Estimating the Rebound Effect of Electricity Consumption in Iran: Threshold Level Approach

Document Type : Research Paper

Authors

1 Assistant Professor of Economics, Alzahra University

2 Ph.D. in Economics, Allameh Tabataba'i University

Abstract

The literature on energy economics suggests a rebound effect of improving energy efficiency. Given the fact that existing rebound effect causes the electricity saving (due to the improvement of the efficiency of consumer electric appliances in the residential sector) be less than expected, the present paper based on the time series data of 1357-1395, uses linear and threshold models to estimate the direct rebound effect of residential electricity consumption in different scenarios. The results of linear model show that the direct rebound effect of residential electricity consumption in Iran during the period 1357-1395 is on average 81%. The results of the other model (threshold model), taking into account the two variables of Gross domestic product (GDP) per capita and cooling degree days (CDD) as threshold variables, show that decrease in GDP per capita and increase in cooling degree days will increase the direct rebound effect of residential electricity consumption.

Keywords

Main Subjects


  1. Allan, G., Hanley, N., McGregor, P., Swales, K., and Turner, K. (2007). The impact of increased efficiency in the industrial use of energy: A computable general equilibrium analysis for the United Kingdom. Energy Economics, 29, 779-798.
  2. Ang, B., Goh, T., and Liu, X. (1992). Residential electricity demand in Singapore. Energy, 17, 37-46.
  3. Belaid, F., Bakaloglou, S., and Roubaud, D. (2018). Direct rebound effect of residential gas demand: Empirical evidence from France. Energy Policy, 115, 23–31.
  4. Berkhout, P., Muskens, J., and Velthuijsen, J. (2000). Defining the Rebound Effect. Energy Policy, 28, 425-432.
  5. Bessec, M, and Fouquau, J. (2008). The non-linear link between electricity consumption and temperature in Europe: a threshold panel approach. Energy Economics, 30, 2705-2721.
  6. Carcedo, J., and Otero, J. (2005). Modeling the non-linear response of Spanish electricity demand to temperature variations. Energy Economics, 27, 477-494.
  7. Delangizan, S., Khanzadi, A., and Heidarian, M. (2017). Estimation and Analysis of Direct Rebound Effects Caused by Improving Fuel Consumption Efficiency in Iran's Road Transportation Sector. Quarterly Journal of Applied Economic Studies of Iran, 6(21), 149-182 (In Persian).
  8. Dimitropoulos, J., and Sorrell, S. (2006). The rebound effect: microeconomic definitions, extensions and limitations. In Proceedings of the 29th IAEE International Conference, Potsdam, Germany.
  9. Duncan, R. (2015). A Threshold Model of the US Current Account. Economic Modeling, 48, 270-280.
  10. Esmailnia, A., and Ekhtyari, S. (2012). Investigating the Rebound Effects of Improving Vehicle Efficiency on Fuel Consumption. Quarterly Journal of Energy Economics, 9(34), 185-213 (In Persian).
  11. Emamverdi, G., Karimi, M., and Sadeghi, H. (2017). Threshold and asymmetric analysis of leverage ratio on profitability of active companies in Tehran Stock Exchange. Financial Economics, 39, 57-81 (In Persian).
  12. Energy Balance (2015). Ministry of Power (In Persian).
  13. Hansen, B. (1999). Threshold effects in non-dynamic panels: Estimation, testing, and inference. Journal of Econometrics, 93, 345-368.
  14. http://www.tavanir.org.ir/
  15. http://sdwebx.worldbank.org/climateportal/index.cfm
  16. Khoshkalam Khosroshahi, M., Jahangard, E., and Abedian, M. (2015). Improving the efficiency of gasoline consumption and its Rebound effects in various economic activities. Quarterly Journal of Energy Economics, 12(44), 37-63 (In Persian).
  17. Khoshkalam Khosroshahi, M. (2017). Investigating Economic Effects of Application of Non-Price Policies on the Consumption of Energy Carriers. Quarterly Journal of Economic Modeling Research, 8(29), 37-72 (In Persian).
  18. Lam, J. (1998). Climatic and economic influences on residential electricity consumption. Energy Conversion and Management, 39, 623-629.
  19. Lin, B., and Li, J. (2014). The rebound effect for heavy industry: Empirical evidence from China. Energy Policy, 74(C), 589-599.
  20. Lu, Y., Liu, Y., and Zhou, M. (2016). Rebound effect of improved energy efficiency for different energy types: A general equilibrium analysis for China. CAMA Working Paper 38/2016.
  21. Manzoor, D., Aghababaie, E., and Hagigi, I. (2010). Analysis of the Rebound Effects Caused by Improving Efficiency in Electricity Consumption in Iran: A Computable General Balance Model. Quarterly Journal of Energy Economics, 8(28), 1-23 (In Persian).
  22. Salem, A., and Akaberi, M. (2017). Estimating the direct rebound effect of improving the efficiency of power consumption in the residential sector of the urban areas of Iran. Journal of Energy Economics of Iran, 6(22), 45-74 (In Persian).
  23. Saunders, H. (1992). The Khazzoom-Brookes postulate and neoclassical growth. The Energy Journal, 13(4), 131.
  24. Sorrell, S. (2007). UKERC review of evidence for the rebound effect.
  25. Sorrell, S., Dimitropoulos, J., and Sommerville, M. (2009). Empirical estimates of the direct rebound effect: A review. Energy Policy, 37, 1356-1371.
  26. Central Bank of Iran, Time series databank.
  27. Thomas, B., and Azevedo, I. (2013). Estimating direct and indirect rebound effects for U.S. households with input–output analysis. Part 2: Simulation. Ecological Economics, 86, 188-198.
  28. Wangpattarapong, K., Maneewan, S., Ketjoy, N., and Rakwichian, W. (2008). The impacts of climatic and economic factors on residential electricity consumption of Bangkok Metropolis. Energy Buildings, 40, 1419-1425.
  29. Wei, T., and Liu, Y. (2017). Estimation of global rebound effect caused by energy efficiency improvement. Energy Economics, 66, 27-34.
  30. Zhang, M., Song, Y., Li, P., and Li, H. (2016). Study on affecting factors of residential energy consumption in urban and rural Jiangsu. Renewable and Sustainable Energy Reviews, 53, 330-337.