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系統識別號 U0002-2206200913271300
中文論文名稱 縱橫資料截面隨機邊界模型—組合誤差假設非獨立
英文論文名稱 Stochastic frontier models assuming dependent composed errors with panel data
校院名稱 淡江大學
系所名稱(中) 經濟學系碩士班
系所名稱(英) Department of Economics
學年度 97
學期 2
出版年 98
研究生中文姓名 梁孝祖
研究生英文姓名 Hsiao-Tsu Liang
學號 696570307
學位類別 碩士
語文別 中文
第二語文別 英文
口試日期 2009-06-12
論文頁數 33頁
口試委員 指導教授-黃台心
委員-林亦珍
委員-李鈞元
中文關鍵字 隨機邊界法  固定效果  組合誤差項內元素不獨立  規模特性法 
英文關鍵字 stochastic frontier analysis  fixed effect  dependent composed errors  scaling property 
學科別分類 學科別社會科學經濟學
中文摘要 隨機邊界法應用在縱橫資料上往往將廠商的無效率項以固定效果或隨機效果項代替,然而此方法會將代表廠商差異性的異質效果包含至無效率項。為了解決此問題學界已有論文推導出可分離廠商無效率項與廠商異質項的方法,然而該方法存在著Incidental parameters problem,後來的文獻藉由一階差分法以及組內轉換法先排除廠商異質效果,再由一般的最大概似估計法估計相關的待估計參數,最後再由估計得出參數估計值由殘差的方式得出廠商的異質效果項,這樣的好處是可以避免Incidental parameters problem。然而上述提及的方法均假設組合誤差項內元素彼此間獨立,學界尚無明顯的證據支持該假設,故本論文將提出一套組合誤差項內元素彼此相關的模型,包括了未分離廠商異質效果與無效率項的組合誤差項內元素不獨立模型以及分離廠商異質項與無效率項的組合誤差項內元素不獨立的固定效果模型。
英文摘要 The method of stochastic frontier analysis with panel data used in the field of productivity and efficiency considers firm’s heterogeneity as individual inefficiency term in the past. The problem of this approach is that the inclusion of firm’s heterogeneity in its inefficiency term has not accessible ability to gain precisely the information of pure inefficiency from fixed effect or random effect. In order to get rid of this troublesome weakness, a model with capability to separate firm’s heterogeneity and inefficiency term is developed .However, This model also arises the incidental parameters problem. In order to immune from this problem, the usages of first difference and within group transformation are worked to eliminate heterogeneity and estimate other parameters that is remained in the model before practicing the method of maximum likelihood estimation. Another issue is that models mentioned above are all based on the assumption of independent composed error. Because the lack of evidence for assuming independent composed error for the methodology of stochastic frontier analysis in the field of productivity and efficiency, this prompts us to build two stochastic frontier models with the hypothesis for dependent composed error. The first is going to derive a model without separating firm’s heterogeneity from its inefficiency term. The second is a fixed effect model with a heterogeneity term. Furthermore, the assumption of dependent composed error is imposed on both models.
論文目次 目錄
第一章 簡介 1
1.1背景 1
1.2目的 2
1.3 本文架構 3
第二章 文獻回顧 5
2.1無效率項不隨時間變動模型 5
2.2無效率隨時間變動模型 6
2.3異質效果項 10
第三章 理論模型 12
3.1組合誤差項內元素不獨立模型 12
3.2組合誤差項內元素不獨立的固定效果模型 15
3.2.1 相鄰兩期的差分後誤差項彼此獨立假設 16
3.2.2 相鄰兩期的差分後誤差項彼此不獨立假設 18
第四章 蒙地卡羅模擬 20
4.1組合誤差項內元素不獨立模型 20
4.2 組合誤差項內元素不獨立的固定效果模型 24
第五章 結論 25
參考文獻 31
中文參考文獻 31
英文參考文獻 31

圖表目錄
圖表 1組織架構圖 4
表格 1組合誤差項內元素不獨立模型 26
表格 2組合誤差項內元素不獨立 27
表格 3組合誤差不獨立模型 28
表格 4組合誤差項內元素不獨立的固定效果模型 29
表格 5組合誤差項內元素獨立的固定效果模型 30
參考文獻 參考文獻

中文參考文獻
王媛慧、李文福、翁竹君 (2007,“台灣國際觀光旅館生產力與效率分析:隨機邊界距離函數之運用” ,經濟論文叢刊,35(1),55-86。

陳忠榮、劉錦添,孫佳宏 (2001),“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”,人文及社會科學,11(4),401-413。

鄭秀玲、劉錦添、陳欽奇 (1997), “台灣中小企業銀行的效率分析(1986-1994年)”,經濟論文,25(1) ,69-95。

鄭秀玲、周群新 (1998), “調整風險後之銀行效率分析:台灣銀行的實證研究”,經濟論文叢刊,26(3),337-366。

英文參考文獻
Aigner, D., Lovell CAK and Schmidt, P. (1977) , “Formulation and estimation of stochastic frontier production function models.” Journal of Econometric 6, 21–37.

Bandyopadhyay, D. and Das, A.(2006),“On measures of technical inefficiency and production uncertainty in stochastic frontier production model with correlated error components.” Journal of Productivity Analysis 26,165-180.

Battese, G. E. and Coelli, T. J. (1992), “Frontier production functions, technical efficiency and panel data: with application to paddy farmers in India.” Journal of Productivity Analysis 3 (1), 153-169.

Battese, G. E. and Coelli, T. J., (1995), “A model for technical inefficiency effects in a stochastic frontier production function for panel data.” Empirical Economics 20, 325-332.

Battese, G. E. and Broca, S. S. (1997), “Functional forms of stochastic frontier production functions and models for technical inefficiency effects: a comparative study for wheat farmers in Pakistan.” Journal of Productivity Analysis 8, 395-414.

Coelli, T. J., Perelman, S. and Romano, E. (1999),“Accounting for environmental influences in stochastic frontier models: with application to international airlines.” Journal of Productivity Analysis 11, 251–273.

Cuesta, R. A. and Orea, L. (2002),“Mergers and technical efficiency in Spanish savings banks: A stochastic distance function approach.” Journal of Banking and Finance 26, 2631-2647.

Chakraborty, K. and Poggio, J. (2008), “Efficiency and equity in school funding: a case study for Kansas.” International Advanced Economic Research 14,228-241.

Fan, Y., Qi, L. and Weersink, A. (1996), “Semiparametric estimation of stochastic frontier models.” Journal of Business & Economic Statistics 14,460-468.

Filippini, M., Hrovatin, A. N. and Zoric, A. (2008), “Cost efficiency of Slovenian water distribution utilities: an application of stochastic frontier methods.” Journal of Productivity Analysis 29, 169–182.

Greene, W. (2005), “Reconsidering heterogeneity in panel data estimators of the stochastic frontier model.” Journal of Econometrics 126, 269-303

Greene, W.(2005), “Fixed and random effects in stochastic frontier models.” Journal of Econometrics 126, 269-303.

Huang, C. J., Liu, J. T. (1994), “Estimation of a non-neutral stochastic frontier production function.”Journal of Productivity Analysis 5, 171-180.

Huang, T. H. (2005),“A study on the productivities of IT capital and computer labor: firm-level evidence from Taiwan’s banking industry.” Journal of Productivity Analysis, 24, 241-257.

Kumbhakar, S. C. (1990), “Production frontiers, panel data and time-varying technical inefficiency.” Journal of Econometrics 46, 201-211.

Kirkley, J., Squire, D. and Strand, I. V.(1998), “Characterizing managerial skill and technical efficiency in a fishery.” Journal of Productivity Analysis 9, 145-160.

Lindara, L. M. J. K., Johnsen, F. H. and Gunatilake, H. M. (2006), “Technical efficiency in the spice based agroforestry sector in Matale district, Sri Lanka.” Agroforest System 68:221–230.

Meeusen, W., ven den Broeck J. (1977), “Efficiency estimation from cobb-douglas production functions wth composed error.” Int Econ Rev 181, 435–444.

Pitt, M. and Lee, L. (1981) , “The measurement and sources of technical inefficiency in Indonesian weaving industry.” Journal of Development Economics 9, 43-64.

Rossi, M. A. (2001),“Technical change and efficiency measures: the post-privatisation in the gas distribution sector in Argentina.” Energy Economics 23, 295-304.

Stevenson, R. (1980), “Likelihood functions for generalized stochastic frontier functions.” Journal of Econometrics 13, 57-66.

Schmidt, P. and Sickles, R.(1984), “Production frontiers with panel data.” Journal of Business and Economic Statistics 2 (4), 367-374.

Wang, H. J. and Schmidt ,P. (2002),“One-step and two-step estimation of the effects of exogenous variables on technical efficiency levels.” Journal of Productivity Analysis 18, 129-144.

Wooldridge, .J M. (2002), “Econometric analysis of cross section and panel data.” Massachusetts Institute of Technology Cambridge, Massachusetts.

Wang, H. J. and Ho, C. W. (2007), “Estimating panel stochastic frontier models with fixed effects by model transformation.” working paper.
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