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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/32265


    Title: 效率與排名之關係研究—以大陸男子甲A籃球聯賽為例
    Authors: 林純琦
    Lin, Chun-chi
    Contributors: 李文福
    Lee, Wen-fu
    林純琦
    Lin, Chun-chi
    Keywords: 生產效率
    隨機邊界分析法
    運動產業
    Production Efficiency
    Stochastic Frontier Approach
    Sports Industry
    Date: 2005
    Issue Date: 2009-09-14 13:32:12 (UTC+8)
    Abstract: 在運動產業逐漸興起的現代,如何評比球隊或運動員的表現好壞,似乎成了現在新興的熱門話題。經濟學上用來評估一家廠商的生產績效優劣,常用的是生產效率分析,生產活動偏離生產邊界的程度代表不效率高低。而球隊比賽的過程就像廠商生產的過程,運用各種投入得到產出。在籃球比賽中,比賽的投入可為球隊的各種技術統計,例如:投籃命中率、抄截、火鍋…等等,產出則是比賽的得分數。因此,在本篇文章中,我們利用經濟學中的生產效率分析來分析球隊的表現優劣,即評估各球隊發揮其潛能的程度。

    評估生產效率的模型有很多,由於比賽的性質,有時候統計誤差、運氣也佔了很重要的部份,所以在選擇模型時,選的是隨機邊界效率分析模型(Stochastic Frontier Approach, SFA),除了利用隨機邊界分析模型分析球隊的生產效率,也利用預估的效率值來預測比賽結果排名,並與一般常用來預測結果的模型PROBIT MODEL做比較。我們利用大陸男子甲A籃球聯賽2003-2004和2004-2005賽季作為實證樣本,發現隨機邊界分析模型不只可以用來評估效率,在預測比賽結果排名上,隨機邊界分析模型預測能力則與PROBIT MODEL沒有顯著統計性的差異。
    關鍵字:生產效率、隨機邊界分析法、運動產業
    Today, sports industry is getting popular, and how to evaluate the performance of sports teams or players seems also to be a newly hot interesting topic. In economics, production efficiency is often applied to evaluate a firm’s production performance. The inefficiency of a production activity is measured as its deviation from the production frontier. The process of a sport game is similar to a firm’s production process, which transforming various inputs into output(s). For basketball games, inputs can be the various technical statistics, such as field goal rate, steals, blacks, assistant attack, etc. Output(s) can be the scores of the teams got. Therefore, in this paper we use the production efficiency to gauge the performance of sports teams.

    There are many models measuring production efficiency. In this paper we choose the Stochastic Frontier Approach (SFA) to evaluate the sport team’s efficiency on account of the white noises which exist in the sport game obviously. We also use estimated efficiency scores to predict the outcome ranking of teams, and compare it to that of the PROBIT MODEL which is usually used to predict the outcome of a game. The sample we used are the results of the CBA men’s regular season and playoff season, and we found that the SFA is not only to evaluate efficiency but also can predict the outcome of competition, and its prediction ability is not significantly statistically different to that of PROBIT MODEL.
    Keywords: Production Efficiency, Stochastic Frontier Approach, Sports Industry
    Reference: Afriat, S.N. (1972), “Efficiency Estimation of Production Functions,” International Economic 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 Function Models,” Journal of Econometrics, 6, 21-37.
    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.
    Berri, D.J., and T. Jewell (2004), “Wage Inequality and Firm Performance: Professional Basketball`s Natural Experiment,” Atlantic Economic Journal, 32(2), 130-139.
    Boulier, L. and H.O. Stekler (1999), “Are Sports Seedings Good Predictors?: An Evaluation,” International Journal of Forecasting, 15, 83-91.
    Caudill, B. (2003), “Predicting Discrete Outcomes with the Maximum Score Estimator: the Case of the NCAA Men’s Basketball Tournament,” International Journal of Forecasting, 19, 313-317.
    Dawson, P., S. Dobson and B. Gerrard (2000), “Stochastic Frontiers and the Temporal Structure of Managerial Efficiency in English Soccer,” Journal of Sports Economics, 1, 341-362.
    Farrell, M.J. (1957), “The Measurement of Productive Efficiency,” Journal of the Royal Statistical Society, Series A, CXX, Part3, 253-290.
    Haas, D., M.G. Kocher and M. Sutter (2003), “Measuring Efficiency of German Football Teams by Data Envelopment Analysis,” Central European Journal of Operations Research, 3, 251-268.
    Hill, R., W.E. Griffiths and G. Judge (2001), “Qualitative and Limited Dependent Variable Models,” in Hill, R., W.E. Griffiths and G. Judge, (eds.), Undergraduate Econometrics, 368-376, United States of America: John Wiley & Sons, Inc..
    Hofler, R. and J.E. Payne (1997), “Measuring Efficiency in the National Basketball Association,” Economics Letters, 55, 293-299.
    Jondrow, J., C.A.K Lovell, I.S. Materov and P. Schmidt (1982), “On Estimation of Technical Inefficiency in the Stochastic Frontier Production Function Model,” Journal of Econometrics, 19, 233-238.
    Meeusen, W. and J. van den Broeck (1977), “Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error,” International Economic Review, 18, 435-444.
    Schmidt, P. (1976), “On the Statistical Estimation of Parametric Frontier Production Functions,” Review of Economics and Statistics, 58, 238-239.
    Wilcoxon, F. (1945), “Individual Comparisons by Ranking Methods,” Biometrics, 1, 80-83.
    Zak, T., C.J. Huang and J. Siegfried (1979), “Production Efficiency: the Case of Professional Basketball,” The Journal of Business, 52, 379-392.
    Description: 碩士
    國立政治大學
    經濟研究所
    92258008
    94
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0922580082
    Data Type: thesis
    Appears in Collections:[經濟學系] 學位論文

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