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1 에너지경제연구 Korean Energy Economic Review Volume 14, Number 1, March 2015 : pp. 111~141 2 차에너지산업의기술적효율성국제비교및 결정요인분석에관한연구 1) 111

2 112

3 113

4 114

5 115

6 116

7 117

8 max ln ln ln ln 118

9 ln ln ln ln ln ln ln 119

10 120

11 121

12 < 표 1> 확률적프론티어생산함수추정치 7) 122

13 [ 그림 1] 전체 16 개국가의기술적효율성변화추이 123

14 [ 그림 2] 전체 15 개국가와한국의기술적효율성비교 124

15 [ 그림 3] 주요 6 개국의기술적효율성추이 125

16 [ 그림 4] 전체국가와한국의기간별평균과증가율 126

17 127

18 [ 그림 5] 지역별기술적효율성변화추이 128

19 [ 그림 6] 지역별 기간별기술적효율성평균변화추이 [ 그림 7] 지역별 기간별기술적효율성증가율변화추이 129

20 < 표 2> 기술적비효율성영향모형 (efficiency effect model) 추정결과 130

21 131

22 132

23 133

24 134

25 135

26 접수일 (2014 년 8 월 13 일 ), 게재확정일 (2014 년 9 월 29 일 ) 136

27 , 2005,,, 16(4), pp (2001), :,, 7(2), pp (2001),,, 9(2), pp (2009),,, 22(4), pp. 1,867-1,889 (2004),,, 12(4), pp (2001),,. (1991), (FRONTIER),., (2009),, :. (2001),,. (2004),, 04-03, (2004),,, 20(2), pp (2010), R&D : SFA,, 17(1), pp (2000), :, 137

28 . (2001),,, 15(1), pp (1998), : (panel data),, 7(3), pp (1998), DEA - -,, 32(4), pp (2003), (Stochastic Frontier Model),. (1995),,, 43(1), pp (1997), (Stochastic Frontier Cost Model),. (2000),,, 3(3), pp (2000), : OECD,, 21(1), pp (2011),,, 25(2), pp (2009),,, 13(2), pp (2003), :,. (1996), :,, 2(2), pp (1987),,. (2007), : 138

29 (stochastic frontier production function),, 20(5), pp. 1,785-1,801. (2004), :,, 29(2), pp Battese, G. E. and T. J. Coelli, " A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data", Empirical Economics, 20, 1995, pp Battese, G. E. and T. J. Coelli, Frontier Production Functions, Technical Efficiency and Panel Data: With Application to Paddy Farmers in India", Journal of Productivity Analysis, 3, 1992, pp Corbo, Vittorio and Patricio Meller, "The Translog Production Function", Journal of Econometrics, Vol. 10, 1979, pp Cornwell C., Peter Schmidt, and Robin C. Sickles, "Production frontiers with cross-sectional and time-series variation in efficiency levels", Journal of Econometrics, Vol 46, Issues 1-2, 1990, pp Farrell, M. J., "The Measurement of Productive Efficiency", Journal of the Royal Statistical Society, Series A, Vol.120, No.3, 1957, pp Greene, Willam, Reconsidering heterogeneity in panel data estimators of the stochastic frontier model, Journal of Econometrics, 126, 2005, pp Huang, Cliff. J. and Jin-Tan Liu, "Estimation of a Non-Neutral Stochastic Frontier Production Function", Journal of Productivity Analysis, 5, 1994, pp Kumbhakar, Subal C, Soumendra Ghosh and J. Thomas McGuckin, "A Generalized Production Frontier Approach for Estimating Determinants of Inefficiency in U.S. Dairy Farms", Journal of Business and Economic Statistics, Vol.9, No.3, 1991, pp Kumbhakar, Subal C. and C. A. Knox Lovell, Stochastic Frontier Analysis, United Kingdom: Cambridge University press, Mahadevan, Renuka, "How technically efficient are Singapore's manufacturing industies?", Applied Economics, 32:15, 2000, pp.2,007-2,

30 Perelman, S., R&D, Technological Progress and Efficiency Change in Industrial Activities, Review of Income and Wealth, Vol. 41, issue 3, 1995, pp Pitt, M. and Kung-Fei Lee, "The Measurement and Sources of Technical Inefficiency in the Indonesian Weaving Industry", Journal of Development Economics, 9, 1981, pp Schmidt, Peter and Robin C. Sickles, "Production Frontiers and Panel Data", Journal of Business and Economic Statistics, Vol. 2, No. 4, 1984, pp Timmer, Marcel P., Mary O'Mahony, and Bart van Ark, EU KLEMS Growth and Productivity Accounts: An Overview, University of Groningen & University of Birmingham, Wakelin, K., "Productivity Growth and R&D Expenditure in UK Manufaturing Firms", Research Policy, Vol.30, No.7, 2001, pp. 1,079-1,090 Wang, Hung-Jen and Peter Schmidt, "One-Step and Two-Step Estimation of the Effects of Exogenous Variables on Technical Efficiency Levels", Journal of Productivity Analysis, 18, 2002, pp Wang J. C. and Tsai, K. H., Productivity Growth and R&D Expenditure in Taiwan s Manufacturing Firms, NBER Working Paper, 2003, pp

31 ABSTRACT This paper compared the technical efficiency of the secondary energy industries of 16 countries and studied the factors that affect technical efficiency. The estimation results indicated that the average technical efficiency of all 16 countries has been stable in a high level since An analysis of the 1st half ( ) and the 2nd half ( ) of the analysis period showed that average technical efficiency was almost the same. Also, the 16 countries were classified into three groups - European countries, Asian countries and the Anglo-American countries - and analyzed. As a result, the high technical efficiency in Asian countries was noticeable and European and Anglo-American countries showed relatively stable trend. In addition, the factors determining technical efficiency were analyzed with labor (education level), capital (capital intensity) and technology (national R&D investment) as variables. The results showed that technical efficiency improved as capital intensity was higher, the portion of low-education population was lower and a national R&D amount was higher. Keywords: secondary energy industry, technical efficiency, stochastic frontier analysis 141

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에너지경제연구 Korean Energy Economic Review Volume 10, Number 1, March 2011 : pp. 1~24 국내화력발전산업에대한연료와자본의대체성분석 1 2 3 ~ 4 5 F F P F P F ln ln ln ln ln ln ln ln ln ln ln ln ln ln ln ln ln 6 ln ln ln ln ln 7 ln