IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v132y2024ics0140988324001865.html
   My bibliography  Save this article

Time preferences and energy consumption of rural household in China

Author

Listed:
  • Mao, Hui
  • Shi, Chaoqian
  • Tang, Heyan
  • Lu, Yufeng

Abstract

Recent empirical evidence suggests that time preferences have significant effects on intertemporal investment, saving behavior and asset pricing. However, limited research has been conducted on the impact of time preferences on energy consumption. This study aims to investigate the relationship between time preferences and energy consumption among rural households in China, using survey data collected on energy consumption patterns. The results reveal that as time preferences increase, there is a reduction in the diversity of energy sources used by households, and this finding remains robust after rigorous testing. Moreover, our findings support the applicability of the energy ladder theory in rural China, indicating that higher household income can mitigate the inhibiting effect of time preferences on the transition and improvement of energy sources. Additionally, policies promoting energy accessibility, raising awareness about high-quality energy sources, and facilitating credit access significantly promote rural households' advancement on the energy ladder toward superior-quality sources. These policy measures, along with heightened awareness and credit access, can alleviate time preference constraints on the energy transition of rural households. Consequently, we recommend enhancing future policies focusing on efficiency and providing customized financial support for energy initiatives.

Suggested Citation

  • Mao, Hui & Shi, Chaoqian & Tang, Heyan & Lu, Yufeng, 2024. "Time preferences and energy consumption of rural household in China," Energy Economics, Elsevier, vol. 132(C).
  • Handle: RePEc:eee:eneeco:v:132:y:2024:i:c:s0140988324001865
    DOI: 10.1016/j.eneco.2024.107478
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988324001865
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.eneco.2024.107478?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Esther Duflo & Michael Kremer & Jonathan Robinson, 2011. "Nudging Farmers to Use Fertilizer: Theory and Experimental Evidence from Kenya," American Economic Review, American Economic Association, vol. 101(6), pages 2350-2390, October.
    2. Lv, Yulan & Chen, Wei & Cheng, Jianquan, 2019. "Modelling dynamic impacts of urbanization on disaggregated energy consumption in China: A spatial Durbin modelling and decomposition approach," Energy Policy, Elsevier, vol. 133(C).
    3. Chen, Qiu & Huang, Jikun & Mirzabaev, Alisher, 2022. "Does fuel price subsidy work? Household energy transition under imperfect labor market in rural China," Energy Economics, Elsevier, vol. 107(C).
    4. Vu, D.H. & Muttaqi, K.M. & Agalgaonkar, A.P., 2015. "A variance inflation factor and backward elimination based robust regression model for forecasting monthly electricity demand using climatic variables," Applied Energy, Elsevier, vol. 140(C), pages 385-394.
    5. Richard G. Newell & Juha Siikamäki, 2015. "Individual Time Preferences and Energy Efficiency," American Economic Review, American Economic Association, vol. 105(5), pages 196-200, May.
    6. Michielsen, T.O., 2011. "The Distribution of Energy-Intensive Sectors in the US," Other publications TiSEM 2f7d55fe-e610-4ec4-8559-0, Tilburg University, School of Economics and Management.
    7. Maximilian Auffhammer & Catherine D. Wolfram, 2014. "Powering Up China: Income Distributions and Residential Electricity Consumption," American Economic Review, American Economic Association, vol. 104(5), pages 575-580, May.
    8. Liu, Haiying & Liu, Zexiao & Zhang, Chunhong & Li, Tianyu, 2023. "Transformational insurance and green credit incentive policies as financial mechanisms for green energy transitions and low-carbon economic development," Energy Economics, Elsevier, vol. 126(C).
    9. S. Tao & M. Y. Ru & W. Du & X. Zhu & Q. R. Zhong & B. G. Li & G. F. Shen & X. L. Pan & W. J. Meng & Y. L. Chen & H. Z. Shen & N. Lin & S. Su & S. J. Zhuo & T. B. Huang & Y. Xu & X. Yun & J. F. Liu & X, 2018. "Quantifying the rural residential energy transition in China from 1992 to 2012 through a representative national survey," Nature Energy, Nature, vol. 3(7), pages 567-573, July.
    10. Ubfal, Diego, 2016. "How general are time preferences? Eliciting good-specific discount rates," Journal of Development Economics, Elsevier, vol. 118(C), pages 150-170.
    11. Saidur, R., 2009. "Energy consumption, energy savings, and emission analysis in Malaysian office buildings," Energy Policy, Elsevier, vol. 37(10), pages 4104-4113, October.
    12. Drescher, Katharina & Janzen, Benedikt, 2021. "Determinants, persistence, and dynamics of energy poverty: An empirical assessment using German household survey data," Energy Economics, Elsevier, vol. 102(C).
    13. Damette, Olivier & Delacote, Philippe & Lo, Gaye Del, 2018. "Households energy consumption and transition toward cleaner energy sources," Energy Policy, Elsevier, vol. 113(C), pages 751-764.
    14. Niu, Shuwen & Zhang, Xin & Zhao, Chunsheng & Niu, Yunzhu, 2012. "Variations in energy consumption and survival status between rural and urban households: A case study of the Western Loess Plateau, China," Energy Policy, Elsevier, vol. 49(C), pages 515-527.
    15. Rong, Rong & Gnagey, Matthew & Grijalva, Therese, 2018. "“The less you Discount, the more it shows you really care”: Interpersonal discounting in households," Journal of Economic Behavior & Organization, Elsevier, vol. 154(C), pages 1-23.
    16. Schleich, Joachim & Gassmann, Xavier & Meissner, Thomas & Faure, Corinne, 2019. "A large-scale test of the effects of time discounting, risk aversion, loss aversion, and present bias on household adoption of energy-efficient technologies," Energy Economics, Elsevier, vol. 80(C), pages 377-393.
    17. Pothitou, Mary & Hanna, Richard F. & Chalvatzis, Konstantinos J., 2016. "Environmental knowledge, pro-environmental behaviour and energy savings in households: An empirical study," Applied Energy, Elsevier, vol. 184(C), pages 1217-1229.
    18. Doremus, Jacqueline M. & Jacqz, Irene & Johnston, Sarah, 2022. "Sweating the energy bill: Extreme weather, poor households, and the energy spending gap," Journal of Environmental Economics and Management, Elsevier, vol. 112(C).
    19. James Andreoni & Charles Sprenger, 2015. "Risk Preferences Are Not Time Preferences: Reply," American Economic Review, American Economic Association, vol. 105(7), pages 2287-2293, July.
    20. Grossman, Michael, 1972. "On the Concept of Health Capital and the Demand for Health," Journal of Political Economy, University of Chicago Press, vol. 80(2), pages 223-255, March-Apr.
    21. Ekholm, Tommi & Krey, Volker & Pachauri, Shonali & Riahi, Keywan, 2010. "Determinants of household energy consumption in India," Energy Policy, Elsevier, vol. 38(10), pages 5696-5707, October.
    22. Pang, Qinghua & Dong, Xianwei & Zhang, Lina & Chiu, Yung-ho, 2023. "Drivers and key pathways of the household energy consumption in the Yangtze river economic belt," Energy, Elsevier, vol. 262(PA).
    23. Finke, Michael S. & Huston, Sandra J., 2013. "Time preference and the importance of saving for retirement," Journal of Economic Behavior & Organization, Elsevier, vol. 89(C), pages 23-34.
    24. Hurwitz, Abigail & Sade, Orly, 2020. "An investigation of time preferences, life expectancy, and annuity versus lump sum choices: Can smoking harm long-term saving decisions?," Journal of Economic Behavior & Organization, Elsevier, vol. 180(C), pages 812-825.
    25. Aldossary, Naief A. & Rezgui, Yacine & Kwan, Alan, 2014. "Domestic energy consumption patterns in a hot and humid climate: A multiple-case study analysis," Applied Energy, Elsevier, vol. 114(C), pages 353-365.
    26. Tomomi Tanaka & Colin F. Camerer & Quang Nguyen, 2010. "Risk and Time Preferences: Linking Experimental and Household Survey Data from Vietnam," American Economic Review, American Economic Association, vol. 100(1), pages 557-571, March.
    27. Apadula, Francesco & Bassini, Alessandra & Elli, Alberto & Scapin, Simone, 2012. "Relationships between meteorological variables and monthly electricity demand," Applied Energy, Elsevier, vol. 98(C), pages 346-356.
    28. Donglan, Zha & Dequn, Zhou & Peng, Zhou, 2010. "Driving forces of residential CO2 emissions in urban and rural China: An index decomposition analysis," Energy Policy, Elsevier, vol. 38(7), pages 3377-3383, July.
    29. Wu, Shu & Han, Hongyun, 2022. "Energy transition, intensity growth, and policy evolution: Evidence from rural China," Energy Economics, Elsevier, vol. 105(C).
    30. Werthschulte, Madeline & Löschel, Andreas, 2021. "On the role of present bias and biased price beliefs in household energy consumption," Journal of Environmental Economics and Management, Elsevier, vol. 109(C).
    31. He, Shutong & Blasch, Julia & van Beukering, Pieter & Wang, Junfeng, 2022. "Energy labels and heuristic decision-making: The role of cognition and energy literacy," Energy Economics, Elsevier, vol. 114(C).
    32. Richard H. Thaler, 2016. "Behavioral Economics: Past, Present, and Future," American Economic Review, American Economic Association, vol. 106(7), pages 1577-1600, July.
    33. Michielsen, T.O., 2011. "The Distribution of Energy-Intensive Sectors in the US," Discussion Paper 2011-075, Tilburg University, Center for Economic Research.
    34. Susanna B. Berkouwer & Joshua T. Dean, 2022. "Credit, Attention, and Externalities in the Adoption of Energy Efficient Technologies by Low-Income Households," American Economic Review, American Economic Association, vol. 112(10), pages 3291-3330, October.
    35. Cayla, Jean-Michel & Maizi, Nadia & Marchand, Christophe, 2011. "The role of income in energy consumption behaviour: Evidence from French households data," Energy Policy, Elsevier, vol. 39(12), pages 7874-7883.
    36. Stephan Meier & Charles D. Sprenger, 2015. "Temporal Stability of Time Preferences," The Review of Economics and Statistics, MIT Press, vol. 97(2), pages 273-286, May.
    37. Zhu, Lin & Liao, Hua & Burke, Paul J., 2023. "Household fuel transitions have substantially contributed to child mortality reductions in China," World Development, Elsevier, vol. 164(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mao, Hui & Zhou, Li & Ying, RuiYao & Pan, Dan, 2021. "Time Preferences and green agricultural technology adoption: Field evidence from rice farmers in China," Land Use Policy, Elsevier, vol. 109(C).
    2. Jindrich Matousek & Tomas Havranek & Zuzana Irsova, 2022. "Individual discount rates: a meta-analysis of experimental evidence," Experimental Economics, Springer;Economic Science Association, vol. 25(1), pages 318-358, February.
    3. Heutel, Garth, 2019. "Prospect theory and energy efficiency," Journal of Environmental Economics and Management, Elsevier, vol. 96(C), pages 236-254.
    4. Thomas Meissner & Xavier Gassmann & Corinne Faure & Joachim Schleich, 2023. "Individual characteristics associated with risk and time preferences: A multi country representative survey," Journal of Risk and Uncertainty, Springer, vol. 66(1), pages 77-107, February.
    5. Groh, Elke D. & Ziegler, Andreas, 2022. "On the relevance of values, norms, and economic preferences for electricity consumption," Ecological Economics, Elsevier, vol. 192(C).
    6. Sébastien Foudi, 2024. "Are risk attitude, impatience, and impulsivity related to the individual discount rate? Evidence from energy-efficient durable goods," Theory and Decision, Springer, vol. 96(4), pages 627-661, June.
    7. Schleich, Joachim & Faure, Corinne & Meissner, Thomas, 2021. "Adoption of retrofit measures among homeowners in EU countries: The effects of access to capital and debt aversion," Energy Policy, Elsevier, vol. 149(C).
    8. Kureishi, Wataru & Paule-Paludkiewicz, Hannah & Tsujiyama, Hitoshi & Wakabayashi, Midori, 2021. "Time preferences over the life cycle and household saving puzzles," Journal of Monetary Economics, Elsevier, vol. 124(C), pages 123-139.
    9. Ubfal, Diego, 2016. "How general are time preferences? Eliciting good-specific discount rates," Journal of Development Economics, Elsevier, vol. 118(C), pages 150-170.
    10. Lan-Cui Liu & Gang Wu & Yue-Jun Zhang, 2015. "Investigating the residential energy consumption behaviors in Beijing: a survey study," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 75(1), pages 243-263, January.
    11. Jacopo Bonan & Philippe LeMay-Boucher & Douglas Scott, 2016. "Can Hypothetical Time Discounting Rates Predict Actual Behaviour: Evidence from a Randomized Experiment," Working Papers 2016.74, Fondazione Eni Enrico Mattei.
    12. Jakučionytė-Skodienė, Miglė & Liobikienė, Genovaitė, 2023. "Changes in energy consumption and CO2 emissions in the Lithuanian household sector caused by environmental awareness and climate change policy," Energy Policy, Elsevier, vol. 180(C).
    13. Chen, Jiahui & Liao, Hua & Zhang, Tong, 2024. "Empowering women substantially accelerates the household clean energy transition in China," Energy Policy, Elsevier, vol. 187(C).
    14. Li, Hui & Li, Yue & Zheng, Guoliang & Zhou, You, 2024. "Interaction between household energy consumption and health: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PA).
    15. Rachel Cassidy, 2018. "Are the poor so present-biased?," IFS Working Papers W18/24, Institute for Fiscal Studies.
    16. Bonan, Jacopo & LeMay-Boucher, Philippe & Scott, Douglas, 2022. "Can hypothetical measures of time preference predict actual and incentivised behaviour? Evidence from Senegal," World Development, Elsevier, vol. 159(C).
    17. Yao, Xi-Long & Liu, Yang & Yan, Xiao, 2014. "A quantile approach to assess the effectiveness of the subsidy policy for energy-efficient home appliances: Evidence from Rizhao, China," Energy Policy, Elsevier, vol. 73(C), pages 512-518.
    18. Zhu, Xiaodong & Zhu, Zheng & Zhu, Bangzhu & Wang, Ping, 2022. "The determinants of energy choice for household cooking in China," Energy, Elsevier, vol. 260(C).
    19. Lin, Boqiang & Jia, Huanyu, 2024. "Present-biased individuals and their underinvestment in household energy efficiency: Evidence from first-tier Chinese cities," Energy Policy, Elsevier, vol. 185(C).
    20. Jakučionytė-Skodienė, Miglė & Dagiliūtė, Renata & Liobikienė, Genovaitė, 2020. "Do general pro-environmental behaviour, attitude, and knowledge contribute to energy savings and climate change mitigation in the residential sector?," Energy, Elsevier, vol. 193(C).

    More about this item

    Keywords

    Energy consumption; Time preferences; Policy intervention; Energy perception; Credit;
    All these keywords.

    JEL classification:

    • R22 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Other Demand
    • R28 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Government Policy
    • D15 - Microeconomics - - Household Behavior - - - Intertemporal Household Choice; Life Cycle Models and Saving
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:eneeco:v:132:y:2024:i:c:s0140988324001865. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.