(34.204.200.74) 您好!臺灣時間:2020/01/22 02:31
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果

詳目顯示:::

我願授權國圖
本論文永久網址: 
line
研究生:李東杰
研究生(外文):Tung Chieh Lee
論文名稱:臺灣製造業中小企業考量地區特性影響下技術效率與生產力的變化:隨機性統計邊界法與資料包絡分析法之比較
論文名稱(外文):Incorporating area characteristic influence on technical efficiency and productivity change in Taiwan''s small and medium manufacturing enterprises:A comparison of Stochastic Statistical Frontier Approach and Data Envelopment Analysis
指導教授:李文福李文福引用關係
指導教授(外文):Win Fu Lee
學位類別:博士
校院名稱:東吳大學
系所名稱:經濟學系
學門:社會及行為科學學門
學類:經濟學類
論文出版年:2001
畢業學年度:89
語文別:中文
論文頁數:189
中文關鍵詞:技術效率生產力變化外部操作環境資料包絡分析法隨機性統計邊界法地區特性製造業中小企業
外文關鍵詞:technical efficiencyproductivity changeexternal operating environmentData Envelopment AnalysisStochastic Statistical Frontier Approacharea characteristicssmall and medium manufacturing enterprises
相關次數:
  • 被引用被引用:28
  • 點閱點閱:511
  • 評分評分:系統版面圖檔系統版面圖檔系統版面圖檔系統版面圖檔系統版面圖檔
  • 下載下載:131
  • 收藏至我的研究室書目清單書目收藏:6
除勞動、資本等內部管理投入外,外部操作環境也會影響廠商生產績效,而外部環境的影響有其重要的政策涵義;因此本文首先從理論層面探討應用資料包絡分析法(DEA)與隨機性統計邊界法(SFA)時,如何將外部操作環境對績效的影響抽離出來,以獲得管理面的技術效率與生產力。本文進而以臺灣製造業中小企業為例,以不同的衡量模型實證研究各縣市之管理技術效率與生產力之相對表現。
囿於資料的限制,本文所選取的廠商外部操作環境僅包括四個面向:公路密度、工業用土地面積、高中以上程度人數、環保稽查人數,通稱為各縣市之地區特性變數。管理技術效率衡量則包括三個模型:DEA-FSY、SFA-ONE、SFA-FSY。DEA-FSY為Fried, Schmidt, and Yaisawarng (FSY, 1999)所提的考量外部操作環境變數下的無母數DEA方法;SFA-ONE為效率文獻中所指的一階段中立性母數隨機邊界法;SFA-FSY則為本文仿照FSY修正資料之程序所提出的母數隨機性邊界法。製造業實證資料係利用民國七十五年、八十年、及八十五年之工業普查資料,依縣市別(惟不含澎湖縣)整理成2欄位產業資料。
主要實證結果為:
1.在大部份產業上,上述剔除地區特性影響後的各模型中,SFA-ONE與SFA-FSY(即同為有母數方法比較)所得到的各縣市技術效率與生產力變化之排名,頗為一致;但SFA-ONE與DEA-FSY間、及SFA-FSY與DEA-FSY間 (即有母數與無母數方法間比較)所得到的各縣市之技術效率(或生產力變化)排名,則在一些產業上並不一致。
2.然而在大部份產業上,剔除地區特性影響後有關技術效率與生產力變化之變動幅度與方向,無母數方法(即DEA與DEA-FSY)間之比較均較有母數方法(即SFA分別與SFA-ONE、SFA-FSY間之比較)有明顯差異,原因可能是無母數衡量方法雖已摒除地區特性之影響,但卻仍受如氣候、地形等社會外部因素之影響,然而在有母數衡量方法上則連社會外部因素之影響亦均排除。
3.就各產業的技術效率受地區特性影響而言,在較科技性產業上僅電力及電子機械器材製造修配業在南部區域明顯較有利;在較污染性產業中則以化學材料製造業在西部各區域明顯受不利的影響。
4.就各產業的生產力變化受地區特性影響而言,在較科技性產業上機械設備製造修配業在各區域均受有利影響,而電力及電子機械器材製造修配業則除中部區域外,亦均受有利影響;在較污染性產業中,則以金屬製品製造業在西部各區域均受不利影響,而紡織業則除中部區域外,在其餘區域亦均受不利影響。
5.若上述地區特性之影響對產業如屬有利,則表該產業適於該縣市發展,但廠商須加強其PTE(純粹技術效率)與TFPch(總要素生產力變動);如屬不利影響,則可擬定改善地區特性之措施以增強該縣市廠商之PTE與TFPch。
6.在摒除地區特性影響前之排名方面,就PTE而言,中部地區與東部地區的縣市排名大致較佳,南部地區較差;就TFPch而言,則並無任何縣市的排名上均能名列前矛,但名次大致均落在後面者則為基隆市。
7.在摒除地區特性影響後之PTE排名上,並未改變位居較優與較差之縣市順序,仍是以臺北縣居冠,臺中縣其次,臺東縣、花蓮縣分居三、四名;而排名在後的縣市則仍為屏東縣、宜蘭縣;在摒除地區特性影響後之TFPch排名上,亦無任何縣市均能名列前矛,但名次大致均落在後面者則改為苗栗縣。因此由各縣市在摒除地區特性影響前後TFPch的排名變動情況,可知若某產業的排名呈上升(或下降),則表該縣市在此產業上之廠商相對其他縣市,是更具有(或不具有)競爭優勢。
Besides the internal controllable factors such as labor and capital, the external operating environment could influence the ability of the firm to transform inputs into outputs, and hence the effects of the external operating environment on firm’s performance has important policy implications. Therefore, the paper aims to study how to theoretically measure managerial technical efficiency and productivity by incorporating the exogenous environment characteristics under Data Envelopment Analysis (DEA) and Stochastic Statistical Frontier Approach (SFA). Furthermore, the paper empirically analyzes the technical efficiency and productivity of small and medium-sized manufacturing enterprises across prefectures and cities in Taiwan.
Being subject to the data availability, the paper only includes four area environment characteristics: highway density, lands available for industrial use, population with senior high school and above, and the official employees for environment protection. Managerial technical efficiency is measured and compared by three models: DEA-FSY, SFA-ONE, and SFA-FSY. DEA-FSY is a nonparametric DEA model proposed by Fried, Schmidt, and Yaisawarng (FSY, 1999); SFA-ONE is one-stage parametric neutral stochastic frontier approach (Battese and Coelli, 1995), and SFA-FSY proposed here adopts SFA and the application of FSY to adjust output data. The data used here is the panel data at two-digit industrial level as well as prefectures and cities level, which are compiled from the Industry, Commerce, and Service Census for the years 1986, 1991 and 1996.
The main empirical results are as follows:
1.In most industries, the two parametric models SFA-ONE and SFA-FSY produce the similar technical efficiency and productivity change rankings of prefectures and cities. But in some industries, the similarity does not exist between parametric and nonparameric models, i.e. between SFA-ONE and DEA-FSY or between SFA-FSY and DEA-FSY.
2.The rate and the direction of changes in technical efficiency and productivity change between the nonparametric models DEA and DEA-FSY are more significant than those between the parametric models SFA and SFA-ONE or between SFA and SFA-FSY. The reason for the difference may be that the nonparametric models incorporate area characteristics, but they still don''t account for the influence of some society external factors such as climate, topography and etc., while the parametric models incorporate area characteristics and society external factors into consideration.
3.As for the effect of area characteristics on technical efficiency, it is significantly favorable to the Electrical & Electronic Machinery Industry among technological intensive industries in southern Taiwan, while it is significantly unfavorable to the Chemical Matter Manufacturing Industry among pollution industries in western Taiwan.
4.As for the effect of area characteristics on productivity change, it is significantly favorable to the Machinery & Equipment Industry in all areas, and to the Electrical & Electronic Machinery Industry in all areas except central Taiwan. But it is unfavorable to the Fabricated Metal Products Industry in all areas except eastern Taiwan, and so it is to the Textile Mill Products Industry in all areas except central regions.
5.If the influence of area characteristics on technical efficiency or productivity change is favorable to an industry in a region, it indicates that the region has gained the advantage to further develop the industry. But if it is unfavorable, the local government has to improve the external operating environment for the firms to gain greater competitiveness.
6.Without incorporating the influence of area characteristics, the central and eastern regions are ranked better in technical efficiency in the three periods, but the southern region is ranked worse. As for productivity change, no prefectures or cities are ranked top throughout all periods, but Keelung City is almost in the lowest position over the periods.
7.With the incorporation of area characteristics, the technical efficiency ranking of prefectures and cities remains the same both in front and at the back of the ranking. Specifically, Taipei Prefecture, Taichung Prefecture, Taitung Prefecture, and Hualien Prefecture are ranked top, and Pingtung Prefecture, Ilan Prefecture are ranked low. As for productivity change ranking, Miaoli Prefecture becomes the lowest one. If the productivity change ranking is falling or rising for a specific industry, the firms of the industry become less or more competitive in the prefectures or cities.
封面
第一章 緒論
1.1 研究動機與目的
1.2 研究方法
1.3 資料說明
1.3.1 產出,投入項說明
1.3.2 研究時點與期間說明
1.3.3 製造業中小企業定義
1.3.4 有關產業說明
1.4 本文架構
第二章 相關理論介紹與文獻回顧
2.1 衡量技術效果之有關方法介紹
2.1.1 有母數邊界函數法
2.1.1 無母數邊界法
2.2 衡量生產力變化之有關方法介紹
2.3 臺灣製造業中小企業技術效率,生產力變化實證文獻
2.3.1 技術效率之實證文獻
2.3.2 生產力變化之實證文獻
2.3.3 有母數與無母數衡量方法間比較之實證文獻
第三章 實證模型
3.1 技術效率之實證模型
3.1.1 FSY之修正DEA程式法
3.1.2 一楷段中立性隨機邊界法
3.2.3 隨機性邊界法依FSY之修正程式
3.2 生產力變化之實證模型
3.2.1 總要素生產力變動指數之衡量
3.2.1.1 一楷段中立性隨機邊界法
3.2.1.2 隨機性邊界法依FSY之修正程式
3.2.2 Malmquist生產力變動指數之衡量
3.2.3 考量地區特性影響前後之生產力變動指數間的關係
第四章 實證結果
4.1 生產函數特性之資料評估
4.2 各種衡量技術效率,生產力變化之方法間的比較
4.2.1 隨機性統計邊界法(SFA)與資料包絡分析法(DEA)之比較
4.2.2 摒除地區特性影響下,DEA-FSY,SFA-ONE,及SFA-FSY之比較
4.2.2.1 各產業有關地區特性對產出無效率之影響
4.2.2.2 摒除地區特性影響後之三種衡量方法間的比較
4.2.2.3 小結
4.2.3 考量地區特性影響前後之衡量方法間的比較
4.2.3.1 有母數衡量方法
4.2.3.2 無母數衡量方法:DEA與DEA-FSY間之比較
4.3 地區特性對技術效率與生產力變化之影響效果分析
4.3.1
4.3.2 各縣市間之比較
4.3.3 各縣市地區特性對產業之利比弊影響
4.3.4 各縣市廠商之競爭力分析
第五章 結論
5.1 結論
5.2 建議
5.3 本文未來之研究方向
附錄一
附錄二
附錄三
參考文獻
一、英文部份:
Abramovitz, M.(1956), “Resource and Output Trends in the U.S. since 1870”, American Economic Review, 46, 5-23.
Afriat, S. N.(1972), “Efficiency Estimation of Production Functions”, International Economics Review, 13, 568-598.
Aigner, D. J. and S. F. Chu(1968), “On Estimating the Industry Production Function”, American Economic Review, 58, 826-839.
Aigner, D. J., C. A. K. Lovell and P. Schmidt(1977), “Formulation and Estimation of Stochastic Frontier Production Models”, Journal of Econometrics, 6, 21-37.
Ali, A. I., W. D. Cook and L. M. Seiford(1991), “Strict vs. Weak Ordinal Relations for Multipliers in Data Envelopment Analysis”, Management Science, 37, 733-738.
Banker, R. D., A. Charnes, and W. W. Cooper(1984), “Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis”, Management Science, 30, 1078-1091.
Banker, R. D., A. Charnes, W. W. Cooper and A. Maindiratta(1988), “A Comparison of DEA and Translog Estimates of Production Frontiers Using Simulated Observations from a Known Technology”, edited by A. Dogramaci and R. Fare, Applications of Modern Production Theory:Efficiency and Productivity, Boston:Kluwer Academic Publishers.
Banker, R. D., R. F. Conrad and R. P. Strauss(1986), “A Comparative Application of Data Envelopment Analysis and Translog Methods:An Illustrative Study of Hospital Production”, Management Science, 32, 31-44.
Battese, G. E. and T. J. Coelli(1988), “Prediction of Firm-Level Technical Efficiencies with a Generalized Frontier Production Function and Panel Data”, Journal of Econometrics, 38, 387-399.
Battese, G. E. and T. J. Coelli(1992), “Frontier Productions, Technical Efficiency and Panel Data : With Application to Paddy Farmers in India”, Journal of Productivity Analysis, 3, 153-169.
Battese, G. E. and T. J. Coelli(1993), “A Stochastic Frontier Production Function Incorporating a Model for Technical Inefficiency Effects”, Working Papers in Econometrics and Applied Statistics No.69. Department of Econometrics, University of New England, Armidale.
Battese, G. E. and T. J. Coelli(1995), “A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data”, Empirical Economics, 20, 325-332.
Bauer, P. W.(1990a), “Recent Developments in the Econometric Estimation of Frontiers”, Journal of Econometrics, 46, 39-56.
Bauer, P. W.(1990b), “Decomposing TFP Growth in the Presence of Cost Inefficiency, Nonconstant Returns to Scale, and Technological Progress”, Journal of Productivity Analysis, 1, 287-299.
Bjurek H., L. Hjalmarsson and F. R. Forsund(1990), “Deterministic Parametric and Nonparametric Estimation of Efficiency in Service Production:A Comparison”, Journal of Econometrics, 46, 213-227.
Bruch, M. and U. Hiemenz(1984), Small - and Medium - Scale Industries in the ASEAN Countries, Boulder:Westview Press.
Byrnes, P., R. Fare and S. Grosskopf(1984), “Measuring Productive Efficiency:An Application to Illinois Strip Mines”, Management Science, 30, 671-681.
Caves, D., L. Christensen and W. E. Diewert(1982a), “The Economic Theory of Index Numbers and the Measurement of Input, Output, and Productivity”, Econometrica, 50, 1393-1414.
Caves, D., L. Christensen and W. E. Diewert(1982b), “Multilateral Comparisons of Output, Input, and Productivity Using Superlative Index Numbers”, Economic Journal, 92, 73-86.
Charnes, A., W. W. Cooper and E. Rhodes(1978), “Measuring the Efficiency of Decision Making Units”, European Journal of Operational Research, 2, 429-444.
Charnes, A., W. W. Cooper, A. Y. Lewin and L. M. Seiford(1994), Data Envelopment Analysis:Theory,Methodology,and Application, Kluwer Academic Publishers, 438-468.
Chen, T. J. and D. P. Tang(1987), “Comparing Technical Efficiency between Import-Substitution-Oriented and Export-Oriented Foreign Firms in a Developing Economy”, Journal of Development Economics, 26, 277-289.
Christensen, L. R. and D. W. Jorgenson(1970), “U.S. Real Product and Real Factor Input, 1929-1967”, Review of Income and Wealth, 16, 19-50.
Coelli, T. J.(1996), “A Guide to FRONTIER Version 4.1:A Computer Program for Stochastic Frontier Production and Cost Function Estimation”, Centre for Efficiency and Productivity Analysis, University of New England, Armidale.
Cooper, W. W., S. Kumbhakar, R. M. Thrall and X. Yu(1995), “DEA and Stochastic Frontier Analyses of the 1978 Chinese Economic Reforms”, Socio-Economic Planning Sciences, 29, 85-112.
Corbo, V. and J. de Melo(1983), “Technical Efficiency in a Highly Protected Economy:Preliminary Results for the Chilean Manufacturing Sector 1967”, Working Paper, World Bank.
Corbo, V. and J. de Melo(1988), “A Comparisons Alternative Methodologies with Census Data”, edited by A. Dogramaci, Measurement Issues and Behavior of Productivity Variables, Boston:Kluwer Nijhoff Publishing.
Cornwell, C., P. Schmidt and R. C. Sickles(1990), “Production Frontiers with Cross-Section and Time-Series Variation in Efficiency Levels”, Journal of Econometrics, 46, 185-200.
Denny, M., M. A. Fuss and L. Waverman(1981), “The Measurement and Interpretation of Total Factor Productivity in Regulated Industries, with an Application to Canadian Telecommunications”, in T. Cowing and R. Stevenson, eds., Productivity Measurement in Regulated Industries, New York:Academic Press, 172-218.
Deprins, D.(1989), Estimationde Frontiers de Production et Mesure de l''Efficacite Technique, Universite Catholique de Louvain, Faculte des Sciences Economiques, Sociales et Politiques, Nouvelle Serie No.186. Louvain-la-Neuve, Belgium:CIACO.
Divisia, F.(1926), L''indice Monetaire et la Theorie de la Monnaie, Sirey, Paris : Societe Anonyme du Recueil.
Dhawan, R. and G. Gerdes(1997), “Estimating Technological Change Using a Stochastic Frontier Production Function Framework:Evidence from U.S. Firm-Level Data”, Journal of Productivity Analysis, 8, 431-446.
Domar, E. D.(1961), “On Measurement of Technological Change”, Economic Journal, 71, 709-721.
Dong, X. Y. and L. Putterman(1997), “Productivity and Organization in China''s Rural Industries : A Stochastic Frontier Analysis”, Journal of Comparative Economics, 24, 181-201.
Fare, R., S. Grosskopf, B. Lindgren and P. Roos(1989), “Productivity Developments in Swedish Hospitals:A Malmquist Output Index Approach”, Discussion Paper 89-3, Department of Economics, Southern Illinois University, Carbondale.
Fare, R., S. Grosskopf and C. A. K. Lovell(1994), Production Frontiers, Cambridge University Press.
Fare, R., S. Grosskopf, M. Norris and Z. Zhang(1994), “Productivity Growth, Technical Progress, and Efficiency Change in Industrialized Countries”, American Economic Revies, 84(1),66-83.
Fare, R., S. Grosskopf and W. F. Lee(1995), “Productivity in Taiwanese Manufacturing Industries”, Applied Economics, 27, 259-265.
Fare, R. and S. Grosskopf(2000), “Research Note. Decomposing Technical Efficiency with Care”, Management Science, 46, 167-168.
Farrell, M. J.(1957), “The Measurement of Productive Efficiency”, Journal of the Royal Statistical Society, 120, 253-281.
Fisher, I.(1922), The Making of Index Numbers, Boston and New York:Houghton Mifflin.
Forsund, F. R.(1992), “A Comparison of Parametric and Non-Parametric Efficiency Measures:The Case of Norwegian Ferries”, Journal of Productivity Analysis, 3, 25-43.
Forsund, F. R., C. A. K. Lovell and P. Schmidt(1980), “A Survey of Frontier Production Functions and of Their Relationship to Efficiency Measurement”, Journal of Econometrics, 13, 5-25.
Fried, H. O., C. A. K. Lovell and S. S. Schmidt(1993), The Measurement of Productive Efficiency:Techniques and Applications, New York, Oxford:Oxford University Press.
Fried, H. O., S. S. Schmidt and S. Yaisawarng(1999), “Incorporating the Operating Environment Into a Nonparametric Measure of Technical Efficiency”, Journal of Productivity Analysis, 12, 249-267.
Giokas, D.(1991), “Bank Branch Operating Efficiency:A Comparative Application of DEA and the Loglinear Model”, OMEGA, 19, 549-557.
Golany, B. and S. Thore(1997), “The Economic and Social Performance of Nations:Efficiency and Returns to Scale”, Socio-Economic Planning Sciences, 31, 191-204.
Gong, B. H. and R. C. Sickles(1992), “Finite Sample Evidence on the Performance of Stochastic Frontiers and Data Envelopment Analysis Using Panel Data”, Journal of Econometrics, 51, 259-284.
Greene, W. H.(1982), “Maximum Likelihood Estimation of Stochastic Frontier Production Models”, Journal of Econometrics, 18, 285-289.
Greene, W. H.(1990), “A Gamma Distributed Stochastic Frontier Model”, Journal of Econometrics, 46, 141-163.
Grosskopf, S.(1986), “The Role of the Reference Technology in Measuring Productive Efficiency”, Economic Journal, 96, 499-513.
Hausman, J. A. and W. E. Taylor(1981), “Panel Data and Unobservable Individual Effects”, Econometrica, 49, 1377-1399.
Hjalmarsson, L., S. C. Kumbhakar and A. Heshmati(1996), “DEA, DFA and SFA:A Comparison”, Journal of Productivity Analysis, 7, 303-327.
Ho, S. P. S.(1980), “Small-Scale Enterprises:Korea and Taiwan”, World Bank Staff Working Paper, No.384, Washington, D.C.
Huang, C. J. and J. T. Liu(1994), “Estimation of a Non-Neutral Stochastic Frontier Production Function”, Journal of Productivity Analysis, 5, 171-180.
Huang, Z. and S. X. Li(1996), “Dominance Stochastic Models in Data Envelopment Analysis”, European Journal of Operational Research, 95, 390-403.
Hulten, C.R.(1979), “On the Importance of Productivity Change”, American Economic Review, 61, 126-136.
Jondrow, J., C. A. K. Lovell, I. S. Materov and P. Schmidt(1982), “On the Estimation of Technical Inefficiency in the Stochastic Frontier Production Function Model”, Journal of Econometrics, 19, 233-238.
Kendrick, J. W.(1961), Productivity Trends in the United States, Princeton : Princeton University Press.
Kendrick, J. W.(1973), Postwar Productivity Trends in the United States 1948-1969, New York: National Bureau of Economic Research.
Land, K. C., C. A. K. Lovell and S. Thore(1993), “Chance-Constrained Data Envelopment Analysis”, Managerial and Decision Economics, 14, 541-554.
Land, K. C., C. A. K. Lovell and S. Thore(1994), “Productive Efficiency under Capitalism and State Socialism:An Empirical Inquiry Using Chance-Constrained Data Envelopment Analysis”, Technological Forecasting and Social Change, 46, 139-152.
Lee, L. F. and W. G. Tyler(1978), “The Stochastic Frontier Production Function and Average Efficiency”, Journal of Econometrics, 7, 385-389.
Leibenstein, H.(1966), “Allocative Efficiency vs. ‘X-Efficiency”, American Economic Review, 56, 392-415.
Liang, C. Y.(1995), “Productivity Growth in Asia NIEs:A Case Study of the Republic of China, 1961-93”, APO Productivity Journal, Winter, 17-40.
Lovell, C. A. K.(1993), “Production Frontier and Productive Efficiency”, Measure of Productivity Efficiency, Oxford University Press.
Lovell, C. A. K.(1996), “Applying Efficiency Measurement Techniques to the Measurement of Productivity Change”, Journal of Productivity Analysis, 7, 329-340.
Maddison, A.(1987), “Growth and Slowdown in Advanced Capitalist Economies:Techniques of Quantitative Assessment”, Journal Economic Literature, xxv, 649-698.
Nishimizu, M. and J. M. Page, Jr.(1982), “Total Factor Productivity Growth, Technological Progress and Technical Efficiency Change:Dimensions of Productivity Change in Yugoslavia, 1965-1978”, Economic Journal, 92, 920-936.
Norsworthy, J. R. and D. H. Malmquist(1983), “Input Measurement and Productivity Growth in Japanese and U.S. Manufacturing”, American Economic Review, 73, 947-967.
Olesen, O. B. and N. C. Petersen(1995), “Chance Constrained Efficiency Evaluation”, Management Science, 41, 442-457.
Pitt, M. M. and L. F. Lee(1981), “The Measurement and Sources of Technical Inefficiency in the Indonesian Weaving Industry”, Journal of Development Economics, 9, 43-64.
Richmond, J.(1974), “Estimating the Efficiency of Production”, International Economic Review, 15, 515-521.
Schmidt, P.(1976), “On the Statistical Estimation of Parametric Frontier Production Functions”, Review of Economics and Statistics, 58, 238-239.
Schmidt, P. and R. C. Sickles(1984), “Production Frontiers and Panel Data”, Journal of Business and Economic Statistics, 2, 367-374.
Schmidt, P.(1985-86), “Frontier Production Functions”, Econometric Reviews, 4, 289-328.
Seiford, L. M. and R. M. Thrall(1990), “Recent Developments in DEA:The Mathematical Programming Approach to Frontier Analysis”, Journal of Econometrics, 46, 7-38.
Sharma, K. R., P. Leung and H. M. Zaleski(1997), “Productive Efficiency of the Swine Industry in Hawaii:Stochastic Frontier vs. Data Envelopment Analysis”, Journal of Productivity Analysis, 8, 447-459.
Shephard, R. W.(1970), Theory of Cost and Production Functions. Princeton, N. J.:Princeton University Press, 206.
Solow, R.(1957), “Technical Change and the Aggregate Production Function”, Review of Economics and Statistics, 39, 312-320.
Staley, E. and R. Morse(1965), Modern Small Industry for Developing Countries, New York:McGraw-Hill.
Stevenson, R. E.(1980), “Likelihood Functions for Generalized Stochastic Frontier Estimation”, Journal of Econometrics, 13, 57-66.
Storey, D. J.(1994), Understanding the Small Firm Sector, London:Reutledge.
Taymaz, E. and G. Saatci(1997), “Technical Change and Efficiency in Turkish Manufacturing Industries”, Journal of Productivity Analysis, 8, 461-475.
Timmer, C. P.(1971), “Using Probabilistic Frontier Production Function to Measure Technical Efficiency”, Journal of Political Economy, 79, 776-794.
Tornqvist, L.(1936), “The Bank of Finland’s Consumption Price Index”, Bank of Finland Monthly Bulletin, 10, 1-8.
Waldman, D.(1978), Estimation in Economic Frontier Functions, University of Wisconsin, Madison, WI.
Weinstein, M. A.(1964), “The Sum of Values from a Normal and a Truncated Normal Distribution”, Technometrics, 6, 104-105 (with some additional material, 469-470).
Young, A.(1995), “The Tynanny of Numbers:Confronting the Statistical Realities of the East Asian Growth Experience”, Quarterly Journal of Economics, 110, 641-680.
Zellner, A., J. Kmenta and J. Dr'eze(1966), “Specification and Estimation of Cobb-Douglas Production Functions”, Econometrica, 34, 784-795.
二、中文部份:
李文福(1991a), 產業多因素生產力指數編製方法之研究, 行政院主計處編印。
李文福(1991b), 臺灣製造業總要素生產力、技術進步與技術效率, 華泰書局, 初版。
李文福(1997), 臺灣製造業生產力成長、技術進步與效率變動:Malmquist生產力指數與資料包絡分析之應用, 行政院國家科學委員會專題研究計畫成果報告。
官俊榮(1991), “中小企業的合理發展”, 經社法制論叢, 7, 225-245。
林安樂,王素彎,與邱淑君(1998), 臺灣經濟總要素生產力與競爭力分析, 經濟建設委員會86/87年度委託專案計畫期終報告, 14-25。
吳惠林(1985), “臺灣地區生產力衡量之檢討”, 企銀季刊, 9:1, 58-65。
吳惠林與藍科正(1995), “臺灣的勞動品質提高對勞動生產力的影響”, 臺灣經濟, 222, 1-33。
吳惠林,馬凱,林志誠,王素彎,鄭凱方,與葉新興(1998), 我國中小企業統計資料的整建與經營現況分析, 經濟部中小企業處委託中華經濟研究院。
吳銘國(1997), 非中立隨機邊界模型之技術效率---以僑外資電子業(1975-1994)panel data為例, 中央大學產業經濟研究所碩士論文。
胡名雯(1991), 臺灣製造業中小企業之研究, 臺灣大學經濟學研究所博士論文。
胡名雯與陳宜亨(1996), “臺灣地區中小企業生產技術之規模報酬的初步探討”, 企銀季刊,1 9:3, 49-72。
胡名雯與薛琦(1997), “中小企業生產特性與效率之研究:臺灣製造業之分析”, 經濟論文叢刊, 25 : 1, 1-26。
黃旭男(1993), 資料包絡分析法使用程序之研究及其在非營利組織效率評估上之應用, 交通大學管理科學研究所博士論文。
黃旭男(2000), “Using Data Envelopment Analysis to Measure the Achievement and Change of Regional Development in Taiwan”, 中研院經研所、中央大學產經所、成功大學管理學院主辦「生產力與效率衡量研習會」。
黃寶祚(1995), “臺灣農業多因素生產力衡量之探討”, 農業經濟叢刊, 1:2, 255-282。
陳添枝與王文娟(1990), “生產配額與生產效率:臺灣洋菇、蘆筍、鳳梨罐頭聯合產銷的實證分析”, 經濟論文叢刊, 18 : 2, 213-231。
陳忠榮,劉錦添,與孫佳宏(1995), “中小企業與大企業技術效率之估計與比較:臺灣電子業四欄位產業之實證研究”, 淡江大學產業經濟研究所研討會論文。
彭作奎與吳江湖(1986), “臺灣牛乳生產之技術效率與其影響因素之分析”, 農業金融論叢, 29-38。
張瑞晃(1998), 臺灣地區產業結構變遷與生產力解析, 東吳大學經濟學研究所博士論文。
傅祖壇與詹滿色(1990), “臺灣記帳農場之隨機性生產邊界及技術效率分析”, 臺灣土地金融季刊, 27:3, 125-142。
傅祖壇與詹滿色(1991), “記帳農場之技術效率及差異來源探討”, 中央研究院經濟研究所, 研討論文8001。
傅祖壇,詹滿色,與劉錦添(1992), “生產邊界估計方法、函數型式與個別農場技術效率---台灣稻作與果樹農場之實證”, 經濟論文叢刊, 20 : 2, 129-153。
曾美萍(1992), 臺灣大企業與中小企業生產行為之比較, 政治大學國際貿易研究所碩士論文。
甯正文(1996), 中國大陸鄉鎮企業經濟效率評估---資料包絡分析法(DEA)之應用, 中山大學大陸研究所碩士論文, 39-41。
楊永列(2000), “科學園區廠商/DEA&EF”, 中研院經研所、中央大學產經所、成功大學管理學院主辦「生產力與效率衡量研習會」。
蔡慧美(1995), 大陸家電工業生產函數及技術效率之評估─隨機邊界模型之應用, 中華經濟研究院經濟專論(166)。
劉錦添與蔡偉德(1989), “隨機性邊界生產函數與技術效率之推估─臺灣地區僑外資廠商之實證研究”, 中國經濟學會年會論文集, 205-245。
劉錦添與徐瑞玲(1992), “臺灣製造業技術效率之實證分析”, 中央研究院經濟研究所, 研討論文8101。
劉錦添(1995), “臺灣製造業技術效率之實證研究”, 經濟論文叢刊, 23 : 2, 449-469。
劉邦典(1989), “整體經濟生產力成長的產業解析分析”, 經濟論文叢刊,17:1, 121-156。
劉天賜與苗坤齡(1995), “臺灣地區產業多因素生產力衡量之探討”, 臺灣經濟, 217, 15-38。
薛琦與周治邦(1984), “Farrell衡量效率之方法與臺灣的實證分析”, 中國經濟學會民國七十三年論文集, 203-226。
賴永梁(1986), 生產效率之衡量與應用, 政治大學財政研究所碩士論文。
蘇莉萍(1994), 市場導向與生產效率---臺灣製造業的實證研究, 臺灣大學經濟學研究所碩士論文。
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top
1. 王木榮(民88)。影響山地學童學業成就因素之研究。原住民教育研究,第二期,頁161-180。
2. 任秀媚(民75)。山地單語與山地雙語兒童語文能力及智力之比較研究。新竹師專學報,第十三期,頁193-208。
3. 李坤崇、邱美華(民80)。國中國小學生學習適應之個人因素探討。輔導月刊,27期3、4卷,頁8-20。
4. 李建興(民85)。台灣地區原住民教育現況與展望。原住民教育季刊,第二期,頁3-19。
5. 李瑛(民87)。原住民成人學習者學習特性與教學策略之探討─以「原住民成人教育工作者培訓計畫」為例。社會教育學刊,27期,頁129-160。
6. 呂枝益(民89)。教科書中族群偏見的探討與革新。原住民教育季刊,第17期,頁34-51。
7. 吳幼妃(民70)。不同成就動機兒童人格特質及社會適應比較研究。教育學刊,第三期,頁111-160。
8. 吳裕益(民69)。國中高、低成就學生家庭背景及心理特質之比較研究。國立高雄師範學院教育學系及教育研究所教育學刊,第二期,頁161-98。
9. 周天賜、吳武典(民69)。國中文化貧乏學生身心特質之調查研究。中國測驗學會測驗年刊,第27輯,頁9-22。
10. 胡永寶(民84)。原住民學生學習現況調查研究。國教園地,第51、52期,頁54-71。
11. 洪麗晴、高淑芳(民87)。原住民與非原住民國小學童的推理表現差異性之分析。原住民教育季刊,第十期,頁1-27。
12. 徐光國(民83)花蓮縣社會不利背景學童學業與行為適應及其輔導效果。社會科教育學報,第2期,頁97-137。
13. 高淑芳、何秀珠(民86)。桃竹苗地區山地國小學童之家庭環境、學習概況、行為困擾調查研究─訪視當地資深教師。原住民教育季刊,第五期,頁17-38。
14. 陳英豪、林正文、李坤崇(民78)。國小學生學習適應量表編製報告。測驗年刊,36輯,頁1-12。
15. 陳英豪、汪榮才、李坤崇(民82)。學習心事誰人知?:國中國小學生學習適應及其相關因素之比較研究。國教之友,第44卷第3期,頁5-14。
 
系統版面圖檔 系統版面圖檔