بررسی علل شکاف مخارج برق خانوارهای شهری-روستایی در ایران

نوع مقاله : علمی

نویسندگان

1 گروه اقتصاد، دانشکده اقتصاد و مدیریت، دانشگاه لرستان، خرم آباد، ایران

2 دانشیار گروه اقتصاد، دانشکده اقتصاد، دانشگاه مازندران

چکیده

هدف مطالعه حاضر استفاده از داده‌های در سطح خانوار برای دوره زمانی 1397-1389 و رهیافت مدل‌های تجزیه برای بررسی علل تفاوت مخارج برق خانوارهای روستایی و شهری است. نتایج رگرسیون چندک نشان می‌دهد که درآمد و بعد خانوار اثر منفی و معنی‌داری بر سهم مخارج انرژی دارد و اثر اندازه مسکن و دسترسی به لوازم خانگی دارای انرژی‌بری بالاتر، مثبت و معنی‌دار است. علاوه بر این مدل اکساکا-بلیندر نشان می‌دهد که  92 درصد از تفاوت سهم مخارج برق خانوارهای شهری و روستایی ناشی از تفاوت ویژگی‌های اقتصادی-اجتماعی خانوارها است. مدل ماچادو-متا نیز نشان می‌دهد که در چندک‌های پایین از سهم مخارج برق، سهم ناکارایی مصرف برق بیش از سهم تفاوت در ویژگی‌های اقتصادی-اجتماعی خانوارها است. از آنجا که تفاوت در دسترسی به امکانات دارای انرژی‌بری بالا سهم غالب را در تفاوت سهم مخارج برق خانوارها دارد، علت اصلی برای رشد مصرف برق خانوارها در ایران عمدتاً ناشی از تمایل برای دستیابی به سطح رفاه بالاتر است. بنابراین، استفاده از تجهیزات پرمصرف انرژی ممکن است نقش اساسی در کاهش انرژی مورد نیاز داشته باشد.

کلیدواژه‌ها

عنوان مقاله [English]

An Investigation of the Causes of Electricity Expenditure Gap in Urban-Rural Households in Iran

نویسندگان [English]

  • Leila Argha 1
  • Yousef Mehnatfar 2
1 Department of Economics, Lorestan University, khoram abad, Iran
2 Associate professor of Economics in Mazandaran University, Babolsar, Iran
چکیده [English]

Employing micro-data, quantile regression, as well as Oaxaca-Blinder and Machado-Mata decomposition models, this study investigated the causes of the existing gap in electricity consumption of the Iranian rural/urban households from 2010 to 2018. The quantile regression analysis showed that income and size of the family have a significant reverse effect on the amounts of energy expenditure. However, the building characteristics and access to high electricity-consuming appliances have a significant impact on the amounts of energy expenditure.  In addition, the Oaxaca-Blinder model showed that 92% of the gap in the electricity expenditures of the urban/rural households is due to differences in socio-economic characteristics of the households. The Machado-Mata model also showed that in areas with lower electricity expenditures, inefficiency in electricity consumption is more effective compared to the difference in the socio-economic characteristics of the households. Since the households’ access to high electricity-consuming appliances has a significant effect on the gap in their electricity expenditures, the main reason for the increase of electricity consumption in Iran is the desire to achieve a higher level of welfare.

کلیدواژه‌ها [English]

  • Decomposition Models
  • Household Electricity Expenditure
  • Inefficiency
  • Quantile Regression
  • Welfare

مراجع

Akbari, N., Talebi, H., & Jalaei, A. (2015). Investigating the social and cultural factors affecting household energy consumption after the implementation of the law on targeted subsidies (Case study: Isfahan). Applied Sociology, 64(9), 1-26. (In Persian)
Amiri, H., Yazdanikia, H., & Mohammadian, A. (2012). The relationship between energy consumption and income in the domestic and commercial sectors of Iran using the approach of gentle transfer regression models. Quarterly Journal of Economic Development Research, 8(11), 65-84. (In Persian)
Boogen, N. (2017). Estimating the potential for electricity savings in households. Energy Economics, 63(8), 288-300.
Chen, J. J., & Pitt, M. M. (2017). Sources of change in the demand for energy by Indonesian households: 1980–2002. Energy Economics, 61(4), 147-161.
Filippini, M., & Pachauri, S. (2004). Elasticities of electricity demand in urban Indian households. Energy Policy, 32(3), 429-436.
Gholizadeh, A., & Barati, J. (2011). Analysis of Factors Affecting Household Energy Consumption and Household Electricity Consumption in Iran, with Emphasis on Productivity. Quarterly Journal of Modern Economics and Trade, 25 & 26, 145-167. (In Persian)
Gram-Hanssen, K. (2013). Efficient technologies or user behaviour, which is the more important when reducing households’ energy consumption? Energy Efficiency, 6(3), 447-457.
Hasan, S. A., & Mozumder, P. (2017). Income and energy use in Bangladesh: A household level analysis. Energy Economics, 65(5), 115-126.
Huang, W.-H. (2015). The determinants of household electricity consumption in Taiwan: Evidence from quantile regression. Energy, 87(2), 120-133.
 Huebner, G., Shipworth, D., Hamilton, I., Chalabi, Z., & Oreszczyn, T. (2016). Understanding electricity consumption: A comparative contribution of building factors, socio-demographics, appliances, behaviours and attitudes. Applied energy, 177(5), 692-702.
 Jones, R. V., Fuertes, A., & Lomas, K. J. (2015). The socio-economic, dwelling and appliance related factors affecting electricity consumption in domestic buildings. Renewable and Sustainable Energy Reviews, 43(7), 901-917.
 Jones, R. V., & Lomas, K. J. (2015). Determinants of high electrical energy demand in UK homes: Socio-economic and dwelling characteristics. Energy and buildings, 101(10), 24-34.
 Kim, M.-J. (2018). Characteristics and determinants by electricity consumption level of households in Korea. Energy Reports, 4(12), 70-76.
 Long, C., Mills, B. F., & Schleich, J. (2018). Characteristics or culture? Determinants of household energy use behavior in Germany and the USA. Energy Efficiency, 11(3), 777-798.
 McLoughlin, F., Duffy, A., & Conlon, M. (2012). Characterising domestic electricity consumption patterns by dwelling and occupant socio-economic variables: An Irish case study. Energy and buildings, 48(6), 240-248.
 Morley, J., & Hazas, M. (2011). The significance of difference: Understanding variation in household energy consumption. eceee Proceedings  Summer Study, France, 2037-2046.
 Nesbakken, R. (1999). Price sensitivity of residential energy consumption in Norway. Energy Economics, 21(6), 493-515.
 Papageorgiou, G., Efstathiades, A., Poullou, M., & Ness, A. N. (2020). Managing household electricity consumption: a correlational, regression analysis. International Journal of Sustainable Energy, 39(5), 486-496.
 Rahimi, A., Marvat, H., &Faridzadeh, A. (2016). The role of attitudes and beliefs on household electricity consumption in Iran. Iranian Journal ofEnergy Economics, 21(8), 162-129. (In Persian)
 Sakah, M., du Can, S. d. l. R., Diawuo, F. A., Sedzro, M. D., & Kuhn, C. (2019). A study of appliance ownership and electricity consumption determinants in urban Ghanaian households. Sustainable Cities and Society, 44(5), 559-581.
 Salari, M., & Javid, R. J. (2017). Modeling household energy expenditure in the United States. Renewable and Sustainable Energy Reviews, 69(4), 822-832.  (In Persian)
 Schleich, J., Gassmann, X., Faure, C., & Meissner, T. (2016). Making the implicit explicit: A look inside the implicit discount rate. Energy Policy, 97(4), 321-331.
 Schultz, T. W. (1975). The value of the ability to deal with disequilibria. Journal of economic literature, 13(3), 827-846.
 Su, Y.-W. (2019). Residential electricity demand in Taiwan: Consumption behavior and rebound effect. Energy Policy, 124(11), 36-45.
 Tiwari, P. (2000). Architectural, demographic, and economic causes of electricity consumption in Bombay. Journal of Policy Modeling, 22(1), 81-98.
 Trotta, G. (2018). Factors affecting energy-saving behaviours and energy efficiency investments in British households. Energy Policy, 114(3), 529-539.
 Ye, Y., Koch, S. F., & Zhang, J. (2018). Determinants of household electricity consumption in South Africa. Energy Economics, 75(8), 120-133.
 Zhou, S., & Teng, F. (2013). Estimation of urban residential electricity demand in China using household survey data. Energy Policy, 61(4), 394-402.
پژوهشنامه اقتصاد کلان Macroeconomics Research Letter
دوره 16، شماره 31
شهریور 1400
صفحه 199-218

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سابقه مقاله

  • تاریخ دریافت: 03 دی 1399
  • تاریخ بازنگری: 29 اردیبهشت 1400
  • تاریخ پذیرش: 16 مرداد 1400

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