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Production Risk, Energy Use Efficiency and Productivity of Korean Industries

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Author Info

  • Khayyat, Nabaz T.

    ()
    (College of Engineering, Seoul National University)

  • Heshmati, Almas

    ()
    (Centre of Excellence for Science and Innovation Studies (CESIS) and Sogang University)

Abstract

Korea imports all of its primary energy, which leads to high dependency and vulnerability related to its energy supply. Efficiency in the use of energy is a way to reduce dependency and emissions. This study provides empirical results of the stochastic production process in energy use. Special attention is given to the factors that increase the risk or variation of using more of the energy input in production. A dynamic panel model is specified and applied to 25 Korean industrial sectors over the period 1970-2007. The determinants of energy use are identified and their effects in the form of elasticities of energy use are estimated. Stochastic production technology is applied to estimate an energy demand model based on an inverted factor demand. The findings reveal that: first, there are large variations in the degree of overuse or inefficiency in energy use among the individual industries as well as over time; second, information and communication technology (ICT) capital and labor are substituting for energy; and third, ICT capital input decreases the variability of energy demand while non-ICT capital, material and labor increase the variability of energy demand. The results suggest that technical progress contributes more to the increase in the mean energy demand than to the reduction in the level of risk. It is recommended that industries increase their level of ICT capital as well as digitalize and invest more in R&D activities and value added services to reduce the uncertainty related to their demand for energy.

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Bibliographic Info

Paper provided by Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies in its series Working Paper Series in Economics and Institutions of Innovation with number 359.

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Length: 27 pages
Date of creation: 31 Mar 2014
Date of revision:
Handle: RePEc:hhs:cesisp:0359

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Postal: CESIS - Centre of Excellence for Science and Innovation Studies, Royal Institute of Technology, SE-100 44 Stockholm, Sweden
Phone: +46 8 790 95 63
Web page: http://www.infra.kth.se/cesis/
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Keywords: Production risk; Energy use efficiency; Technical change; Stochastic production; Panel data; Industrial Sector; Korea;

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  1. Mark Coppejans & Donna Gilleskie & Holger Sieg & Koleman Strumpf, 2007. "Consumer Demand under Price Uncertainty: Empirical Evidence from the Market for Cigarettes," The Review of Economics and Statistics, MIT Press, vol. 89(3), pages 510-521, August.
  2. Subal Kumbhakar, 1997. "Efficiency estimation with heteroscedasticity in a panel data model," Applied Economics, Taylor & Francis Journals, vol. 29(3), pages 379-386.
  3. Almas Heshmati, 2001. "Labour demand and efficiency in Swedish savings banks," Applied Financial Economics, Taylor & Francis Journals, vol. 11(4), pages 423-433.
  4. Mary O'Mahony & Marcel P. Timmer, 2009. "Output, Input and Productivity Measures at the Industry Level: The EU KLEMS Database," Economic Journal, Royal Economic Society, vol. 119(538), pages F374-F403, 06.
  5. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
  6. Phoebe Koundouri & Céline Nauges & Vangelis Tzouvelekas, 2006. "Technology Adoption under Production Uncertainty: Theory and Application to Irrigation Technology," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 88(3), pages 657-670.
  7. Mukherjee, Kankana, 2008. "Energy use efficiency in U.S. manufacturing: A nonparametric analysis," Energy Economics, Elsevier, vol. 30(1), pages 76-96, January.
  8. Diewert, W E, 1974. "Functional Forms for Revenue and Factor Requirements Functions," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 15(1), pages 119-30, February.
  9. Elie Appelbaum & Aman Ullah, 1997. "Estimation Of Moments And Production Decisions Under Uncertainty," The Review of Economics and Statistics, MIT Press, vol. 79(4), pages 631-637, November.
  10. Fan, Ying & Liao, Hua & Wei, Yi-Ming, 2007. "Can market oriented economic reforms contribute to energy efficiency improvement? Evidence from China," Energy Policy, Elsevier, vol. 35(4), pages 2287-2295, April.
  11. Wansbeek, Tom & Kapteyn, Arie, 1989. "Estimation of the error-components model with incomplete panels," Journal of Econometrics, Elsevier, vol. 41(3), pages 341-361, July.
  12. Subal C. Kumbhakar & Ragnar Tveter�s, 2003. "Risk Preferences, Production Risk and Firm Heterogeneity," Scandinavian Journal of Economics, Wiley Blackwell, vol. 105(2), pages 275-293, 06.
  13. Welsch, Heinz & Ochsen, Carsten, 2005. "The determinants of aggregate energy use in West Germany: factor substitution, technological change, and trade," Energy Economics, Elsevier, vol. 27(1), pages 93-111, January.
  14. Zheng, Yingmei & Qi, Jianhong & Chen, Xiaoliang, 2011. "The effect of increasing exports on industrial energy intensity in China," Energy Policy, Elsevier, vol. 39(5), pages 2688-2698, May.
  15. Moss, Charles B. & Erickson, Kenneth W. & Ball, V. Eldon & Mishra, Ashok K., 2003. "A Translog Cost Function Analysis Of U.S. Agriculture: A Dynamic Specification," 2003 Annual meeting, July 27-30, Montreal, Canada 22027, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
  16. Tveteras, Ragnar & Flaten, Ola & Lien, Gudbrand D., 2008. "Production risk in multi-output industries: estimates from Norwegian dairy farms," 2008 International Congress, August 26-29, 2008, Ghent, Belgium 43958, European Association of Agricultural Economists.
  17. Just, Richard E. & Pope, Rulon D., 1978. "Stochastic specification of production functions and economic implications," Journal of Econometrics, Elsevier, vol. 7(1), pages 67-86, February.
  18. Sandmo, Agnar, 1971. "On the Theory of the Competitive Firm under Price Uncertainty," American Economic Review, American Economic Association, vol. 61(1), pages 65-73, March.
  19. Koundouri, Phoebe & Nauges, Celine, 2005. "On Production Function Estimation with Selectivity and Risk Considerations," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 30(03), December.
  20. Kamerschen, David R. & Porter, David V., 2004. "The demand for residential, industrial and total electricity, 1973-1998," Energy Economics, Elsevier, vol. 26(1), pages 87-100, January.
  21. Barry T. Coyle, 1999. "Risk Aversion and Yield Uncertainty in Duality Models of Production: A Mean-Variance Approach," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 81(3), pages 553-567.
  22. Christensen, Laurits R & Jorgenson, Dale W & Lau, Lawrence J, 1973. "Transcendental Logarithmic Production Frontiers," The Review of Economics and Statistics, MIT Press, vol. 55(1), pages 28-45, February.
  23. Hans Binswanger, 1980. "Attitudes toward risk: Experimental measurement in rural india," Artefactual Field Experiments 00009, The Field Experiments Website.
  24. Kumbhakar, Subal C. & Heshmati, Almas & Hjalmarsson, Lennart, 2000. "How Fast Do Banks Adjust? A Dynamic Model of Labor-Use with an Application to Swedish Banks," Working Paper Series in Economics and Finance 411, Stockholm School of Economics, revised Nov 2001.
  25. Cho, Won G. & Nam, Kiseok & Pagan, Jose A., 2004. "Economic growth and interfactor/interfuel substitution in Korea," Energy Economics, Elsevier, vol. 26(1), pages 31-50, January.
  26. Subal C. Kumbhakar, 2002. "Risk preference and productivity measurement under output price uncertainty," Empirical Economics, Springer, vol. 27(3), pages 461-472.
  27. Leonardo Becchetti & Luigi Paganetto & David Andres Londono Bedoya, 2003. "ICT Investment, Productivity and Efficiency: Evidence at Firm Level Using a Stochastic Frontier Approach," CEIS Research Paper 29, Tor Vergata University, CEIS.
  28. Abdelaziz, E.A. & Saidur, R. & Mekhilef, S., 2011. "A review on energy saving strategies in industrial sector," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(1), pages 150-168, January.
  29. Liu, Yaobin, 2009. "Exploring the relationship between urbanization and energy consumption in China using ARDL (autoregressive distributed lag) and FDM (factor decomposition model)," Energy, Elsevier, vol. 34(11), pages 1846-1854.
  30. Allan, Grant & Hanley, Nick & McGregor, Peter & Swales, Kim & Turner, Karen, 2007. "The impact of increased efficiency in the industrial use of energy: A computable general equilibrium analysis for the United Kingdom," Energy Economics, Elsevier, vol. 29(4), pages 779-798, July.
  31. Hurd, Brian H., 1994. "Yield Response And Production Risk: An Analysis Of Integrated Pest Management In Cotton," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 19(02), December.
  32. Urga, Giovanni & Walters, Chris, 2003. "Dynamic translog and linear logit models: a factor demand analysis of interfuel substitution in US industrial energy demand," Energy Economics, Elsevier, vol. 25(1), pages 1-21, January.
  33. Harvey, A C, 1976. "Estimating Regression Models with Multiplicative Heteroscedasticity," Econometrica, Econometric Society, vol. 44(3), pages 461-65, May.
  34. Asche, Frank & Tveteras, Ragnar, 1999. "Modeling Production Risk With A Two-Step Procedure," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 24(02), December.
  35. Fufa, B. & Hassan, Rashid M., 2003. "Stochastic maize production technology and production risk analysis in Dadar district, East Ethiopia," Agrekon, Agricultural Economics Association of South Africa (AEASA), vol. 42(2), June.
  36. Berndt, Ernst R & Wood, David O, 1975. "Technology, Prices, and the Derived Demand for Energy," The Review of Economics and Statistics, MIT Press, vol. 57(3), pages 259-68, August.
  37. Ragnar Tveteras & Ola Flaten & Gudbrand Lien, 2011. "Production risk in multi-output industries: estimates from Norwegian dairy farms," Applied Economics, Taylor & Francis Journals, vol. 43(28), pages 4403-4414.
  38. Caudill, Steven B & Ford, Jon M & Gropper, Daniel M, 1995. "Frontier Estimation and Firm-Specific Inefficiency Measures in the Presence of Heteroscedasticity," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(1), pages 105-11, January.
  39. Heshmati, Almas, 2000. "Productivity Growth, Efficiency and Outsourcing in Manufacturing and Service Industries," Working Paper Series in Economics and Finance 394, Stockholm School of Economics, revised 18 Oct 2001.
  40. Soytas, Ugur & Sari, Ramazan, 2009. "Energy consumption, economic growth, and carbon emissions: Challenges faced by an EU candidate member," Ecological Economics, Elsevier, vol. 68(6), pages 1667-1675, April.
  41. Griffin, James M & Gregory, Paul R, 1976. "An Intercountry Translog Model of Energy Substitution Responses," American Economic Review, American Economic Association, vol. 66(5), pages 845-57, December.
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