Advertisement

Discussion of the Results and Policy Implications

  • Nabaz T. KhayyatEmail author
Chapter
  • 535 Downloads
Part of the Green Energy and Technology book series (GREEN)

Abstract

This chapter summarizes the findings from the estimated models. The empirical results are summarized for (i) The mean in case of production function and energy demand function without risk, and (ii) for the mean and variance function in the case of energy demand accounting for risk , in which the findings are related to the theory of the competitive firm under production risk. The empirical results are also discussed in relation to the information available about the industrial sector for the data period. Furthermore, the chapter covers the implications and policy recommendations based on the estimated models for production function and energy demand.

Keywords

Energy Demand Technical Efficiency Energy Price Output Elasticity Industry Code 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. Becchetti, L., Bedoya, D., & Paganetto, L. (2003). ICT investment, productivity and efficiency: Evidence at firm level using a stochastic frontier approach. Journal of Productivity Analysis, 20(2), 143–167. doi: 10.1023/A:1025128121853.CrossRefGoogle Scholar
  2. Benjamin, D., & Meza, F. (2009). Total factor productivity and labor reallocation: The case of the Korean 1997 crisis. B E Journal of Macroeconomics, 9(1), 1–39. doi: 10.2202/1935-1690.1625.CrossRefGoogle Scholar
  3. Cho, W. G., Nam, K., & Pagan, J. A. (2004). Economic growth and interfactor/interfuel substitution in Korea. Energy Economics, 26(1), 31–50. doi: 10.1016/j.eneco.2003.04.001.CrossRefGoogle Scholar
  4. Fai, A. H. T., & Cornelius, P. L. (1996). Approximate F-tests of multiple degree of freedom hypotheses in generalized least squares analyses of unbalanced split-plot experiments. Journal of Statistical Computation and Simulation, 54(4), 363–378. doi: 10.1080/00949659608811740.MathSciNetCrossRefzbMATHGoogle Scholar
  5. Fan, Y., Liao, H., & Wei, Y.-M. (2007). Can market oriented economic reforms contribute to energy efficiency improvement? Evidence from China. Energy Policy, 35(4), 2287–2295. doi: 10.1016/j.enpol.2006.07.011.CrossRefGoogle Scholar
  6. Fukao, K., Miyagawa, T., & Pyo, H. K. (2009). Estimates of multifactor productivity, ICT contributions and resource reallocation effects in japan and korea. RIETI Discussion Paper Series 09-E-021. Retrieved from The Research Institute of Economy, Trade and Industry http://www.rieti.go.jp/jp/publications/dp/09e021.pdf.
  7. Gallant, A. R. (2008). Nonlinear statistical models. Wiley.Google Scholar
  8. Greene, W. H. (2008). Econometric analysis (7th ed.). Prentice Hall.Google Scholar
  9. Harvey, A. C. (1976). Estimating regression-models with multiplicative heteroscedasticity. Econometrica, 44(3), 461–465. doi: 10.2307/1913974.MathSciNetCrossRefzbMATHGoogle Scholar
  10. IEA, I. E. A. (2011). Climate & Electricity Annual: Data and Analysis. International Energy Agency. Retrieved from IEA http://www.iea.org/publications/freepublications/.
  11. Johnston, J. (1984). Econmetric methods (3rd ed.). New York: Mc-Graw-Hill.Google Scholar
  12. Kamerschen, D. R., & Porter, D. V. (2004). The demand for residential, industrial and total electricity, 1973–1998. Energy Economics, 26(1), 87–100. doi: 10.1016/S0140-9883(03)00033-1.CrossRefGoogle Scholar
  13. Lee, W. N., Kim, H. J., Park, J. B., Roh, J. H., & Cho, K. S. (2012). An economic evaluation of the energy efficiency programs in Korea. Journal of International Council on Electrical Engineering, 2(2), 219–224.CrossRefGoogle Scholar
  14. Liu, Y. (2009). Exploring the relationship between urbanization and energy consumption in China using ARDL (autoregressive distributed lag) and FDM (factor decomposition model). Energy, 34(11), 1846–1854. doi: 10.1016/j.energy.2009.07.029.CrossRefGoogle Scholar
  15. Moss, C. B., Erickson, K. W., Ball, V. E., & Mishra, A. K. (2003). A Translog Cost Function Analysis of U.S. Agriculture: A Dynamic Specification. http://EconPapers.repec.org/RePEc:ags:aaea03:22027.
  16. Tsunoda, J., Inui, T., & Takeuchi, A. (2000). Environmental conservation by Japan’s electric power industry: An example of the electric power development company. In W. C. et al. (Eds.) Protecting the global environment; initiatives by Japanese business (pp. 77–79). Washington, DC: World Bank.Google Scholar
  17. Welsch, H., & Ochsen, C. (2005). The determinants of aggregate energy use in West Germany: factor substitution, technological change, and trade. Energy Economics, 27(1), 93–111. doi: 10.1016/j.eneco.2004.11.004.CrossRefGoogle Scholar
  18. Zheng, Y., Qi, J., & Chen, X. (2011). The effect of increasing exports on industrial energy intensity in China. Energy Policy, 39(5), 2688–2698. doi: 10.1016/j.enpol.2011.02.038.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  1. 1.Technology Management, Economics, and Policy Program, College of EngineeringSeoul National UniversitySeoulSouth Korea

Personalised recommendations