Skip to main content
Log in

Energy consumption by rural migrant workers and urban residents with a hukou in China: quality-of-life-related factors and built environment

  • Original Paper
  • Published:
Natural Hazards Aims and scope Submit manuscript

Abstract

This paper compares energy consumption (electricity, gasoline, and gas) by rural migrant workers and urban residents with a hukou (a China-specific household registration system) and influential factors (including quality-of-life [QOL]-related factors, built environment, and individual and household attributes) in China. A questionnaire survey was conducted in Dalian (a coastal city) in 2014 and in Guiyang (an inland city) in 2015, respectively. A zero-inflated negative binomial (ZINB) model was applied to understand whether and how much people consume a certain type of energy. The results showed that built environment explains 8.4–21.8% and 6.3–41.4% of the total variance in energy consumption by rural migrant workers and urban residents with a hukou. The corresponding variance related to QOL-related factors was 9.1–15.8% and 4.1–22.6%, respectively. The built environment was mostly associated with electricity consumed by urban residents with a hukou, while its influences on other types of energy consumption were moderate. Mixed effects of both built environment and QOL-related factors on reducing energy consumption were observed. Thus, it is context-sensitive whether and how much compact city development and social security policy affect residents’ energy consumption.

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

Access this article

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

Notes

  1. For energy consumption in China, see https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy/country-and-regional-insights/china.html (Accessed November 10, 2018).

  2. For urbanization rates in China, see http://www.gov.cn/guowuyuan/2018-02/04/content_5263778.htm (in Chinese, Accessed November 9, 2018).

References

  • Anderson JE, Wulfhorst G, Lang W (2015) Energy analysis of the built environment—a review and outlook. Renew Sustain Energy Rev 44:149–158

    Article  Google Scholar 

  • Chan KW, Zhang L (1999) The hukou system and rural–urban migration in China: processes and changes. China Q 160:818–855

    Article  Google Scholar 

  • Chen Q, Song Z (2014) Accounting for China’s urbanization. China Econ Rev 30:485–494

    Article  Google Scholar 

  • Cheng Z, Wang H (2013) Do neighbourhoods have effects on wages? A study of migrant workers in urban China. Habitat Int 38:222–231

    Article  Google Scholar 

  • Cheng Z, Nielsen I, Smyth R (2014) Access to social insurance in urban China: a comparative study of rural–urban and urban–urban migrants in Beijing. Habitat International 41:243–252

    Article  Google Scholar 

  • Cui Y, Tani M, Nahm D (2012) The determinants of employment choice of rural migrant workers in China: SOEs and non-SOEs. Procedia Econ Finance 1:98–107

    Article  Google Scholar 

  • Ding C, Liu C, Zhang Y, Yang J, Wang Y (2017) Investigating the impacts of built environment on vehicle miles traveled and energy consumption: differences between commuting and non-commuting trips. Cities 68:25–36

    Article  Google Scholar 

  • Dreger C, Zhang Y (2017) The Hukou impact on the Chinese wage structure. Discussion papers 1660, DIW Berlin, German Institute for Economic Research

  • Fan J-L, Liao H, Tang B-J, Pan S-Y, Yu H, Wei Y-M (2016) The impacts of migrant workers consumption on energy use and CO emissions in China. Nat Hazards 81(2):725–743

    Article  Google Scholar 

  • Greene WH (1994) Accounting for excess zeros and sample selection in Poisson and negative binomial regression models. Working paper EC-94-10, Department of Economics, Stern School of Business, New York University. http://ideas.repec.org/p/ste/nystbu/94-10.html. Accessed 22 July 2018

  • Jiang Y, Zhang J, Jin X, Ando R, Chen L, Shen Z, Ying J, Fang Q, Sun Z (2017) Rural migrant workers’ intentions to permanently reside in cities and future energy consumption preference in the changing context of urban China. Transp Res Part D: Transp Environ 52(B):600–618

    Article  Google Scholar 

  • Liu S, Xie F, Zhang H, Guo S (2014) Influences on rural migrant workers’ selection of employment location in the mountainous and upland areas of Sichuan, China. J Rural Stud 33:71–81

    Article  Google Scholar 

  • Lu L, Gong X, Zeng J (2016) Health status and migration: a propensity score matching with difference-in-difference regression approach. Lancet 388(Supplement 1):S60

    Article  Google Scholar 

  • National Bureau of Statistics of China (2017) Statistical Communique of the People’s Republic of China on the 2017 National Economic and Social Development. http://www.stats.gov.cn/english/pressrelease/201802/t20180228_1585666.html. Accessed 22 July 2018

  • Ning G, Qi W (2017) Can self-employment activity contribute to ascension to urban citizenship? Evidence from rural-to-urban migrant workers in China. China Econ Rev 45:219–231

    Article  Google Scholar 

  • Shen H, Chen Y, Russell AG, Hu Y, Shen G, Yu H, Henneman LRF, Rua M, Huang Y, Zhong Q, Chen Y, Li Y, Zou Y, Zeng EY, Fan R, Tao S (2018) Impacts of rural worker migration on ambient air quality and health in China: from the perspective of upgrading residential energy consumption. Environ Int 113:290–299

    Article  Google Scholar 

  • Wang P, Liu Z, Yang R (2017) An empirical study on rural household energy consumption influencing factors about migrant workers in the country. J Energy Nat Resour 6(4):52–57

    Article  Google Scholar 

  • Ward IC (2008) What are the energy and power consumption patterns of different types of built environment? Energy Policy 36(12):4622–4629

    Article  Google Scholar 

  • Wei T, Zhu Q, Glomsrød S (2014) Energy spending and household characteristics of floating population: evidence from Shanghai. Energy Sustain Dev 23:141–149

    Article  Google Scholar 

  • Xie Y, Jiang Q (2016) Land arrangements for rural–urban migrant workers in China: findings from Jiangsu Province. Land Use Policy 50:262–267

    Article  Google Scholar 

  • Xu L, Paterson AD, Turpin W, Xu W (2015) Assessment and Selection of competing models for zero-inflated microbiome data. PLoS ONE 10(7):e0129606. https://doi.org/10.1371/journal.pone.0129606

    Article  Google Scholar 

  • Yau K-K-W, Wang K, Lee AH (2003) Zero-inflated negative binomial mixed regression modeling of over-dispersed count data with extra zeros. Biomet J 45(4):437–452

    Article  Google Scholar 

  • Yu B (2012) Integrated analysis on household energy consumption behavior across residential and transport sectors: model development and applications. Doctoral Dissertation, Graduate School for International Development and Cooperation, Hiroshima University, Japan

  • Yu B, Zhang J, Fujiwara A (2012a) A household time use and energy consumption model with multiple behavioral interactions and zero-consumption. Environ Plan B 40(2):330–349

    Article  Google Scholar 

  • Yu B, Zhang J, Fujiwara A (2012b) Analysis of the residential location choice and household energy consumption behavior by incorporating multiple self-selection effects. Energy Policy 46:319–334

    Article  Google Scholar 

  • Yu B, Zhang J, Fujiwara A (2013) Rebound effects caused by the improvement of vehicle energy efficiency: an analysis based on an SP-off-RP survey. Transp Res Part D 24:62–68

    Article  Google Scholar 

  • Zhang J (2014) Revisiting the residential self-selection issues: a life-oriented approach. J Land Use Transp 7(3):29–45

    Article  Google Scholar 

  • Zhang J (2017b) Life-oriented behavioral research for urban policy. Springer, Tokyo

    Book  Google Scholar 

  • Zhang M, Song Y, Li P, Li H (2016a) Study on affecting factors of residential energy consumption in urban and rural Jiangsu. Renew Sustain Energy Rev 53:330–337

    Article  Google Scholar 

  • Zhang L, Sharpe RV, Li S, Darity WA (2016b) Wage differentials between urban and rural–urban migrant workers in China. China Econ Rev 41:222–233

    Article  Google Scholar 

  • Zhao C, Zhou X, Wang F, Jiang M, Hesketh T (2017) Care for left-behind children in rural China: a realist evaluation of a community-based intervention. Child Youth Serv Rev 82:239–245

    Article  Google Scholar 

  • Zhong B, Liu T, Chan SSM, Jin D, Hu C-Y, Dai J, Chiu HFK (2015) Prevalence and correlates of major depressive disorder among rural-to-urban migrant workers in Shenzhen, China. J Affect Disord 183:1–9

    Article  Google Scholar 

  • Zhu P, Zhao S, Wang L, Yammahi SA (2017) Residential segregation and commuting patterns of migrant workers in China. Transp Res Part D: Transp Environ 52:586–599

    Article  Google Scholar 

  • Zhu Y, Hu X, Yang B, Wu G, Wang Z, Xue Z, Shi J, Ouyang X, Liu Z, Rosenheck R (2018) Association between migrant worker experience, limitations on insurance coverage, and hospitalization for schizophrenia in Hunan Province, China. Schizophr Res 197:93–97

    Article  Google Scholar 

Download references

Acknowledgement

This research has been financially supported by a Grants-in-Aid for Scientific Research (B), Japan Society for the Promotion of Science (JSPS) (No. 26303003) and a Grants-in-Aid for Scientific Research (A), JSPS (No. 15H02271).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Junyi Zhang.

Additional information

Publisher's Note

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

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jiang, Y., Zhang, L. & Zhang, J. Energy consumption by rural migrant workers and urban residents with a hukou in China: quality-of-life-related factors and built environment. Nat Hazards 99, 1431–1453 (2019). https://doi.org/10.1007/s11069-019-03802-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11069-019-03802-1

Keywords

Navigation