Evaluate the impact of demand management policies on electricity consumption saving in the household sector (Evidence from 31 provinces of Iran)

Document Type : Research Paper


1 Ph.D. Studnt of Economics, Islamic Azad University Abhar Branch.

2 Professor of Economics, University of Allameh Tabatabaee. emami@atu.ac.ir

3 Assistant Profosser of Economics, Islamic Azad University Abhar Branch.

4 Professor of Economics, Islamic Azad University Central Tehran Branch


The purpose of this study is to evaluate the impact of demand management policies on electricity consumption saving in the household sector in Iran during 2010-2017. The results confirm that household electricity demand is an inverse function of electricity price, household dimension, cooling requirement, and gas price in the second 5 months of the year and energy intensity index. Household electricity demand is also a direct function of gas prices in the summer, heating needs and income. According to the results, the average short-term and long-term price elasticity of electricity demand in Iran are estimated at -0.03 and -0.13, respectively. Electricity consumption in the previous period was the most influential variable in the trend of electricity consumption during the studied years in the domestic sector in Iran. Given the diversity of climate and the need for heating and cooling, which is one of the involuntary factors leading Iranian citizens to increase energy consumption, it is necessary to pay attention to non-price policies in the home and building sector


Main Subjects

  1. Alirezaei, A. T., & Tulaei, R. A. (2008). Productivity management by modifying the consumption pattern in the country's energy demand. Human Resource Management in the Oil Industry, 2(4), 31-59 (In Persian)
  2. Arellano, M., & Bond, S. (1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. The review of economic studies58(2), 277-297.
  3. Arellano, M., & Bover, O. (1995). Another look at the instrumental variable estimation of error-components models. Journal of econometrics68(1), 29-51.
  4. Alberini, A., & Filippini, M. (2011). Response of residential electricity demand to price: The effect of measurement error. Energy economics33(5), 889-895.
  5. Blundell, R., & Bond, S. (1998). Initial conditions and moment restrictions in dynamic panel data models. Journal of econometrics87(1), 115-143.
  6. Bohlmann, J. A., & Inglesi-Lotz, R. (2021). Examining the determinants of electricity demand by South African households per income level. Energy Policy148, 111901.
  7. Broin, E. Ó., Nässén, J., & Johnsson, F. (2015). Energy efficiency policies for space heating in EU countries: A panel data analysis for the period 1990–2010. Applied Energy150, 211-223.
  8. Broin, E. Ó., Nässén, J., & Johnsson, F. (2015). The influence of price and non-price effects on demand for heating in the EU residential sector. Energy81, 146-158.
  9. Chindarkar, N., & Goyal, N. (2019). One price doesn't fit all: An examination of heterogeneity in price elasticity of residential electricity in India. Energy Economics81, 765-778.
  10. Divanbagi, M. (2016). Investigating the role of non-price policies in optimizing energy consumption in Iran. Master Thesis in Environmental Economics, University of Kurdistan (In Persian).
  11. Emodi, N. V., Chaiechi, T., & Alam Beg, A. R. (2018). The impact of climate change on electricity demand in Australia. Energy & Environment29(7), 1263-1297.
  12. Eslami Andargoli, M., Sadeghi, H., & Mohammadi Khabazan, M. (2013). The effect of energy carrier price correction on different economic sectors using data-output table. Research on Sustainable Growth and Development (Economic Research), 13(2), 85-106 (In Persian).
  13. Eghbali, L. Ranjpour, R., & Sadeghi, k. (2020). Granger Causality Analysis of Energy Consumption and Value Added in Industrial Sub-Sectors of Iran: A Bootstrap Panel Approach. .Journal of Applied theories of economics, 7(3), 99-130.
  14. Frankel, J. A., & Rose, A. K. (1996). Currency crashes in emerging markets: An empirical treatment.Journal of international Economics, 41(3), 351-366.
  15. Hamidi Rozi, D., Ranjpour, R., & Motafaker Azad, M. A. (2019). Investigating the Effectiveness of Price Policies for Improving the Energy Consumption Pattern among the Provinces of the Country: A Dynamic Panel Data Approach. Economic Progress Policy, 7(1). 86-63 (In Persian).
  16. Jalaei, S. A. M., Jafari, S., & Ansari Lari, S. (2013). Estimation of household electricity demand function in Iran using provincial panel data. Iranian Energy Economics (Environmental and Energy Economics), 2(8), 69-92 (In Persian).
  17. Jones, R. V., & Lomas, K. J. (2015). Determinants of high electrical energy demand in UK homes: Socio-economic and dwelling characteristics. Energy and Buildings101, 24-34.
  18. Kao, C. (1999). Tests of dividend signaling using the Marsh-Merton model: a generalized friction approach. Journal of Business, 45-68.
  19. Labandeira, X., Labeaga, J. M., & López-Otero, X. (2017). A meta-analysis on the price elasticity of energy demand. Energy policy102, 549-568.
  20. Latif, E. (2015). A panel data analysis of the demand for electricity in Canada. Economic Papers: A journal of applied economics and policy34(3), 192-205.
  21. Levin, A., & Lin, C. F. (1992). Unit root tests in panel data: asymptotic and finite-sample properties.Journal of econometrics, 108(1), 1-24.
  22. Liddle, B., & Huntington, H. (2021). How prices, income, and weather shape household electricity demand in high-income and middle-income countries. Energy Economics95, 104995.
  23. Mohammadi, T., Khorsandi, M., & Fooladi Moghadam, Sh. A. (2015). Estimation of household electricity demand function with variable parameter during space-state approach time. Economic Progress Policy, 4(1), 119-140 (In Persian).
  24. Oh, S. H. (1996). Differential expression of bone morphogenetic proteins in the developing vestibular and auditory sensory organs.The Journal of neuroscience, 16(20), 64-75.
  25. Shah Moradi, A., Haghighi, I., & Zahedi, R. (2011). Investigating the effects of rising energy carrier prices and cash subsidies in Iran: The CGE approach. Economic Research and Policy, 19(57), 5-30 (In Persian).
  26. Sharif Azadeh, M. R., & Esmail Nia, A. R. (2006). Assessing the impact of demand management policies (price and non-price) on energy saving in the country using an integrated energy model. The Future of Management Research, 18, 19-32 (In Persian).
  27. Ullah, A., Neelum, Z., & Jabeen, S. (2019). Factors behind electricity intensity and efficiency: An econometric analysis for Pakistan. Energy Strategy Reviews26, 100371.
  28. Woo, C. K., Liu, Y., Zarnikau, J., Shiu, A., Luo, X., & Kahrl, F. (2018). Price elasticities of retail energy demands in the United States: New evidence from a panel of monthly data for 2001–2016. Applied energy222, 460-474.
  29. Wu, D. K. (1996). Differential expression of bone morphogenetic proteins in the developing vestibular and auditory sensory organs.The Journal of neuroscience, 16(20), 63-75.
  30. Yazdani Kia, H. (2012). Relationship between energy consumption structure and economic structure with energy intensity in Iran. Master Thesis in Environmental Economics, Tehran, Allameh Tabatabaei University (In Persian).