越中兩國自古以來是山水相連、唇齒相依的鄰國、兩國人民間之文化交流與互動關系源遠流長、成為雙方傳統友誼之重要構成要素。越中兩國均為開發中國家、目前經濟均快速成長越中兩國是山水相連、唇齒相依的鄰國，越中兩國均為開發中國家、目前經濟均快速成長，其雙邊關系發展值得重視。第二次世界大戰以來，越中關係歷經友好合作、疏離及對抗時期，中國採行「睦鄰外交」政策、確實穩定了週邊環境、同屬社會主義共產黨領導的越中兩國關系也由對抗走向正常化、兩國高層領導人頻繁互訪、經由談判解決陸地邊界及北部灣劃界問題、並在經貿、社會文化等各方面加強交流合作。其雙邊關係發展值得重視。經過一段時間所發生不愉快對兩國與兩國人民之間而言這是一場衝突遺留給後代兩國、兩個政府一個準確地看法在兩國關係之間中。 另一方面，兩國自從把關係回係正常化以後也給了地區和國際社會作出不少貢獻。這也表示中國如何對鄰廊的外交政策、反而越南也如何去應對此政策讓此關係日後更加緊密。

本文採用新的隨機共同邊界方法，將其擴充至Fourier富伸縮成本函數，針對西歐地區十個國家的銀行業進行成本效率之分析，資料期間涵蓋1996年至2010年。不同於Battese et al. (2004), O’Donnell et al. (2008), and Huang et al. (2011a) 等人利用線性規劃法，本文應用隨機共同邊界法來估計技術缺口比率，進而做跨國間的效率比較，此法的特點在於技術缺口比率可以設為一些反映國家環境差異的外生變數之函數，而線性規劃法則無法做此設定。實證結果顯示採用線性規劃方法所估計出的技術缺口比率與共同成本效率會有低估的現象，技術缺口比率以及共同成本效率在1996年至2000年間逐步上升，此結果支持金融市場的整合可以增進效率，然而，到2000年之後則反轉向下，特別是在2007年至2010年次級房貸風暴時期明顯惡化。此外，進一步的分群進行分析的結果顯示，小規模、高獲利、或是較保守的銀行相對來說較具有效率。 / This paper aims to gain further insights into cost efficiency using the newly developed metafrontier approach under the framework of the Fourier flexible cost frontier for banking industries across 10 Western European nations during the period 1996-2010. Unlike Battese et al. (2004), O’Donnell et al. (2008), and Huang et al. (2011a), who suggest using programming techniques, the stochastic metafrontier is formulated and applied to obtain the technology gap ratio (TGR) for efficiency comparisons among countries. One salient feature of our method is that the TGR can be specified as a function of some exogenous variables that reflect group-specific environmental differences, while the mathematical programming is not allowed to do so. Empirical results show that both TGR and metafrontier cost efficiency (MCE) are underestimated by programming techniques. The TGR and MCE exhibit a gradual upward trend during 1996-2000 and then followed by a downward trend, especially after the subprime crisis of 2007-2010. This suggests that a more integrated financial market is able to improve banking efficiency. Smaller banks tend to be more cost efficient than larger ones. Higher profitable banks and more conservative banks are related to greater efficiency.

在運動產業逐漸興起的現代，如何評比球隊或運動員的表現好壞，似乎成了現在新興的熱門話題。經濟學上用來評估一家廠商的生產績效優劣，常用的是生產效率分析，生產活動偏離生產邊界的程度代表不效率高低。而球隊比賽的過程就像廠商生產的過程，運用各種投入得到產出。在籃球比賽中，比賽的投入可為球隊的各種技術統計，例如：投籃命中率、抄截、火鍋…等等，產出則是比賽的得分數。因此，在本篇文章中，我們利用經濟學中的生產效率分析來分析球隊的表現優劣，即評估各球隊發揮其潛能的程度。 評估生產效率的模型有很多，由於比賽的性質，有時候統計誤差、運氣也佔了很重要的部份，所以在選擇模型時，選的是隨機邊界效率分析模型（Stochastic Frontier Approach, SFA），除了利用隨機邊界分析模型分析球隊的生產效率，也利用預估的效率值來預測比賽結果排名，並與一般常用來預測結果的模型PROBIT MODEL做比較。我們利用大陸男子甲A籃球聯賽2003-2004和2004-2005賽季作為實證樣本，發現隨機邊界分析模型不只可以用來評估效率，在預測比賽結果排名上，隨機邊界分析模型預測能力則與PROBIT MODEL沒有顯著統計性的差異。 關鍵字：生產效率、隨機邊界分析法、運動產業 / Today, sports industry is getting popular, and how to evaluate the performance of sports teams or players seems also to be a newly hot interesting topic. In economics, production efficiency is often applied to evaluate a firm’s production performance. The inefficiency of a production activity is measured as its deviation from the production frontier. The process of a sport game is similar to a firm’s production process, which transforming various inputs into output(s). For basketball games, inputs can be the various technical statistics, such as field goal rate, steals, blacks, assistant attack, etc. Output(s) can be the scores of the teams got. Therefore, in this paper we use the production efficiency to gauge the performance of sports teams. There are many models measuring production efficiency. In this paper we choose the Stochastic Frontier Approach (SFA) to evaluate the sport team’s efficiency on account of the white noises which exist in the sport game obviously. We also use estimated efficiency scores to predict the outcome ranking of teams, and compare it to that of the PROBIT MODEL which is usually used to predict the outcome of a game. The sample we used are the results of the CBA men’s regular season and playoff season, and we found that the SFA is not only to evaluate efficiency but also can predict the outcome of competition, and its prediction ability is not significantly statistically different to that of PROBIT MODEL. Keywords: Production Efficiency, Stochastic Frontier Approach, Sports Industry

Greene (2005) 在縱橫資料型態下提出真實固定效果隨機邊界模型 (true fixed effect stochastic frontier analysis, TFESFA)，該模型保留了傳統隨機邊界法之架構並考量到廠商間之異質性問題，同時設定廠商之無效率項可隨時間改變。但此模型假定不同廠商皆有特定之固定效果參數，當廠商家數多而資料觀察期間較少時，會因待估參數過多而導致模型存在擾攘參數問題，產生估計偏誤 。 本研究利用Tsay et al. (2009) 提出之方法，以錯誤函數 (error function) 之非線性近似函數以及關聯結構函數 (copula function) 推導得到TFESFA模型經一階差分轉換後組合誤差項之近似概似函數，成為本研究提出之差分隨機邊界模型(difference stochastic frontier model, DSFA) 模型，透過模擬過程生成平衡縱橫樣本及不平衡縱橫樣本，發現本研究提出之DSFA模型的確能在觀察期間較少時消除擾攘參數問題之影響。最後，本研究使用TFESFA模型及DSFA模型，配合投入面距離函數來衡量俄羅斯銀行之技術效率，而DSFA模型亦能達到更良好之估計效果。

隨著台海兩岸經貿往來密切，發展迅速，客觀上對銀行業提出了許多服務要求，為兩岸金融業的合作提供了廣闊的空間。本文通過採用數據包絡分析法和共同邊界成本函數比較分析了兩岸商業銀行的成本結構及效率差異，實證結果表示大陸商業銀行的成本效率要高於台灣銀行。對這一結果的可能性解釋是大陸銀行的資產規模要遠高於台灣銀行。銀行總資產越高，其獲取低投入要素價格的市場能力越強，因此生產成本更低，成本效率更高。台灣和大陸商業銀行有必要發揮自身的優勢，通過各種方式和渠道，加快兩岸銀行界合作的進程。 / With cross-strait rapid economic development and trade exchanges, huge business investments have induced a great demand for financial services and provided a broad space for cross-strait cooperation. This paper adopts data envelopment analysis and meta-frontier cost function to compare and analyze the different cost structure and efficiency of mainland and Taiwan commercial banks. The empirical results reveal that cost efficiency of mainland commercial banks is higher than Taiwanese ones, which is maybe caused by the larger bank size and total assets. The larger the size of banks, the higher the market power for reaping the benefits of low input prices, thereby resulting in a lower cost of production and a higher cost efficiency. It is necessary for mainland and Taiwan commercial banks to develop their own strengths to accelerate the process of cross-strait cooperation in the banking sector through various means and channels.

自一九七七年Ainger,Lovell,and Schmidt 發表隨機性邊界生產函數估計方法一文以 後，這項方法便廣泛地應用於廠商生產技術效率的估計。然而， Ainger，et al的方 法係利用單一年度橫斷面資料，方法中有一些缺失，例如：技術無效率部份的統計分 配假設、技術無效率部份與生產投入可能存在某些相關，以及技術無效率可能會隨廠 商經營期間而變化。本文的目的，即嚐試利用橫斷面與時間數列混合資料來修正上述 缺點，分析對象為台灣地區的外人投資廠商，包含電子電器、基本金屬、橡塑膠製品 、化學等產業，時間由民國64年至71年共八年。 台灣地區自一九五二年引進直接外人投資，外資在我國的經濟發展過程扮演重要角色 。過去有關台灣地區外人投資的文獻甚多，然而有關外資廠商生產效率的研究卻不多 見，直至目前僅 Chen and Tang(1987)，劉錦添與蔡偉德(1989)兩篇，且均偏重於橫 斷面的分析。本文將利用近年來發展的Panel Data生產技術效率測定方法來進行，文 中主要參考Schmidt and Sickles(1984) 與Cornwell，Schmidt and Sickles (1988) 兩篇著作。在實證中，假設廠商生產函數為Cobb-Douglas函數，分別利用「固定效果 」(fixed effect)及「隨機效果」(random effect) 二種模型。固定效果模型認為廠 商生產技術效率差異為一固定係數，反映於迴歸式截距項的差異；而隨機效果模型假 設生產術效率項目為隨機變數，效率的差異反映於迴歸式中殘差項的差異。此外，由 於生產因素投入與效率可能存在相關，為得到具有一致性的估計值，本文將利用工具 變數方法來修正。最後，本文分析不同年度廠商效率之變化，並探討造成效率變化之 原因。

兩岸在2001年底加入世界貿易組織（WTO），使得兩岸壽險市場受到經濟自由化及國際化的衝擊。因此，要如何提高自身的經營績效及競爭能力，便成為兩岸壽險公司最重要的目標。本研究以資料包絡分析法為基礎，並結合共同邊界（metafrontier）分析法，針對兩岸地區在2004年至2007年共59家壽險公司，進行經營效率與Malmquist生產力指數的實證研究。在生產力變動來源的拆解上，本文延伸Pastor and Lovell（2005）的固定規模報酬模型，利用變動規模報酬的生產邊界來衡量各公司的技術變動及技術差距比率變動，使生產力變動的來源上獲得更明確的意涵。最後本文利用Tobit迴歸模型，探討影響兩岸壽險公司經營效率的因素。 / After joining the WTO in December 2001, there is the advent of economic liberalization and internationalization on the life insurance market of Taiwan and Mainland China. Therefore, how to improve the operating performance and the industrial competitiveness in the present economic circumstance is the critical and important goal of the life insurance industry in Taiwan and Mainland China. This study applies data envelopment analysis with metafrontier model to measure the managerial efficiency and Malmquist productivity index of 59 firms of life insurance industry in Taiwan and Mainland China from 2004 to 2007. On decomposing the sources of productivity change, we extend Pastor and Lovell’ s CRS model (2005) to a VRS frontier benchmark to measure technical change and technical gap ratio change, which apparently provides us a more meaningful decomposition of productivity change. Finally, this study uses Tobit regression model to examine the factors which influence the managerial efficiency of the life insurance industry in Taiwan and Mainland China.

各國視生技產業為未來發展的關鍵產業，並積極推動各項政策，使生技產業能快速成長，而生技醫藥市場是促成全球生技產業成長的主要動力，為了增加我國的競爭力，希望藉由與鄰近國家醫藥產業的比較，能更了解台灣生技醫藥產業經營績效。 本研究採用Battese and Coelli (1995)隨機成本邊界法，針對2002-2007年間，日本、南韓、中國、印度與台灣等五個國家，共61家生技醫藥廠商進行實證分析，研究結果如下：(1)研發密集度增加使成本效率降低，五個國家裡，日本最具成本效率。(2)產業平均成本效率值為0.855，且有逐年惡化的趨勢。(3)整體產業平均處於遞增規模報酬階段。(4)整體而言，總要素生產力(TFP)的提升主要是因為規模成分的貢獻，其次為技術的進步，而技術效率變動率對TFP成長率為負影響。(5)各國間雖然TFP變動率不存在顯著性差異，但在規模成分、技術變動率與技術效率變動率等方面存在著顯著的差異。 / Many countries regard biotechnology as a key industry for the future development. Governments often implement a variety of policies to help it grow rapidly. The biotech pharmaceutical industry is the main momentum for the growth of the global biotech industry. The objective of this paper is to measure the productivity and efficiency of the industry among Asian countries, and investigates the sources of the performance changes, and then hope to give some insight into the enhancement of the industry’s productivity. To pursue our goal, we adopt Battese and Coelli’s (1995) stochastic frontier approach to assess 61 biotech pharmaceutical firms during 2002-2007. The main empirical results can be summarized as follows: (1) The R&D intensity is negatively related to cost efficiency; in five countries, Japan has the highest cost efficiency. (2) On average, the cost efficiency is about 0.86, and has become worsen year after year. (3)Most of time, the industry is characterized with the increasing returns to scale. (4) The growth of total factor productivity (TFP) is mainly attributed to the scale efficiency change, and technical progress accounts for a minor source. However, technical efficiency deteriorates over time. (5) Among countries, the TFP growth rates have no significant differences, but the components show apparent differences.

本文採用一階段隨機邊界分析法（Battese and Coelli, 1995）衡量2004 年第一季至2008 年第三季台灣上市櫃證券商的技術效率，並將Orea（2002）提出的產出導向一般化Malmquist生產力指數改寫成投入導向模式，用來分析台灣上市櫃證券商的生產力變動情形。實證結果顯示，小型券商之經營效率平均而言比大型券商之經營效率高，而大部分的證券商都呈現規模報酬遞增的技術狀態，可見台灣上市櫃證券商整體而言規模不夠大，必須設法再擴大至適當的規模方可發揮規模經濟效果。另外，較多的股本雖然理論上具備較強的競爭優勢，但可能沒有適當的決策支持，造成資源浪費反而降低經營效率；股價指數愈高，在相同的投入之下有較多的產出表現且較有能力調整規模至規模報酬較佳的狀況，因而提高經營效率。 / This paper adopts one-stage stochastic frontier analysis (Battese and Coelli, 1995) to measure technical efficiency of listed securities firms in Taiwan from the first quarter of 2004 to the third quarter of 2008. In addition, inspired by the Orea (2002) output orientated productivity model, this paper derives an input orientated generalized Malmquist productivity index to analyze the productivity change of the firms. The empirical results reveal that smaller securities firms are more efficient than larger securities firms in average. The majority of securities firms are operating with increasing returns to scale, indicating that the scale of listed securities firms in Taiwan are generally not large enough, so firms need to enlarge their scale in order to get the effect of economies of scale. Although more capital stocks possess stronger competitive advantage theoretically, without proper strategy to support the firms may waste resources and result in operational inefficiency. Operational efficiency is positively correlated with stock index.

本文採取隨機方向距離函數方法，探討制度變革前、後(第一次金融改革)對台灣銀行業技術效率的影響。資料期間涵蓋1999年至2012年。相較傳統Shephard距離函數，隨機方向距離函數方法最大優點係可同時考量增加意欲產出、減少投入與非意欲產出。本文依循Koutsomanoli-Filippaki et al. (2009a) 模型，並納入考慮非意欲產出。本文採取隨機邊界法進行實證估計，以最大概似法估計方向距離函數，依據Battese and Coelli (1995)的模型將環境變數納入實證模型 (主要模型)，並考量未包含環境變數之模型，與主要模型比較。此外，為凸顯非意欲產出之重要性，本文亦估計未考慮非意欲產出之模型以及傳統距離函數，以茲比較。 實證結果顯示，考慮非意欲產出與環境變數的主要模型，其估計結果相較其他模型之無效率明顯高估。2002年以前，技術無效率逐漸攀升。一次金改期間，技術無效率明顯下降，證明制度變革下，銀行效率獲得改善。惟2004年後反轉向上，尤其在雙卡風暴與次貸風暴期間，技術無效率明顯惡化。此外，本文將資料分群進行分析，發現公營銀行或是金控銀行較有效率。 / This paper aims to gain further insights into whether the policy of First Financial Restructuring (FFR) does improve the technical efficiency of banks in Taiwan during the period 1999-2012 by using the directional technology distance function (DDF). Compared to the conventional distance function, DDF simultaneously allows for the expansion of the desirables and the contraction of the undesirables. We follow Koutsomanoli-Filippaki et al. (2009a), and differing from them, we include undesirable outputs in DDF to depict a bank’s true production activities. We find on average that the banks have a lower technical inefficiency with the main model compared to the other models. However, prior to 2002, the technical inefficiency exhibits a gradual upward trend and then posts a downward trend during the FFR period. These results suggest that the improved efficiency in the FFR period is possibly due to enhanced banking and benefits obtained from compliance with FFR. After the FFR period, the inefficiency scores deteriorate sharply, especially during the “credit card and cash card crisis” in 2006 and “the subprime mortgage crisis” in 2008. Public banks are more efficient than private banks. Banks belonging to a financial holding company (FHC) may operate more efficiently than those belonging to a non-FHC.