本文欲利用方向距離函數 (DDF) 來驗證中東歐國家銀行業之效率。不同的國家之銀行業者會由於不同的文化、資源稟賦和環境而採取不同的經營模式。因此，本文藉由共同邊界方向距離函數，其允許我們在跨國間不同的技術下，得以估計出銀行的技術效率並加以比較。使用方向距離函數，得以讓我們的模型中納入非意欲產出，此外，其亦允許銀行廠商同時增加產出與縮減投入和非意欲產出，相較於傳統模型，方向距離函數屬於較有彈性之模型。重要的是，不良貸款被視為是貸款過程中之副產品，其可能會降低銀行的利潤和績效。因此，為了減少不良貸款之產生，銀行管理者必須花費額外的成本，以確保借貸者是否有良好的信用，此舉亦可能影響銀行的績效。 本文試圖發展新的共同邊界隨機方向距離函數，其不同於Battese et al. (2004) 所提出的方法，該方法是屬於線性規畫法。此數理規畫法是屬於確定邊界，其無法針對有興趣之參數估計出該標準誤，因此，無法做有效地統計推論。因為本文提出的新共同邊界方向距離函數是隨機的，所以參數之標準誤可以被估計，其亦允許我們建造信賴區間和假設檢定。此外，共同邊界方向距離函數之無效率項可以被進一步設定成環境變數之函數，即Battese and Coelli (1995)所提出之模型。 / This study plans to employ directional technology distance function (DDF) to examine bank efficiency of Central-East European countries. Banks from different countries choose to operate under distinct technologies due to their differences in culture, endowments, and environments. A metafrontier directional distance function will be established, which allows for calculating comparable technical efficiencies for banks under different technologies relative to the potential technology available to the industry across nations. The salient feature of the DDF is its ability to include undesirable outputs into the model. In addition, it allows for a bank to simultaneously expand outputs and contract inputs, as well as undesirable outputs. It is important to note that the non-performing loans (NPL) can be regarded as a by-product of various loans granted, which lowers a bank’s profitability and performance. To reduce the occurrence of NPL bank managers have to spend extra costs to confirm whether the potential applicants for loans have good credit before granting loans to them. This may also affect the bank’s performance. This study attempts to develop a new metafrontier DDF in the context of the stochastic frontier approach, which differs from the one proposed by Battese et al. (2004) who suggest the use of a linear and/or a quadratic programming technique. The mathematical programming technique is known as deterministic, which is unable to estimate the standard errors for the parameters of interest. Hence, no statistical inference can be made. As our new metafrontier DDF is stochastic, the standard errors of the parameters are estimable, which permits establishing confidence intervals and hypotheses testing for the parameters. Moreover, the inefficiency term of the metafrontier DDF can be further specified as a function of several environmental variables of the form proposed by Battese and Coelli (1995).

隨著經濟的全球化，外人直接投資(foreign direct investment)儼然成為國際間技術擴散的主要途徑，技術外溢也成為外人直接投資發生下的重要議題，尤其利用跨國公司的先進技術促進本國生產力的提升，為開發中國家致力於吸引外人直接投資前來投資的強大動機。其中來自港、澳、台地區的資金佔有相當程度的地位，主要原因為地理位置與中國大陸相近、文化相似度高有很大的關係，但隨著中國大陸實施改革開放政策以來，這種狀況開始有所改變，愈來愈多的大型跨國公司前進中國大陸，觀察這十年流入中國大陸的外人直接投資加總，來自香港、日本、美國和韓國的投資金額分別位居一、二、三和四名，故其造成的後續效應不容小覷。 　　本研究以中華人民共和國國家統計局進行年度工業企業數據庫的1998-2006年間的製造業廠商資料，利用STATA統計軟體進行橫斷面資料分析，再依照中華人民共和國國家統計局工業分類和黃志聰、高安邦和陳子芸(2003)的分類方法，將中國大陸製造業分成輕工業、重工業、化學工業和高科技產業，研究針對外人直接投資進度中國大陸後，衍生出產業技術外溢效果和生產效率的改變進行討論。 / With economic globalization, foreign direct investment has become a major international technology diffusion channels. The spillover effect has become an important topic under foreign direct investment, especially using their advanced technology for productivity upgrade. It is committed to developing countries to attract foreign direct investment a strong incentive to invest. The capital from Hong Kong, Macao and Taiwan plays an important role in China, mainly because of the highly correlative location, culture and language. The situation has changed accompanied by the implementation of the reform and open policy in China. More and more large multinational enterprises enter China. According to the sum of foreign direct investment of China within a decade, the investment amount from Hong Kong, Japan, America and Korea come in the first, second, third and forth places. Therefore, the upcoming effects cannot be underestimated. In this study, The manufacturers database of the annual industrial enterprises from National Bureau of Statistics of China in the period of 1998 to 2006 is used for cross-sectional data analysis of STATA statistical software. And then according to the classification of National Bureau of Statistics industry and Huang, Kao and Chen (2003), the manufacturing sector in China is divided into light industry, heavy industry, chemical industry and high-tech industries. This study discusses the change of spillover effects and production efficiency after the entering of foreign direct investment in China.

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。

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。

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.

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.

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.

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。