Skip to main content

Advertisement

SpringerLink
Log in

Estimating residential electricity demand’s response to price policy and income dynamics in China

  • Original Article
  • Published:
Energy Efficiency Aims and scope Submit manuscript

Abstract

This paper estimates the residential electricity demand’s response to price policy and income dynamics in China at both national and provincial levels, specifically in Anhui, Guizhou, Zhejiang, Jiangsu, and Jiangxi provinces, using the unbalanced panel partial adjustment model (PAM) and time-series PAM based on monthly data from January 2006 to October 2016. The empirical results show that the income elasticity of demand is inelastic in the short term on the whole while it is elastic in the long term and ranges from 0.807 to 2.371 in different provinces. The own-price elasticity of electricity demand is insignificant in most cases due to the government’s price regulation, leading to that the regulating effect of the electricity price policy, such as the tiered pricing policy, is weak. Overall, the residents’ income and seasonality are the most important driving forces of residential electricity consumption (REC). The price policy for pipeline natural gas has a significant effect on REC, and it would be an effective alternative option to regulate REC in China. This paper recommends reducing the upper limit of REC in each grade under the tiered tariff policy and further promoting the use of energy-efficient household appliances.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Notes

  1. Due to data unavailability, for Jiangsu Province, the time span of the household electricity consumption data is from January 2003 to October 2016, while the time span of the national-level data and of the other four provinces is from January 2006 to October 2016.

References

  • Alberini, A., & Filippini, M. (2011). Response of residential electricity demand to price: The effect of measurement error. Energy Economics, 33(5), 889–895.

    Article  Google Scholar 

  • Alberini, A., Gans, W., & Velez-Lopez, D. (2011). Residential consumption of gas and electricity in the US: The role of prices and income. Energy Economics, 33(5), 870–881.

    Article  Google Scholar 

  • Ang, B. W., Goh, T. N., & Liu, X. Q. (1992). Residential electricity demand in Singapore. Energy, 17(1), 37–46.

    Article  Google Scholar 

  • Beenstock, M., Goldin, E., & Nabot, D. (1999). The demand for electricity in Israel. Energy Economics, 21(2), 168–183.

    Article  Google Scholar 

  • Berkhout, P. H. G., Ferrer-i-Carbonell, A., & Muskens, J. C. (2004). The ex post impact of an energy tax on household energy demand. Energy Economics, 26(3), 297–317.

    Article  Google Scholar 

  • Bernard, J. T., Bolduc, D., & Yameogo, N. D. (2011). A pseudo-panel data model of household electricity demand. Resource and Energy Economics, 33(1), 315–325.

    Article  Google Scholar 

  • Billings, R. B. (1982). Specification of block rate price variables in demand models. Land Economics, 58(3), 386–394.

    Article  Google Scholar 

  • Blázquez, L., Boogen, N., & Filippini, M. (2013). Residential electricity demand in Spain: New empirical evidence using aggregate data. Energy Economics, 36, 648–657.

    Article  Google Scholar 

  • Bose, R. K., & Shukla, M. (1999). Elasticities of electricity demand in India. Energy Policy, 27(3), 137–146.

    Article  Google Scholar 

  • BP. (2014). BP statistical review of world energy 2014. Beyond Petroleum http://www.bp.com/statisticalreview.

  • Cheng, J. (2011). Energy efficiency labeling system & its development in China. The second U.S.-China Energy Efficiency Forum.

  • Cuddington, J. T., & Dagher, L. (2015). Estimating short and long-run demand elasticities: A primer with energy-sector applications. Energy Journal, 36(1).

  • Dilaver, Z., & Hunt, L. C. (2011). Modelling and forecasting Turkish residential electricity demand. Energy Policy, 39(6), 3117–3127.

    Article  Google Scholar 

  • Donatos, G. S., & Mergos, G. J. (1991). Residential demand for electricity: The case of Greece. Energy Economics, 13(1), 41–47.

    Article  Google Scholar 

  • Filippini, M. (2011). Short- and long-run time-of-use price elasticities in Swiss residential electricity demand. Energy Policy, 39(10), 5811–5817.

    Article  Google Scholar 

  • Filippini, M., & Pachauri, S. (2004). Elasticities of electricity demand in urban Indian households. Energy Policy, 32(3), 429–436.

    Article  Google Scholar 

  • Halicioglu, F. (2007). Residential electricity demand dynamics in Turkey. Energy Economics, 29(2), 199–210.

    Article  Google Scholar 

  • Holtedahl, P., & Joutz, F. L. (2004). Residential electricity demand in Taiwan. Energy Economics, 26(2), 201–224.

    Article  Google Scholar 

  • Hondroyiannis, G. (2004). Estimating residential demand for electricity in Greece. Energy Economics, 26(3), 319–334.

    Article  Google Scholar 

  • Houthakker, H. S. (1980). Residential electricity revisited. Energy Journal, 1, 29–41.

    Article  Google Scholar 

  • Houthakker, H. S., Verleger, P. K., & Sheehan, D. P. (1974). Dynamic demand analysis for gasoline and residential electricity. American Journal of Agricultural Economics, 56, 412–418.

    Article  Google Scholar 

  • Hung, M. F., & Huang, T. H. (2015). Dynamic demand for residential electricity in Taiwan under seasonality and increasing-block pricing. Energy Economics, 48, 168–177.

    Article  Google Scholar 

  • Hunt, L.C., Salgado, C., and Thorpe, A., 1998. The policy of power and the power of policy: Energy policy in Honduras. Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.

  • Liao, H., Liu, Y., Gao, Y., Hao, Y., Ma, X. W., & Wang, K. (2017). Forecasting residential electricity demand in provincial China. Environmental Science and Pollution Research, 24, 6414–6425.

    Article  Google Scholar 

  • Lin, B., & Jiang, Z. (2012). Designation and influence of household increasing block electricity tariffs in China. Energy Policy, 42, 164–173.

    Article  Google Scholar 

  • Lin, B., & Liu, X. (2013). Electricity tariff reform and rebound effect of residential electricity consumption in China. Energy, 59, 240–247.

    Article  Google Scholar 

  • Nakajima, T. (2010). The residential demand for electricity in Japan: An examination using empirical panel analysis techniques. Journal of Asian Economics, 21(4), 412–420.

    Article  Google Scholar 

  • Nakajima, T., & Hamori, S. (2010). Change in consumer sensitivity to electricity prices in response to retail deregulation: A panel empirical analysis of the residential demand for electricity in the United States. Energy Policy, 38(5), 2470–2476.

    Article  Google Scholar 

  • Narayan, P. K., & Smyth, R. (2005). The residential demand for electricity in Australia: An application of the bounds testing approach to cointegration. Energy Policy, 33(4), 467–474.

    Article  Google Scholar 

  • National Bureau of Statistics of China. (2019). China Statistical Yearbook 2019. China Statistical Publishing House.

  • Nordin, J. A. (1976). A proposed modification of Taylor’s demand analysis: Comment. Bell Journal of Economics, 719–721.

  • Paul, A. C., Myers, E. C., & Palmer, K. L. (2009). A partial adjustment model of US electricity demand by region, season, and sector. SSRN Electronic Journal, dp-08–dp-50.

  • Kamerschen, D.R, Porter, D.V., 2004. The demand for residential, industrial and total electricity, 1973–1998. Energy Economics, 26(1): 87-100.

  • Reiss, P. C., & White, M. W. (2005). Household electricity demand, revisited. The Review of Economic Studies, 72(3), 853–883.

    Article  Google Scholar 

  • Sa’ad, S. (2009). Electricity demand for South Korean residential sector. Energy Policy, 37(12), 5469–5474.

    Article  Google Scholar 

  • Shi, G., Zheng, X., & Song, F. (2012). Estimating elasticity for residential electricity demand in China. Scientific World Journal, 1–6.

  • Su, Y. W. (2018). Electricity demand in industrial and service sectors in Taiwan. Energy Efficiency, 11, 1541–1557.

    Article  Google Scholar 

  • Sun, C., & Lin, B. (2013). Reforming residential electricity tariff in China: Block tariffs pricing approach. Energy Policy, 60, 741–752.

    Article  Google Scholar 

  • Taylor, L. D. (1975). The demand for electricity: A survey. Bell Journal of Economics, 6, 74–110.

    Article  Google Scholar 

  • Yoo, S. H., Lee, J. S., & Kwak, S. J. (2007). Estimation of residential electricity demand function in Seoul by correction for sample selection bias. Energy Policy, 35(11), 5702–5707.

    Article  Google Scholar 

  • Zhou, S., & Teng, F. (2013). Estimation of urban residential electricity demand in China using household survey data. Energy Policy, 61, 394–402.

    Article  Google Scholar 

  • Zhou, N., Khanna, N., Feng, W., Ke, J., & Levine, M. (2018). Scenarios of energy efficiency and CO2 emissions reduction potential in the buildings sector in China to year 2050. Nature Energy, 3, 978–984.

    Article  Google Scholar 

  • Zin, A. A. B. M., & Moradi, M. (2019). An experimental investigation of price elasticity in electricity markets using a response surface methodology. Energy Efficiency, 12, 667–680.

    Article  Google Scholar 

  • Ziramba, E. (2008). The demand for residential electricity in South Africa. Energy Policy, 36(9), 3460–3466.

    Article  Google Scholar 

Download references

Funding

Supports from the National Natural Science Foundation of China under Grant No. 72001065, No. 71673266, and No. 71690245; National Key Research and Development Program of China under Grant No.2017YFE0101800; and the Fundamental Research Funds for the Central Universities of China under Grant No. JZ2019HGBZ0179 are acknowledged. All remaining errors are the authors’ own.

Author information

Authors and Affiliations

  1. School of Economics, Hefei University of Technology, Hefei, 230601, China

    Jun-Jun Jia

  2. Center for Energy and Environmental Policy Research, Institutes of Science and Development, Chinese Academy of Sciences, Beijing, 100190, China

    Jin-Hua Xu

Authors
  1. Jun-Jun Jia
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jin-Hua Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jin-Hua Xu.

Ethics declarations

Conflict of interest

The authors declare no competing interests.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Highlights

•Residential electricity demand’s elasticity is estimated on monthly frequency.

•The short-term income elasticity is less than 1 while the long-term is greater than

•Residents’ income and seasonality are important driving factors.

•Natural gas price policy could be an effective alternative option to regulate REC.

•The effect of tiered pricing policy on electricity conservation is weak.

Appendix

Appendix

Table 12 Variable definition, data sources, and the means to construct
Full size table
Table 13 Pearson correlation coefficients of HDD variables in five provinces
Full size table
Table 14 Pearson correlation coefficients of CDD variables in five provinces
Full size table
Table 15 Unit root tests for all time-series data in the model
Full size table

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jia, JJ., Xu, JH. Estimating residential electricity demand’s response to price policy and income dynamics in China. Energy Efficiency 14, 65 (2021). https://doi.org/10.1007/s12053-021-09974-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s12053-021-09974-9

Keywords

Search

Navigation