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1 에너지경제연구 Korean Energy Economic Review Volume 13, Number 2, September 2014 : pp. 171~197 국내신재생에너지 R&D 사업의 경제적성과분석 * 171

2 172

3 173

4 174

5 175

6 < 표 1> PSM 방법론을사용한정부사업의성과평가사례 176

7 177

8 178

9 Pr 179

10 min 지원을받은기업의성향지수 지원을받지않은기업의성향지수 정부의지원을받지않은기업전체 180

11 181

12 < 표 2> 분석에따른분류 182

13 < 표 3> R&D 지원을받은기업과지원을받지않은기업들의 기초통계량비교 183

14 184

15 < 표 4> R&D 지원사업의효과 ( 지원받은신재생에너지기업 vs. 일반 제조업기업 ) 185

16 < 표 5> R&D 지원사업의효과 ( 지원받은신재생에너지기업 vs. 지원받지않은신재생에너지기업 ) 186

17 < 표 6> R&D 지원사업의효과 ( 지원받은태양광기업 vs. 일반제조업기업 ) 187

18 < 표 7> R&D 지원사업의효과 ( 지원받은태양광기업 vs. 지원받지않은신재생에너지기업 ) 188

19 < 표 8> R&D 지원사업의효과 ( 지원받은비태양광기업 vs. 일반제조업기업 ) 189

20 < 표 9> R&D 지원사업의효과 ( 지원받은비태양광기업 vs. 지원받지않은신재생에너지기업 ) 190

21 < 표 10> R&D 지원사업의효과정리 191

22 192

23 접수일 (2014 년 8 월 12 일 ), 게재확정일 (2014 년 9 월 15 일 ) 193

24 , 2012., 15, , PSM DID, Information systems review 15, , 2008., R&D,, 16(4), 1-33., R&D :, 19, , R&D,, 10, 1-21., 2000,,, 1-134, 2013.,., 1998, R&D - -, 6(2), , 2009., 10, Almus, M. and Czarnitzki, D The effects of public R&D subsidies on firms innovation activities: the case of Eastern Germany, Journal of Business & Economic Statistics, 21(2), Becker, S. O., & Ichino, A Estimation of average treatment effects based on propensity scores. The Stata Journal, 2(4), Bloomberg New Energy Finance Global Renewable Energy Market Outlook Blundell, R. and Costa Dias, M Evaluation methods for non experimental data, 194

25 Fiscal Studies, 21(4), Busom, I An Empirical Evaluation of The Effects of R&D Subsidies, Economics of Innovation and New Technology, 9(2), Caliendo, M Microeconometric evaluation of labour market policies. Berlin: Springer. Carboni, O. A R&D subsidies and private R&D expenditures: evidence from Italian manufacturing data, International Review of Applied Economics, 25(4), Czarnitzki, D., Ebersberger, B., and Fier, A The relationship between R&D collaboration, subsidies and R&D performance : Empirical evidence from Finland and Germany, Journal of Applied Econometrics, 22, David, P. A., Hall, B. H., & Toole, A. A Is public R&D a complement or substitute for private R&D? A review of the econometric evidence. Research Policy, 29(4), Gorg, H. and Strobl, E The Effect of R&D Subsidies on Private R&D, Economica, 74(294), Klein, A.., Held. A., Ragwitz. M., Resch. G., and Faber.T Evaluation of different feed-in tariff design options- Best practice paper for the International Feed-in Cooperation Koshi, H Public R&D subsidies and empolyment growth-microeconomic evidence from Finnish firms, Keskusteluaiheita-Discussion Paper, Lerner, J The Government as Venture Capitalist: The Long-Run Impact of the SBIR Program, The Journal of Business, 72(3), Neyman, J. and Iwaszkiewicz, K Statistical problems in agricultural experimentation, Supplement to the journal of the Royal Statistical Society, 2(2), Piekkola, H. 2007, Public funding of R&D and Growth : Firm-level evidence from Finland, Economics of Innovation and New Technology, 16(3),

26 Quandt, R. E A new approach to estimating switching regressions, Journal of the American Statistical Association, 67(338), Rosenbaum, P. R., & Rubin, D. B The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), Rubin, D. B Estimating causal effects of treatments in randomized and nonrandomized studies, Journal of educational Psychology, 66(5), Wallsten, S. J The effects of government-industry R&D programs on private R&D: the case of the Small Business Innovation Research program, The RAND Journal of Economics, 31(1),

27 ABSTRACT The importance of renewable energy is all the more growing sharply as the necessity for climate change mitigation and energy security enhancement has been increasing. Korean Government also has been increasing the R&D support for renewable energy consistently and there has been considerable achievements in research paper publications and patent applications. Despite these kinds of efforts, however, as there has been questions whether the achievements of R&D in renewable energy is led to the creation of economic value. Therefore, the paper aims at analyzing the connection between the R&D support and the economic performance. Propensity Score Matching method which solves the issue of selectivity bias has been used for analysis. The result shows that the R&D support in Solar PV sector has a statistically significant effect on the growth and innovation of corporations while but not significant in non-pv sector. Key Words : Renewable Energy, R&D, Technology Commercialization, PSM, Outcome Evaluation JEL Codes : C19, H59, Q42 197

에너지경제연구 제13권 제1호

에너지경제연구 제13권 제1호 에너지경제연구 Korean Energy Economic Review Volume 13, Number 1, March 2014 : pp. 83~119 거시계량모형을이용한유가변동및 유류세변화의파급효과분석 * 83 84 85 86 [ 그림 1] 모형의해결정과정 87 [ 그림 2] 거시계량모형의흐름도 (flow chart) 88 89 < 표 1> 유류세현황 (2013