年金商品須對負債面進行評價，以確保被保險人之權益，保險商品價值除因投資市場環境變動造成投資商品價值累積變動之外，對於被保險人因應市場環境轉變造成脫退問題亦影響保險公司對於投資型商品準備金價值評估，本篇依照Kolkiewicz & Tan(2006)之研究，假設附保證年金型投資商品評價方式，除投資標的受到市場變動影響外，對於經濟環境變動造成被保險人解約狀況亦考慮於核保模型中，因脫退因素考慮層面過廣，故本篇主要以死亡、經濟環境變動劇烈與利率上升導致解約因素為主要考慮狀態。 本研究推導之模型主要得出下列結果：(1)附保證年金型商品的公帄價格以保險年期的影響最大，其次為風險性資本市場長期帄均波動，而死亡率影響附保證投資年金型商品主要由風險性資本市場價值決定。(2)契約初始為主要解約期間，當解約力持續增加至一定值，契約後期解約率將趨於帄坦，本研究推估契約前期經濟市場波動易造成被保險人解約狀況，故解約程度增加。(3)主要投資型商品風險價差問題影響因素為長期市場波動程度，因風險價差之衡量主要考慮風險因子變動因素導致與公帄價值或期初保費差距，依照模型假設變動因子以風險性資產價值波動程度影響最巨，其次為保險期間，因此歸納出風險價差因子主要變動來源為風險性資產價值。 / In this paper, the goal is to evaluate fair value of guaranteed annuity-type investment products. In addition to death factors, the insured terminate by other reasons, such as interest rates raising, economic growth rate, and unemployment rate. Accordance with the liabilities side, the reserve of guaranteed annuity-type investment products must match it’s fair value. There is a question how to accurately evaluate fair value of guaranteed annuity-type investment products. The price of guaranteed annuity-type investment products is affected by two parts. One is cumulative index price change in value of investment goods, the other one is withdrawal rates. Kolkiewicz & Tan’s research assume guaranteed annuity-type investment products evaluation methods which is affected by market environment and termination status of the insured. The results show that (1) The major impact on fair value of guaranteed annuity-type investment products is mainly from the period of the insurance contracts. The secondary effect is long-term average risk capital market volatility. (2) The main terminate time is the beginning of the contracts. When the lapse rates continued to increase to a certain value, lapse rate tends to smooth.(3) The major impact on risk spread of guaranteed annuity-type investment products is mainly from long-term market volatility. To sum up, the major changes in sources of risk spreads factor are from asset value.

署立醫院為全國分佈最廣，且數量最多之公立醫院體系，負有貫徹國家公共衛生政策之責任，故其經營績效之良瓠影響各地區民眾健康照護水準甚鉅。惟署立醫院目前之經營仍仰賴國庫補助，在國庫補助逐年縮減的情形下，署立醫院惟有提升經營績效，才能維持醫療照護品質。 本研究運用三階段DEA分析法，評估步驟第一階段運用一般DEA分析法，以原始投入及產出項衡量各DMU的相對效率值，求得總差額值；第二階段運用SFA將差額分解，探討環境變數對於各DMU的影響程度，並利用SFA的結果調整產出項，將處於不同外在環境或是不同運氣之DMU，調整為相同之情況；第三階段則利用第二階段調整後的產出項，再次以DEA分析法評估調整後的效率值。 由研究結果可知，各署立醫院之無效率主要來自於非處於最適經營規模所造成之無效率，整體而言，大部分署立醫院之產能實際上係存在擁擠現象，而產生規模不經濟，故建議主管機關應嘗試調整部分署立醫院之經營規模，考慮醫療的投入與產出的效率性，以符合經濟規模的要求，應可有效提升管理效率。 另部分署立醫院在各方面之管理效率均較呈現相對較佳之結果，因此，建議由主管機關主導，加強各署立醫院醫療資源之整合及技術交流，透過相互觀摩學習，以同時提升整體署立醫院之經營管理效率。至有關目前區域聯盟之整合作業，建議「北區區域聯盟」應加強注意手術業務部分之資源整合，而「中南區區域聯盟」應加強注意門診病患業務部分之資源整合。

2011年，美國政府在經歷次級房貸和高軍事支出的雙重壓力下，爆發高度財政赤字的問題，造成歐巴馬政府面臨調高債務比例與債務上限的壓力。然而，在眾多的輿論聲中，美國民主黨與共和黨在八月底達成下列協議，減少政府支出、提高債務比例以及增加債務上限等；但是，是否這些方式將改善美國經濟？本篇文章在動態隨機一般均衡(DSGE)架構下，建立一個封閉經濟體系，並將政府支出加入私人廠商部門，透過公共投資，幫助私人廠商增加產出；並且在政府僅採行公債和徵稅融通下，找出一個最適的債務持有比例，使國內福利為最高。而本文發現政府進入生產部門時，將影響最適債務持有比例。即是，隨著政府支出生產彈性越大，最適債務持有比例也會上升，而在基準參數下，我們將會得到最適債務持有比例為百分之十的結論。 / In 2011, under the pressure of subprime mortgage and high military expenditure, the U.S. government accumulated high fiscal deficit, and the Obama government faced the pressure of raising debt ratio and raising debt ceiling. However, among the huge debates, the Republican Party and Democratic Party reached the deal in August which included cut-down government expenditure, raise debt ratio, raise debt ceiling, and so on. But, will these ways improve the U.S. economy? This paper follows the dynamic stochastic general equilibrium (DSGE) framework to construct a closed economy, which the government helps private firm to production through public investment. Besides, given that government only undertakes debt financing and tax financing, we try to find an optimal debt ratio which makes the highest domestic welfare. In our finding, if the government enters private production sector, the optimal debt ratio will be influenced. That is, the optimal debt ratio will increase with the production elasticity of government expenditure. Under the benchmark parameter, the optimal debt ratio is 10 percent.

本論文應用數學規劃建立符合我國法令規範與投資政策說明書之投資政策及風險管理的資產負債管理模型。主要的討論對象為國民年金、公務人員退休撫卹基金與新制勞工退休金。模型中主要透過資產配置的收益與提撥收入維持現金流的平衡，以支應現在或未來的負債。在提出的模型中，採取維持最低基金公積率的策略，以確保長期的償付能力。當償付能力不足時，以政府撥補或是修正提撥率處理巨額的虧損。且使用機率限制式將發生不足的風險控制在可接受的範圍內。因此本論文提出的模型為多階段的有補償的混和整數隨機規劃模型。

由於許多國家死亡率下降快速、壽命延長幅度超乎預期，加上生育率持續低於替代水準，人口老化現象愈發明顯，近年來個人生涯規劃及政府施政，都格外強調退休後經濟生活及老年相關社會資源分配的比重。以臺灣為例，行政院經濟建設委員會 (簡稱經建會) 從1990年代開始，每兩年公布一次未來的人口推估，但過去十年來經建會屢次修正歷年的推估假設，以因應生育率及死亡率變化快速，適時提醒臺灣日益加速的人口老化。正因為人口推估可能受到人口數、社會變遷、資料品質等因素，影響統計分析的可靠性，常用於國家層級的推估方法，往往無法直接套用至縣市及其以下的層級 (即小區域)，使得小區域人口推估較為棘手，需要更加謹慎面對。 本文延續王信忠等人 (2012) 的研究，以小區域人口推估為目標，著重在生育率推估研究，結合隨機模型與修勻方法，尋找適合臺灣縣市層級的小區域人口推估方法。本文考量的隨機模型計有區塊拔靴法 (Block Bootstrap) 和 Lee-Carter 模型 (Lee and Carter 1992)，以預測未來的生育率和死亡率，並套用年輪組成推計法 (或稱為人口要素合成法；Cohort Component Method) 及修勻 (Graduation) 方法，探討這些方法與人口規模之間的關係，評估用於小區域人口推估之可行性。 本文首先以電腦模擬，探討生育率的推估，討論是否可直接推估總生育率，類似增加樣本數的概念，取代各縣市的年齡別生育率，以取得較為穩定的推估。根據模擬結果，發現人口規模對出生數的推估沒有明顯的關係，只要使用總生育率、再結合區塊拔靴法，就足以提供穩定的推估結果。實證研究方面，以臺灣縣市層級的人口及其年齡結構 (例如：0-14歲、15-64歲、65歲以上) 為驗證對象，發現分析結果也與電腦模擬相似，發現以區塊拔靴法推估臺灣各縣市的總生育率、年齡組死亡率，其推估精確度不因人口規模而打折扣，顯示以區塊拔靴法推估總生育率、年齡組死亡率，可用於推估臺灣小地區的未來人口。 / Due to the rapid mortality reduction, prolonging human longevity is a common phenomenon and longevity risk receives more attention in 21st century. Many developed countries encounter many problems brought up by prolonging life, such as poor community infrastructure and insufficient financial pension funds for the elderly. Population Projection thus becomes essential in government planning in dealing with the population aging. However, rapid changes in mortality and fertility make the projection very tricky. It would be even more difficult to project areas with fewer populations (i.e., small areas) since it takes extra efforts to deal with the larger fluctuations in small population. The objective of the study is to construct a standard operating procedure (SOP) for small population projection. Unlike the previous study, e.g., Wang et al. (2012), we will take both the fertility and mortality into account (but set migration aside for simplicity). First, for the fertility projection, we evaluate if total fertility rates (TFR) are more appropriate than the age-specific fertility rates for small population. Also, we compare two fertility projection methods: Lee-Carter model and block bootstrap, and check which shows better results. Based on the computer simulation, we found that TFR performs better and the block bootstrap method is more sensitive to rapid fertility changes. As for mortality rate projection, we also recommend the standard operating procedure by Wang et al. (2012). However, the smoothing methods have limited impacts on mortality projection and can be ignored. In addition to simulation, we also apply the SOP for projecting the small population to Taiwan counties and it achieves satisfactory results. However, due to the availability of data, our method can only be used for short-term projection (at most 30 years) and these results might not apply to long-term projection. Also, similar to the previous work, the fertility rates have the larger impact on small population projection, although we think that the migration has large impact as well. In this study, only the stochastic projection is considered and we shall consider including expert opinions as the future study.