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.

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.

臺灣於1990年放寬銀行設立的限制後，本國銀行和外商銀行的數目快速增加，使得金融市場更加競爭，因此銀行的經營績效是個重要的議題，銀行可透過績效的評估結果找出可能的改善方向。本國銀行與外商銀行的進入條件、經營形態、銀行制度等因素可能使得兩種類型的銀行生產技術有所不同，因此本研究採用全域共同邊界法研究37家本國銀行與20家外商銀行在2005-2015年間效率與生產力的分析，並採用變動規模的方式拆解Malmquist生產力指數，使得生產力變動來源能更精準地衡量。最後使用Tobit迴歸分析找出影響銀行技術效率、最佳實務差距和技術差距比率之因素。 / Since Taiwan relaxed the restriction of setting up a bank in early 1990s, the number of both domestic and foreign banks in Taiwan had increased rapidly. This leads to the result that the financial market become more competitive. Consequently, the performance of bank is an important issue. It can be used to find some way for improvement. Due to the different entry conditions, types of operating system and bank systems between domestic and foreign banks, this paper uses global metafrontier approach to research the efficiency and productivity change of 37 domestic banks and 20 foreign banks during 2005-2015 in Taiwan. Furthermore, this research adopts VRS to decompose Malmquist productivity indexes, which makes the sources of the productivity change can be measured more accurately. Finally, Tobit regression analysis is used to investigate the factors accounting for the differences in technical efficiency, best practice gap and technology gap.

Submitted by Sandro Camargo (sandro.camargo@unipampa.edu.br) on 2015-05-09T19:30:37Z No. of bitstreams: 1 117110019.pdf: 3622835 bytes, checksum: bf885e1754a3be10513d615ebdb016c7 (MD5) / Made available in DSpace on 2015-05-09T19:30:37Z (GMT). No. of bitstreams: 1 117110019.pdf: 3622835 bytes, checksum: bf885e1754a3be10513d615ebdb016c7 (MD5) Previous issue date: 2013-11-23 / Este trabalho investiga o processo de evolução dos índices de eficiência técnica e de produtividade de Malmquist para as 30 maiores empresas distribuidoras de energia elétrica no Brasil, confrontando a metodologia do órgão regulador (Agência Nacional de Energia Elétrica – ANEEL) de avaliação dos Custos Operacionais Regulatórios do Ciclo de Revisão Tarifária Periódica, com as relações existentes entre a tecnologia de produção utilizada por estas empresas e a qualidade dos serviços prestados à sociedade, entre 2003 e 2009, aplicando-se a Análise por Envoltória de Dados (Data Envelopment Analysis – DEA). Para tanto, utilizam-se os seguintes modelos DEA, orientados para insumo: o CRS (CCR), o VRS (BCC) e o NDRS (usado pela ANEEL), que presumem tecnologias com os seguintes retornos à escala de produção: constantes, variáveis e não decrescentes, respectivamente. Sendo estes modelos DEA aplicados aos dois cenários modelados: no primeiro (chamado de C1), observam-se as variáveis quantitativas adotadas pela ANEEL, tendo como insumo o Custo Operacional – OPEX (R$) e como produtos a Extensão de Redes de Distribuição de Energia Elétrica – Rede (km), o Consumo de Energia Elétrica – Mercado (TWh) e o Número de Unidades Consumidoras de Energia Elétrica – UC (No de Clientes); no segundo (chamado de C2) são inseridas variáveis de qualidade ao cenário C1, definindo-as como produtos na modelagem DEA, citando-se o Índice ANEEL de Satisfação do Cliente – IASC (No Índice) e o Indicador de Desempenho Global de Continuidade – DGC (No Índice). Desta forma, com base nos resultados de desempenho relativo para o período analisado, identificam-se como resultados principais a tendência de evolução positiva das medidas de eficiência técnica e a tendência de estabilização das medidas de produtividade, para o conjunto das 30 maiores empresas distribuidoras de energia elétrica do país. Além disso, comparando-se os resultados de eficiência técnica e produtividade, nos diferentes cenários e nas diferentes modelagens DEA (benchmarking), verificou-se que a implementação de um cenário e de uma modelagem deve refletir a realidade econômica (aproximação com a função de produção verdadeira) das empresas distribuidoras de energia elétrica no Brasil, de modo a possibilitar a identificação das distribuidoras de energia elétrica que estão operando na escala ótima (ou não) e se os retornos à escala de produção são constantes, crescentes ou decrescentes. Assim, percebeu-se que boa parte das empresas (C1 igual a 40% e C2 igual a 50%) apresentaram retornos de escala de produção decrescentes (DRS) em todo o período de tempo analisado. Portanto, a modelagem DEA VRS apresenta-se mais adequada para a avaliação de desempenho, em detrimento da modelagem DEA NDRS usada pela ANEEL, pois admite que as empresas atuem na região decrescente da fronteira de produção e ainda assim possam ser consideradas eficientes. Já o cenário C2, ao agregar variáveis de qualidade ao Cenário C1 (ANEEL), aproxima-se também desta realidade econômica, buscada pelo órgão regulador através da mensuração dos custos operacionais regulatórios associados aos indicadores de qualidade na prestação dos serviços à comunidade. Por fim, são realizadas considerações sobre a necessidade de aprimoramento de alguns pontos na metodologia utilizada pelo regulador, representando desafios para a garantia de equidade entre a modicidade tarifária e a sustentabilidade das empresas do setor elétrico brasileiro, de modo a garantir-se, efetivamente, o equilíbrio econômico-financeiro nos próximos Ciclos de Revisão Tarifária Periódica. / This work investigates the evolution process of technical efficiency indices and Malmquist productivity for the 30 largest power utilities in Brazil, comparing the methodology of the regulator (ANEEL – National Agency of Electric Energy) of evaluation of Regulatory Operational Costs of the Periodic Tariff Review Cycle, with the relationship etween the production technology used by these companies and the quality of services provided to the society between 2003 and 2009, applying the Data Envelopment Analysis (DEA). For this, it is used the following models DEA – input oriented: CRS (CCR), the VRS (BCC) and the NDRS (used by ANEEL), assume that the following technologies returns to scale production: constants, variables, and nondecreasing, respectively. It was adopted two scenarios: the first (called C1), it was observed quantitative variables adopted by ANEEL, taking as input the Operating Cost – OPEX (R$), and as products the Extension of Distribution Networks Electricity - Network (km), the Consumption of Electricity – Market (TWh) and the Unit Number of Electric Consumers – UC (No of Customers), the second (called C2), and quality variables to the scenario C1 are inserted by defining them as products in modeling DEA, the ANEEL’s index of Customer Satisfaction - IASC (NoIndex) and Performance Indicator of Global Continuity – DGC (No Index). Thus, based on performance results relative to the analysis period, it is identified measures of technical efficiency with positive trend and productivity measures with stabilizing trend for the whole of the 30 largest power utilities in Brazil. Furthermore, comparing the results of technical efficiency and productivity in the different scenarios and different DEA modeling (benchmarking), it was found that the implementation of a scenario and a model should reflect the economic reality (closer to the function of real production) of power utilities in Brazil, in order to facilitate the identification of power utilities that are operating at optimal scale (or not) and returns to scale of production are constant , increasing or decreasing. Thus, it was noticed that most companies (C1 equal to 40% and C2 equal to 50%) showed decreasing returns to scale of production (DRS) throughout the time period analyzed. Therefore, the VRS DEA model appears more suitable for the evaluation of performance, rather than modeling the DEA NDRS used by ANEEL, since it allows companies to act in the decreasing region of production frontier and still can be considered efficient. Finally, we discuss the need to improve some points in the methodology used by the regulator, representing challenges to ensuring equity between low tariffs and sustainability of the Brazilian electricity sector, in order to guarantee effectively the economic-financial balance over the next Periodic Tariff Review Cycle.

La exposición de las contribuciones al análisis estocástico de la eficiencia técnica de este trabajo de investigación, requiere que: en el primer capítulo se definan los conceptos básicos para la comprensión de los capítulos dos y tres. Además y para la formulación de los problemas que han dado origen a este trabajo, se presenta también en este capítulo una breve revisión de las técnicas de estimación de la eficiencia técnica y de la productividad.Dentro de estas técnicas y debido a la gran flexibilidad funcional que proporciona, nos hemos centrado en la estimación no paramétrica y más en concreto en mejorar la inferencia estadística de sus estimaciones. Es por ello que el segundo de los aspectos que se trata es la inferencia estadística que se debería de efectuar en el análisis de la envolvente de datos, habitualmente denominado con el acrónimo DEA. El análisis estadístico es sistemáticamente "olvidado" en casi todos los trabajos que aplican esta técnica, y tal y como mostramos en este apartado, según se incorpore o no inferencia estadística al DEA la interpretación de los resultados es diferente. En el tercer apartado y continuando en la línea de mejorar las herramientas de inferencia estadística en el ámbito no paramétrico, presentamos un nuevo contraste basado en simetría condicional para evaluar consistentemente la ineficiencia técnica de cada uno de los productores. Este contraste relaja algunos de los supuestos funcionales de otros contrastes anteriores y a diferencia de los contrastes basados en los momentos, es consistente con todo tipo de distribuciones de la ineficiencia. / This thesis provides in the first chapter a brief review of efficiency and productivity methods. Secondly we examine how to analyze efficiency and productivity by DEA and we apply the method for the Spanish airports in the period 1992-94. Although the time period analyzed is fairly short, we study the impact of the crisis in the productivity of Spanish airports. We apply the Malmquist index since among its other advantages this ratio allows for the decomposition of total productivity changes into different sources of variation. We also use resampling methods to gain statistical precision and the bootstrap analysis yields further evidence given that for many airports efficiency and productivity is not statistically significant.In standard deterministic frontier analysis, either DEA or FDH techniques allowed to determinate inefficient units just but taking some measure between the estimated frontier and the related output. Unfortunately, when we assume that some symmetric noise is present in the data, then the previous task becomes much harder. The problem is that in this setting noise and efficiency are not identified and therefore, without an statistical tool it is impossible to decide whether a firm is efficient or not. In the third chapter we propose a test for efficiency in a stochastic nonparametric frontier analysis. Under weak conditions on the specification of the production frontier, and the null hypothesis of efficiency, we provide the asymptotic distribution of the test statistic. Furthermore we show the test is consistent against a broad set of alternatives of inefficiency. Evidence of the good properties of the test is given by a simulation study.

本文採用一階段隨機邊界分析方法，建立一多投入多產出之投入距離函數模型，衡量民國81~91年間台灣66家國際觀光旅館經營之相對技術效率，同時探討造成不效率之因素。並利用投入導向Malmquist生產力指數進一步分析國際觀光旅館產業生產力改變的原因與幅度。 整體而言，台灣國際觀光旅館產業之經營效率大致呈現緩慢進步之趨勢。造成整體產業生產力提升之原因，主要為業者對於投入產出配置使用之效率改善，而非生產技術進步。除了整體經濟景氣因素當然影響觀光產業之興衰外，個別國際觀光旅館業者之效率表現仍受到許多因素影響。諸如規模、國際化程度等內部原因，及旅館是否位處風景區、所在地縣市政府對觀光發展投注之資源預算和該地市場競爭程度等外在因素。 從政府政策方面來分析，若以整體國際觀光旅館產業經營效率來衡量我國觀光產業興衰，民國87年隔週休二日政策及民國90年實施之全面週休二日政策，的確有效帶動國人休閒旅遊之風潮，促進國內觀光發展。而各縣市政府觀光相關支出與國際觀光旅館生產力變動之關係，呈現正向相關，則表示政府支出增加有助於觀光產業蓬勃發展，並增加國際觀光旅館之經營效率。由於觀光產業生產具外部性，政府積極利用觀光產業以帶動經濟景氣繁榮成長的政策應當可行。 / In this paper a multi-output, multi-input and input oriented distance function is built by one-stage stochastic frontier approach (Battese and Coelli, 1995) to estimate the relative efficiency of the 66 international tourist hotels in Taiwan in 1992~2002 and to explore the determinants of technical efficiency. In addition, the Malmquist productivity index model is used to analyze the range and the causes of the productivity changed. The results reveal that managerial efficiency of international tourist hotel industry improves gradually. The productivity growth can be attributed to efficiency gains, but not the effects of technical progress. There are significant differences in efficiency due to difference not only in the macroeconomic situation, but also in many other individual factors, such as scale, joining an international chain, located in scenic area, local government other economic service expenditure and competitiveness. Analyzing the government policy, the implementations of two-day-off twice a month policy in 1998 and two-day-off per week policy in 2001 have fostered domestic traveling and expanded tourist hotel industry. The local government other economic service expenditure has positive effect on efficiency of international tourist hotels. That is to say, increasing in local government tourist expenditure will promote tourism market and improve efficiency of a hotel. Because of the production externality in tourism industry the idea that government tries to promote tourism to benefit economic development would be workable.

本論文對於醫療市場的生產績效研究，係由兩篇獨立的學術研究報告所組成，研究重點在於利用非參數資料包絡分析方法 ( nonparametric DEA approach )，估計醫院的生產技術，以衡量醫院的技術效率及不同年度間之生產力變動，進而分析不同醫院間，生產績效差異的主要原因。本論文所採用的研究方法與探討的主題，不同於國內既有的相關文獻。 第一部分：生產不確定性與醫院效率 本部分主要探討在醫院面對不確定性時的效率評估。一般而言，醫院有兩種生產上的不確定性來源：醫師或醫院的診療結果所導致的生產不確定性；及消費者對醫療服務需求的不確定性 (Arrow, 1963)。當醫院面對生產不確定性時，醫院效率將與廠商如何處理不確定性問題有關，亦即，當廠商事前規劃愈縝密，未來可能的產出失靈水準愈低，則其生產效率表現愈佳。本文利用民國 82 及 83 年（準）醫學中心與（準）區域醫院資料，模擬醫院在面對生產不確定性時，各種可能的產出失靈水準，以chance constrained DEA 模式 (Land, Lovell and Thore, 1993) 估算醫院的隨機技術效率，並與傳統、確定性的DEA模式所得到之結果，做一比較。 Chance constrained DEA模式與傳統DEA模式的不同，在於前者估計出的生產前緣，並不總是包絡所有的樣本點，亦即，允許某廠商之產出超越生產前緣或說允許產出失靈可能性之存在，而後者則否。實證結果發現，在chance constrained DEA模式下，私立醫院的技術效率高於公立醫院，且呈現統計顯著性的差異，但兩者間的差異隨著醫院事前準備程度的提高而縮小；而傳統DEA模式也顯示，私立醫院的技術效率確實顯著地高於公立醫院。此外，若產出失靈水準夠低，則chance constrained DEA模式的效率值與傳統DEA模式的效率值，兩者間的分配會呈現統計顯著性差異。 在面對生產不確定性時，欲提升公立醫院的生產效率，應提高廠商事先規劃的程度，才能與私立醫院之生產效率並駕齊驅。一般而言，廠商事先準備的程度高低，與醫院本身的特性有關，因此，欲改善公立醫院緩衝產能的準備程度，以降低產出失靈水準，有必要進行體制層面的改革，亦即，從進行人事變革、財務之授權與彈性化等方向開始做起，如此應可提高公立醫院的生產效率。 第二部分：全民健康保險制度與醫院生產力變動 全民健保實施後，民眾對醫療服務的可近性提高，醫院間的市場結構改變，因此，醫院生產力與效率的提升，成為眾所關切的焦點。為瞭解醫院在全民健保實施後，資源是否有效配置，本部分利用民國 82 至 86 年醫學中心、區域醫院與地區醫院等大小型醫院資料，以範疇DEA模式估計Malmquist生產力變動指標，並將之分解為技術變動、純技術效率變動、及規模效率變動等三項變動來源。 實證結果發現，從82至86年醫院整體平均效率而言，CRS（VRS）生產技術下的平均效率為 66.00%（74.87%），表示不論大小型醫院，平均而言，皆存在技術不效率的情形。再者，在民國84年，亦即全民健保實施的年度，其效率水準明顯較其他年度為低，其餘年度的效率水準都相對較高，此一結果意謂，政策干擾對於醫院效率表現的影響，是短期性的。另外，小型醫院皆較大型醫院不效率，兩者的效率差異呈現統計顯著性；以權屬別而言，不論是大型醫院或小型醫院中的私立醫院，其生產效率均優於公立醫院，且兩者的效率差異呈現統計顯著性。而透過迴歸分析顯示，全民健保實施、權屬別之虛擬變數、佔床率、平均住院日、及以醫院產出衡量的集中度指標等，是影響醫院生產效率的重要因素。 從Malmquist生產力變動（　et al., 1994）來看，平均而言，82-86年間醫院生產力成長率約在 -3.06 % 左右。就生產力變動來源而言，技術成長率（-2.74 %）與整體效率成長率（-0.33 %）均為負，而技術變動則是阻礙生產力成長的主要原因。此外，若以醫院整體效率變動來源來看，平均而言，整體效率退步是由於規模效率變動所致（-0.74%）。 此外，本文著重在　et al.(1994)、Ray and Desli (1997) 及Grifell and Lovell (1998) 三種定義下的Malmquist生產力變動指標之比較。研究結果發現，Grifell and Lovell (1998) 的一般化Malmquist生產力指數，並沒有正確衡量廠商的生產力變動及其變動來源項。而利用Kruskal-Wallis檢定結果發現，三個模式中的生產力變動差異，並不具統計顯著性，而變動來源項（技術變動與規模效率變動）亦顯示相同的結果。 / This dissertation is focused on the efficiency and productivity studies of hospitals in Taiwan. It includes two independent academic papers. The primary intention is to introduce the newly developed ideas in the measurement of efficiency and productivity, rather than to create new ones. The utilization of these ideas has not, however, been discussion in print. And some of the arguments we used and brought together are new regarding to the literature of hospital efficiency and productivity measurement. Utilizing the non-parametric data envelopment analysis (DEA) approaches, efficiency scores and productivity change indexes were estimated. Efforts were made to explain the difference of productivity performance among individual hospitals. Nevertheless, the methods we used and the economic approach behind them distinguish this study from other empirical studies of the medical market. Part I　 Market Uncertainty and Hospital Efficiency This part of the dissertation is focused on the measurement of efficiency of hospitals, incorporating uncertainty. There are stochastic variations in production relationships for hospitals. Generally speaking, the uncertainty of hospitals comes from two major sources: the natural uncertainty of medical cares; and the uncertainty of demands for medical cares (Arrow, 1963). Given the uncertainty in the medical market, the efficiency of hospitals hinges on how decision-makers deal with it. Undoubtedly, an optimal planning of the output buffers improves the efficiency performance. Using the hospital survey data in 1993 and 1994, and employing the chance constrained DEA model (Land, Lovell and Thore, 1993), the stochastic efficiency indexes of public and private medical centers and regional hospitals were estimated. Compared with deterministic frontier enveloping a given set of sample observations all the time, the chance-constrained frontier envelops them most of the time. That is, the chance constrained DEA allows the possibilities of output failure. Imposing different values of output failure probability, the estimation results were compared with the traditional (deterministic) DEA models. The empirical evidences of the chance constrained DEA model showed that, on average, private hospitals performed significantly better than public hospitals. This result matches with the result of the traditional DEA model. With Mann-Whitney U test, we compared the distributions of efficiency indexes under chance constrained DEA and deterministic DEA models. The test results showed that the difference between these two different models is statistically significant given a higher probability of output failure. These results imply that the nature of risk and the manipulation for risk are different for public and private hospitals. We also find that that the efficiency performance of public hospitals could be improved by the increasing of its reserve capacity. Part II　 National Health Insurance and Hospital Productivity Change In this part of the dissertation, we examine the impact of NHI on hospitals, and trace the sources of hospital productivity growth in Taiwan. To pursue our goal, we employ a data consisting of 157 medical centers, regional hospitals and district hospitals over the period 1993 to 1997, and resort to the Malmquist productivity index to measure total factor productivity change. The index could be decomposed into three components: technical change, pure technical efficiency change and scale efficiency change. The estimation technique used in the study is the deterministic non-parametric DEA approach. The results we find are revealing and suggestive to the public and the government in order to promote and assure the efficient delivery of quality health care. The average efficiency scores are 66.00% (74.87%) for CRS (VRS) technology and it means that there are substantial efficiency losses for the sample hospitals during the study period. The efficiency score of the hospitals as a whole in 1995 (the beginning year of NHI) was much lower than the other 4 years' efficiency scores. A censored Tobit regression analysis is used and identifies that NHI policy, ownership, rate of bed occupancy, average length of stay and the output-specific concentration level were all the significant determinants of technical efficiency. Empirical results indicate that most medical care regions became more output-specific concentrated. Total factor productivity on average deteriorated at an annual rate of -3.1%, and it was dominated by substantial technical regresses at an annual rate of -2.74%. The small hospitals were severely affected by NHI. Furthermore, within large and small hospital groups, the difference in technical change was statistically significant, but the differences in TFP and the associated components between ownership were not. Special attention was paid to compare　 et al.(1994), Ray and Desli (1997) and Grifell and Lovell (1998) approaches to decomposing the Malmquist productivity index. Empirical results indicate that the first 2 approaches yield accurate productivity changes, while GL doesn't. However, they produce almost the same magnitude of average TFP. In addition, no significant differences in the measured technical change and efficiency change were found among the three approaches.