A Panel Stochastic Frontier Model for Estimating Technical Efficiency in U.S. Industries.

以作者查詢圖書館館藏

、以作者查詢臺灣博碩士

、以作者查詢全國書目

、勘誤回報

、線上人數：5

、訪客IP：3.145.153.86

姓名

林士槐(Shih-Huai Lin) 查詢紙本館藏

畢業系所

經濟學系

論文名稱

(A Panel Stochastic Frontier Model for Estimating Technical Efficiency in U.S. Industries.)

相關論文

★ 消費財富效果不對稱分析: 馬可夫轉換共同趨勢模型之應用	★ 股票市場報酬與波動性外溢效果分析
★ 中國大陸勞動合同法與企業所得稅法對台商的衝擊與因應	★ 結構FAVAR模型與台灣貨幣政策分析
★ 通貨膨脹率預測:考慮結構變動之動態因子模型應用	★ 匯率因子與市場基要之預測表現
★ 台灣大小公司報酬與流動性之實證研究	★ 台灣外匯暨股票市場流動性與景氣循環關係之探討
★ 台灣經濟成長率之混合頻率預測-MIDAS迴歸應用	★ 油價對匯率預測能力之分析
★ 重新驗證遠期匯率不偏性假說: Bonferroni Q 檢定之應用	★ 台灣期貨市場處份效果之研究
★ 寡占廠商成本歧異下之最適產業與貿易政策	★ The Macroeconomic Effects of Foreign Direct Investment
★ 平行輸入、仿冒與服務品質	★ 經濟成長、消費者信心與銀行風險

檔案

[Endnote RIS 格式]

[Bibtex 格式]

[相關文章]

[文章引用]

[完整記錄]

[館藏目錄]

[檢視]

[下載]

本電子論文使用權限為同意立即開放。
已達開放權限電子全文僅授權使用者為學術研究之目的，進行個人非營利性質之檢索、閱讀、列印。
請遵守中華民國著作權法之相關規定，切勿任意重製、散佈、改作、轉貼、播送，以免觸法。

摘要(中)

本篇論文利用一隨機邊界模型調查五十五個美國產業類別 (分類標準依據 2002 North American Industry Classification System) 的技術效率, 同時估計一隨機邊界生產函數與無效率因素分析。研究期間為1997年到2011年, 總共15年。與現有應用隨機邊界模型的研究文獻不同的是, 在現有研究與文獻中並沒有廣泛討論到未能觀察到的衝擊 (unobserved common shocks) 所產生之影響,若忽略這些影響將使得估計結果產生偏誤且不ㄧ致的現象。本文的計量模型考慮並且控制這些影響進行估計並且得出估計果, 除估計出隨機生產逼界函數與無效率因子分析式之外, 也依據所估計出的效率值將五十五個美國產業類別的技術效率表現進行排序, 並且檢視跨橫斷面平均技術效率隨十五年間的變動情形。本篇論文的研究結果指出一個重要訊息: 美國的主要產業跨橫斷面平均技術效率在1997到2011年間呈現出一波動且逐漸下降的趨勢。除此之外, 本研究亦發現美國主要產業跨橫斷面平均技術效率的波動型態與美國實質經濟成長率變動似乎有著特定的關聯, 兩數列的波動型態非常一致但有著時間先後的差異。對於此現象的一個預先推論是廠商對於未來前景的預期將會影響其對於調整技術效率的決策。

摘要(英)

This paper uses an unconventional panel stochastic frontier model to investigate the technical efficiency of 55 industries in the United States during 1997-2011. Unlike the
existing research adopting the stochastic frontier model, this paper takes account of and controls the common correlated effect caused by unobserved common shocks when estimating the panel stochastic frontier model. The parameters in the model and the indicators of technical efficiency are obtained through estimation; the results estimated by conventional techniques are also provided as a comparison. Based on the results, the technical efficiency
of the 55 industries and the overall technical efficiency are examined. The technical efficiency ranking of the 55 industries is also given, and their overall technical efficiency reveals important information: the overall technical efficiency of these industries has a decreasing
trend and fluctuating movement. Additionally, it is found that the overall technical efficiency movement seems to have a specific relation to the real GDP growth rate in the United States. A preliminary explanation of this finding is based on future expectations and the decisions made by firms in these industries for adjusting their technical efficiency.

關鍵字(中)

★ 隨機邊界
★ 技術效率
★ 共同相關效果

關鍵字(英)

★ Stochastic frontier
★ Technical efficiency
★ Common correlated effect

論文目次

1 Introduction 1
2 Literature Review 3
3 Econometric Framework 5
3.1 Panel Stochastic Frontier Model with Unobserved Common Shocks . . . . . 6
3.2 CCE Transformation and Estimation . . . . . . . . . . . . . . . . . . . . . . 7
4 Empirical Method 9
5 Data 10
5.1 Sample Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
5.2 Variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
5.3 Data Sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
5.4 Data Adjustment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
6 Estimation Results 18
6.1 Production Function and Ineciency Equation Results . . . . . . . . . . . . 18
6.2 Estimated Technical Eciency Performance . . . . . . . . . . . . . . . . . . 21
6.3 The Movement of Technical Eciency . . . . . . . . . . . . . . . . . . . . . 28
7 Conclusion 32
References. . . . . . . . . . . 34

參考文獻

Aigner, D. J., C. A. K. Lovell and P. Schmidt, 1977. Formulation and Estimation of Stochastic Frontier Production Function Models, Journal of Econometrics, 6, 21-37.
Andrews, D. W. K., 2005. Cross-section regression with common shocks, Econometrica, 73, 1551-1585.
Battese, G. E. and T. J. Coelli, 1992. Frontier Production Functions, 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, 1995. A model for Technical Inefficiency Eects in a Stochastic Frontier Production Function for Panel Data, Emprical Economics, 20, 325-332.
Buck, J. and D. Young, 2007. The Potential for Energy Eciency Gains in the Canadian Commercial
Building Sector: A Stochastic Frontier Study, Energy, 32, 1769-1780.
DeLorme, C. D., Jr., H. G. Thompson, JR. R. S. Waeewn, JR., 1995. Money and Production: A Stochastic Frontier Approach, Journal of Productivity Analysis, 6, 333-342.
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 Economics, 26, 277-289.
Coellia, T. and S. Perelman, 1999. A comparison of parametric and non-parametric distance functions: With application to European railways, European Journal of Operational Research,117, 326-339.
Cornwell, C., P. Schmidt and R. C. Sickles, 1990. Production Frontiers with Cross-sectional and Time-series Variation in Efficiency Levels, Journal of Econometrics, 46, 185-200.
Cullinane, K., D. W Song and Gray, R., 2002. A Stochastic Frontier Model of the Eciency of Major Container Terminals in Asia: Assessing the Influence of Administrative and Ownership Structures, Transprotation Research Part A: Policy and Practice, 36, 743-762.
Greene, W., 2005. Fixed and random eects in stochastic frontier models, Journal of Productivity Analysis, 23, 7–32.
Han, C., L. Orea and P. Schmidt, 2005. Estimation of a panel data model with parametric temporal variation in individual effects, Journal of Econometrics, 126, 241–267.
Hsu, C. C. , C. C Lin and S. Y. Yin, 2012. Estimation of a Panel Stochastic Frontier Model with Unobserved Common Shocks, Working Paper.
Huang, C. J. and J. T. Liu, 1994. Estimation of a Non-Neutral Stochastic Frontier Production Function, Journal of Productivity Analysis. 5, 171–180.
Khan, Ashfaque H. and Mushtaq Ahmad, 1985. Real Money Balance in the Production Function of a Developing Country, Review of Economics and Statistics, 67, 336–340.
Khatri, C. G., 1968. Some results for the singular normal multivariate regression models, Sankhya. 30, 267–280.
Lee, Y. H., 2006. A Stochastic Production Frontier Model with Group-specific Temporal Variation in Technical Effciency, European Journal of Operational Research, 174, 1616–1630.
Meeusen, Wim and Julien Van Den Broeck, 1977. Efficiency Estimation from Cobb-Douglas Production Function with Composed Error, International Economic Review, 18, 435–444.
Mester, L. J., 1996. A Study of Bank Efficiency Taking into Account Risk-preferences, Journal of Banking and Finance, 42, 423–445.
Neogi, Chiranjib and Buddhadeb Ghosh, 1994. Intertemporal Efficiency Variations in Indian Manufacturing Industries, Journal of Productivity Analysis, 5, 301–342.
Nishimizu, M. and J. M Page Jr., 1982. Total Factor Productivity Growth, Technological Progress and Technical Efficiency Change: Dimensions of Productivity Change in Yugoslavia, Economic Journal, 92, 920–936.
Orea, L. and S. C. Kumbhakar, 2004. Efficiency Measurement Using a Latent Class Stochastic Frontier Model, Empirical Economics, 29, 169–183.
Pesaran, M. H., 2006. Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure, Econometrica, 74, 967–1012.
Phillips, P. C. B. and D. Sul, 2003. Dynamic panel estimation and homogeneity testing under cross section dependence, The Econometrics Journal, 6, 217–259.
Schmidt, P. and R. C. Sickles, 1984. Production Frontiers and Panel Data, Journal of Business and Economic Statistics, 2, 367–374.
Sickles, R. C. and M. L. Streitwieser, 1992. Technical Inefficiency and Productive Decline in the U.S. Interstate Natural Gas Pipeline Industry under the Natural Gas Policy Act, Journal of Productivity Analysis, 3, 119–133.
Wang, H. J. and C. W. Ho, 2010. Estimating Fixed-effect Panel Stochastic Frontier Models by Model Transformation, Journal of Econometrics, 157, 286–296.
Wang, H. J. and P. Schmidt, 2002. One-step and Two-step Estimation of the Effects of ExogenousVariables on Technical Efficiency Levels, Journal of Productivity Analysis, 18, 129–144.

指導教授

徐之強

審核日期

2013-7-18

推文