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1 ** 9* 88/2/22 : 86/9/26 : 56. COLS /43.. COLS : ( kimiagar@aut.ac.ir) * **

2 ) (.( ). (COLS) (MLE)..(10) ) 1997 (COLS.(9) (11) (11) 11. 7) 18/5.(11 102

3 (8 6 2).(1 ) Ser02 Ser01 1 Fig. 1. The conversion of average production function to frontier production function.. DEA COLS MLE ( ) DAE 1 Data Envelopment Analysis 2 Maximum Likelihood Estimation 4 Data Envelopment Analysis 3 Corrected Ordinary Least Squares 103

4 COLS OLS. y = f (x, x,..., x ) + ε j. α 0. y = α + f (x, x,..., x ) + ε ε. α = t n j 1,0. 02σ 1 2 σ j n j 98.. : f(x1i,x 2i,..., x ji ) > yi, i = 1,..., n. t....(15 6 3) MLE.... (Output). f(x) y f(x) 6 2).(8 COLS. 104

5 ( ) (2 1 ) ( ) (FAO) Eviews 3 5) (4 3 ).( ) 2005 (.( ) (7 6 5 ) 1. ( 600 ) f (x 1i, x 2i,..., x OLS OLS...( ) ( ) ji ) 105

6 / ( ) ) 1 ( ( ) Table 1 The highest yield of sugar beet production in the world in year 2005 (metric ton/) Standard deviation Average Between 200 to 800 thousand Between 50 to 200 thousand Between 10 to 50 thousand 10 Less than 10 thousand Harvest area rainfall ((mm) ) Egypt Syrian Arab Tunisia Less than Republic Turkey Hungary Canada Pakistan Between 300 to France Spain Greece Portugal Between 600 to Japan Chile Slovenia Between 1000 to Average Standard deviation 106

7 ( ) Table 2 The highest yield of sugar beet production in the world in year 2005 (metric ton/) standard deviation average between 200 to 800 thousand between 50 to 200 thousand between 10 to 50 thousand 10 less than 10 thousand harvest area ( ) Number of Tractors Morocco Slovakia Lebanon Less than Belgium Chile Slovenia Between to Ukraine Serbia and Montenegro Austria Portugal Between to France Spain Canada Between to Average Standard deviation..( ) 56 (P) (FS) (HA) (H) (TR) 107

8 Table 3 Sugar beet Production Function in the World in Year t Prob tstatistic Std. Error Coefficient Variable HA FS TR R 2 F DurbinWatson stat Akaike info criterion Schwarz criterion Fstatistic Outgoing of Eviews 3 software * Eviews 3..( ) 56 (P) (FS) (HA) (H) (TR) Table 3 Sugar beet production function in the world in year t Prob tstatistic Std. Error Coefficient Variable HA FS TR R 2 DurbinWatson stat Akaike info criterion Schwarz criterion F Fstatistic

9 COLS 14.(6 5) R 2. Table 4 Sugar beet COLS production function in the world in year 2005 * 2005 COLS 4 t Prob tstatistic Std. Error Coefficient Variable HA FS E TR R 2 DurbinWatson stat Akaike info criterion Schwarz criterion F Fstatistic Outgoing of Eviews 3 software * Eviews 3 P = *HA * FS *TR. 1).( α = 1660/66 ) 2005 (FS) (P) (HA) (TR).( 109

10 Table 5 The Ranking of Countries Sugar beet Production Efficiency in Year 2005 Efficiency Countries Rank Efficiency Countries Rank China France Spain Belgium Hungary Poland Czech Republic Germany Sweden Egypt Turkey Chile Austria Netherlands Japan Slovakia Serbia and Montenegro Italy Iran, Islamic Rep of United States of America Denmark United Kingdom Morocco Ukraine 110

11 () 5 Table 5 (continuance) The Ranking of Countries Sugar beet Production Efficiency in Year 2005 Efficiency Countries Rank Efficiency Countries Rank Kazakhstan Belarus Pakistan Russian Federation Turkmenistan Finland Lebanon Greece Azerbaijan, Republic of Switzerland Macedonia,The Fmr Yug Rp Croatia Albania Lithuania Bulgaria Moldova, Republic of Tunisia Portugal Venezuela,Bolivar Rep of Ireland Uzbekistan Syrian Arab Republic Ecuador Latvia Armenia Romania Mexico Canada Estonia Slovenia Georgia Kyrgyzstan

12 ( ) 0/ (7 6 ) ( ) Table 6 The highest efficiency of sugar beet production in the world in year 2005 (metric ton/) Standard deviation Average Between 200 to 800 thousand Poland France Between 50 to 200 thousand Egypt Hungary Belgium United Kingdom Between 10 to 50 thousand Syrian Arab Republic Finland Slovakia Chile Less than 10 thousand Tunisia Pakistan Portugal Slovenia Harvest area Rainfall ((mm) ) 300 Less than Between 300 to Between 600 to Between 1000 to2100 Average Standard deviation 112

13 ( ) Table 7 The highest efficiency of sugar beet production in the world in year 2005 (metric ton/) standard deviation average between 200 to 800 thousand Ukraine France between 50 to 200 thousand Morocco Belgium Serbia and Montenegro United Kingdom between 10 to 50 thousand Slovakia Chile Sweden Canada less than 10 thousand Lebanon Slovenia Portugal harvest area ( ) Number of Tractors less than between to between to between to average standard deviation. (6).. (7) (6)

14 References 1 Agricultural Jahad Ministry (2009) 2 Aigner D (1997) Formulation and estimation of stochastic frontier production models. Journal of Econometrics 6: Andersen P and Petersen N (1993) A procedure for ranking efficient unit in data envelopment analysis. Management Science 39(10): Anderson B and Peterson P (1996) The benchmarkinghandbook step by step instructions. Chapman & Hall 15: Arabmazar A (1990) General Econometrics. Kavir Press., Tehran. Iran. 503 pp. 6 Barkhordar Sh (2000) Designing a model in order to determine the statistical standards of efficiency in Iran electricity industry using deterministic frontier production function. M.sc. thesis Amirkabir University of Technology, Tehran. Iran. 7 FAO (2007) 8 Forsund F (1980) Survey of frontier production function and of their relationship to efficiency measurement. Journal of Econometrics 13: Hu B and McAleer M (2005) Estimation of Chinese agricultural production efficiencies with panel data. Journal of Mathematics and Computers in Simulation 68: Iran wheat Khajepour M (2004) Industrial Plants. Jahad Daneshgahi Press., Isfahan Industrial Unit. 564 p. 12 Rajiv D, Robert B, Conrad F and Strauss R (1986) A comparative application of data envelopment analysis and translog methods: An illustrative study of hospital production. The institute of Management Sciences 31: Sarrico C, Hogan S, Dyson R and Athanassopoules A (1997) Data envelopment analysis and university selection. Journal of the Operational Research Society 48: Statistics Center of Iran Thanassoulis R, Dyson G and Foster M (1987) Relative efficiency assessments using data envelopment analysis: An application to data on rates. Department Operational Research Society 38(5):

15 Journal of Agriculture, Vol. 11, No. 1, Spring 2009 Evaluation of sugar beet production efficiency with estimation of frontier production function A. M. Kimiagari *32 and A. Teymouri **33 Abstract For evaluation of efficiency and yield per surface unit with using the 56 sugar beet producer countries data in year 2005 an econometric model based on COLS method has presented. With this model maximum sugar beet production efficiencies considering the harvested area and annual rainfall measure and level of mechanization has been determined. In total Iran with production efficiency 0.43 is in rank 22 of the world and France with production efficiency 1 has the maximum sugar beet production efficiency in the world. In continuance of discussion relation between the countries sugar beet harvest area, annual rainfall measure and level of mechanization with their efficiency and yield in sugar beet production has tried to be studied. Key words: COLS, Frontier production function, Iran, Production efficiency, Sugar beet * Assistant professor, System and Efficiency Management Department, Amirkabir University of Technology, Tehran Iran (kimiagar@aut.ac.ir) ** M.Sc., Industrial Engineering Department, Amirkabir University of Technology, Tehran Iran (arman6297@hotmail.com)