淡江大學覺生紀念圖書館 (TKU Library)
進階搜尋


下載電子全文限經由淡江IP使用) 
系統識別號 U0002-1607200819261800
中文論文名稱 縱橫資料下隨機邊界模型之技術效率的半參數估計方法
英文論文名稱 Semiparametric Estimation Method for Stochastic Production Frontier Panel Data Model with Time-Invariant Technical Efficiency
校院名稱 淡江大學
系所名稱(中) 統計學系碩士班
系所名稱(英) Department of Statistics
學年度 96
學期 2
出版年 97
研究生中文姓名 梁永能
研究生英文姓名 Yung-Neng Liang
學號 695650183
學位類別 碩士
語文別 中文
口試日期 2007-06-13
論文頁數 35頁
口試委員 指導教授-鄧文舜
委員-黃台心
委員-林志娟
中文關鍵字 半參數隨機生產邊界模型  核估計量  技術效率  縱橫資料  組合誤差項 
英文關鍵字 Semiparametric stochastic production frontier model  Kernel estimators  Technical efficiency  Panel data  Composed error 
學科別分類 學科別自然科學統計
中文摘要 Deng 和Huang (2008) 延伸了Fan et al. (1996)所提出的橫斷面資料下的半參數隨機生產邊界模型為縱橫資料下的時間變量(time-variant)半參數隨機邊界模型,其方法容許技術效率隨時間改變。本論文參考Deng 和Huang (2008)的方法,探討的是縱橫資料下時間不變量(time-invariant)半參數隨機邊界模型,文中假定的技術效率是不會隨著時間的改變而改變,並且利用無母數迴歸的技巧來建構模型組合誤差項未知參數的估計量。經由蒙地卡羅模擬研究結果發現,本文所提出的估計方法是具有一致性(consistent),因此適合應用在隨機邊界生產函數的估計。最後採用了96間台灣電子產業公司的資料來進行實證分析。
英文摘要 Deng and Haung (2008) extend the semiparametric stochastic frontier model of Fan et al. (1996). A semiparametric estimation procedure suitable for the case when panel data are available is proposed and time varying technical efficiency allowed therein. This dissertation considers the extended model with panel data and time-invariant technical efficiency. The proposed semiparametric estimation procedure is similar to that of Deng and Huang (2008) and also provides consistent estimators of the model parameters as demonstrated by the Monte Carlo simulations. An empirical application of the proposed procedure, which employs the panel data from 96 Taiwanese electronic firms over the period 1996-2001, is carried out.
論文目次 目 錄

第一章 文獻探討 1
第一節 技術效率的定義 1
第二節 隨機邊界模型之文獻 1
第三節 研究動機與目的 4
第二章 無母數迴歸分析簡介 6
第一節 前言 6
第二節 一維度的區域常數與區域線性估計量 7
第三節 多維度的區域常數與區域線性估計量 9
第三章 研究方法 12
第四章 蒙地卡羅模擬研究 20
第五章 實證分析 28
第六章 結論 33
參考文獻 34

表目錄
表4.1 A的蒙地卡羅模擬結果 22
表4.2 A的蒙地卡羅模擬結果 23
表4.3 樣本大小對模型A的影響結果 25
表4.4 標準差比A的影響結果 26
表5.1 樣本統計量 31
表5.2 土地的邊際生產 31
表5.3 實質投入資本的邊際生產 32

圖目錄
圖5.1 函數A的估計曲面圖 29
圖5.2 96間公司技術效率之箱型圖 32


參考文獻 參考文獻
Aigner, D. J. and S. F. Chu (1968), On Estimation the Industry Production Function, American Economic Review, 58, 826-839.
Aigner, D. J., C. A. K. Lovell, and C. P. Schmidt (1977), Formulation and Estimation of Stochastic Frontier Production Function Models, Journal of Econometrics, 6, 21-37.
Afriat, S. N. (1972), Efficiency Estimation of Production Functions, International Economic Review, 13, 568-598.
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, 159-169.
Casella, G., Fienberg, S., and Olkin, I. (2006), All of Nonparametric Statistics, Springer Texts in Statistics.
Charnes, A., W. W. Cooper and E. Rhodes. (1978), Measuring Efficiency of Decision Making Units. European Journal of Operational, 3, 429-444.
Deng, W. S. and Huang, T. H. (2008), A Semiparametric Approach to Estimation of the Stochastic Frontier Model with Time-Variant Technical Efficiency, Academia Economic Papers, To appear.
Fan, Y., Q. Li, and A. Weersink (1996), Semiparametric Estimation of Stochastic Production Frontier Models, Journal of Business and Economic Ststistics, 14, 460-468.
Farrell, M. J. (1957), The Measurement of Production Efficiency, Journal of the Royal Statistical Society, Series A. 120, 253-281.
Forsund, F. R., Knox Lovell, C. A. and Schmidt, P. (1980), A Survey of Frontier Productions and of Their Relationship to Efficiency Measurement, Journal of Econometrics, 13, 5-20.
Härdel, W. (1990), Applied Nonparametric Regression, Cambridge University Press Cambridge, U.K.
Härdel, W., Müller, M., Sperlich S., and Werwatz, A. (2004), Nonparametric and Semiparametric Models, Springer Series in Statistics.
Kumbhakar, S. C., and C. A. K. Lovell (2000), Stochastic Frontier Analysis, Cambridge University Press, Cambridge, U.K.
Linton, O. (1995), Second Order Approximation in the Partially Linear Regression Model, Econometrica, 63, 1079-1112.
Meeusen, W. and van den Broeck, (1977), Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error, International Economic Review, 18, 435-44.
Marron, J. S. (1988), Automatic Smoothing Parametric Selection: A Survey, Empirical Economics, 13, 187-208.
Nadaraya, E. A. (1964), On Estimating Regression. Theory of Probability and Its Application, 10, 186-190.
Olson, J. A., Schmidt, P., and Waldman, D. M. (1980), A Monte Carlo Study of Estimators the Stochastic Frontier Production Function, Journal of Econometrics, 13, 67-82.
Robinson, P. (1988), Root-N-Consistent Semiparametric Regression, Econometrica, 56, 931-954.
Rohatgi, V. K. (2001), An Introduction to Probability Theory and Mathematical Statistics, John Wiley and Sons, Inc.
Schmidt, P. and R. C. Sickles (1984), Production Frontier and Panel Data, Journal of Business and Economic Statistics, 2, 367-374.
Scott, D. (1992), Multivariate Density Estimation, New York: Wiley.
Stock, J. H. (1989), Nonparametric Policy Analysis, Journal of the American Statistical Association, 84, 567-575.
Yatchew, A. (1998), Nonparametric Regression Techniques in Economics, Journal of Economic Literature, 669-772.
Yatchew, A. (2003), Semiparametric Regression for the Applied Econometrician, Cambridge University Press, Cambridge, U.K.
論文使用權限
  • 同意紙本無償授權給館內讀者為學術之目的重製使用,於2010-07-21公開。
  • 同意授權瀏覽/列印電子全文服務,於2010-07-05起公開。


  • 若您有任何疑問,請與我們聯絡!
    圖書館: 請來電 (02)2621-5656 轉 2281 或 來信