IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v77y2025ics1544612325003332.html
   My bibliography  Save this article

Does demolition compensation stimulate household allocation of financial assets

Author

Listed:
  • Yu, Jiaohui
  • Luo, Jinliang
  • Chen, Jian

Abstract

As a unique wealth transfer approach, demolition compensation (Compen) directly modifies households’ wealth foundations and exerts an influence on their investment behaviors and risk appetites. This study establishes an empirical model that includes moderating effects and uses the CHFS data to examine the manner in which demolition compensation impacts household financial assets allocation decisions. The results show that demolition compensation promotes the allocation of household financial assets (Fin), especially a greater preference for risky financial assets such as stocks. Household financial knowledge plays a moderating role in this. This facilitating effect is more pronounced in the central region and among urban households. The contributions of this study are threefold. First, we theoretically define demolition compensation as a kind of economic rent, not only arguing that it has the nature of a Ricardian rent, but it also explains the mechanisms by which psychological accounts, wealth loss expectations, loss aversion, and other characteristics impact the effect of demolition compensation on households’ financial asset choices by applying the basic principles of behavioral finance. Second, this study tests the specific impacts of demolition compensation on household financial asset allocation. Third, we consider the impact of financial literacy, constructing a model to reveal the mechanism of demolition compensation on household financial asset choices.

Suggested Citation

  • Yu, Jiaohui & Luo, Jinliang & Chen, Jian, 2025. "Does demolition compensation stimulate household allocation of financial assets," Finance Research Letters, Elsevier, vol. 77(C).
    • Handle: RePEc:eee:finlet:v:77:y:2025:i:c:s1544612325003332
    DOI: 10.1016/j.frl.2025.107069
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612325003332
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.frl.2025.107069?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Briggs, Joseph & Cesarini, David & Lindqvist, Erik & Östling, Robert, 2021. "Windfall gains and stock market participation," Journal of Financial Economics, Elsevier, vol. 139(1), pages 57-83.
    2. Zhao, Tianrui & Chen, Kezheng & Wang, Qian & Luo, Chunyang, 2023. "Financial literacy, liquidity constraits and household risk asset allocation," Finance Research Letters, Elsevier, vol. 58(PC).
    3. Li, Feng & Xiao, Jing Jian, 2020. "Losing the future: Household wealth from urban housing demolition and children's human capital in China," China Economic Review, Elsevier, vol. 63(C).
    4. Fu, Xiaoxia & Wang, Shanshan & Jia, Jia, 2024. "Equity incentives and dynamic adjustments to corporate financialization: Evidence from Chinese A-share listed companies," International Review of Economics & Finance, Elsevier, vol. 92(C), pages 948-966.
    5. Luo, Sumei & Sun, Yongkun & Zhou, Rui, 2022. "Can fintech innovation promote household consumption? Evidence from China family panel studies," International Review of Financial Analysis, Elsevier, vol. 82(C).
    6. Pengpeng Yue & Aslihan Gizem Korkmaz & Haigang Zhou, 2020. "Household Financial Decision Making Amidst the COVID-19 Pandemic," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 56(10), pages 2363-2377, August.
    7. Brown, Sarah & Gray, Daniel & Harris, Mark N. & Spencer, Christopher, 2021. "Household portfolio allocation, uncertainty, and risk," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 96-117.
    8. Chen, Haiyang & Dai, Ya & Guo, David, 2023. "Financial literacy as a determinant of market participation: New evidence from China using IV-GMM," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 611-623.
    9. Pengpeng Yue & Aslihan Gizem Korkmaz & Zhichao Yin & Haigang Zhou, 2021. "Household-owned Businesses’ Vulnerability to the COVID-19 Pandemic," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 57(6), pages 1662-1674, May.
    10. Pengpeng Yue & Aslihan Gizem Korkmaz & Haigang Zhou, 2020. "Household Financial Decision Making Amidst the COVID-19 Pandemic," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 56(10), pages 2363-2377, August.
    11. Wang, Shuo & Li, Chengyou & Wang, Zeru & Sun, Guanglin, 2023. "Digital skills and household financial asset allocation," Finance Research Letters, Elsevier, vol. 58(PC).
    12. Lu, Xiaomeng & Guo, Jiaojiao & Gan, Li, 2020. "International comparison of household asset allocation: Micro-evidence from cross-country comparisons," Emerging Markets Review, Elsevier, vol. 43(C).
    13. Ye, Xiang & Yue, Pengpeng, 2023. "Financial literacy and household energy efficiency: An analysis of credit market and supply chain," Finance Research Letters, Elsevier, vol. 52(C).
    14. Wu, Fan & Cui, Fengxiang & Liu, Tao, 2023. "The influence of digital inclusive finance on household wealth: A study based on CHFS data," Finance Research Letters, Elsevier, vol. 58(PC).
    15. Li, Bo & Huang, Yayi, 2023. "Uncertain random portfolio selection with different mental accounts based on mixed data," Chaos, Solitons & Fractals, Elsevier, vol. 168(C).
    16. Baulkaran, Vishaal, 2022. "Personal bankruptcy and consumer credit delinquency: The case of personal finance education," International Review of Financial Analysis, Elsevier, vol. 81(C).
    17. Ma, Chao & Zhang, Shuoxun, 2024. "Can housing booms elevate financing costs of financial institutions?," Journal of Development Economics, Elsevier, vol. 167(C).
    18. Bao, Haijun & Xu, Yueling & Zhang, Wenyu & Zhang, Shuai, 2020. "Has the monetary resettlement compensation policy hindered the two-way flow of resources between urban and rural areas?," Land Use Policy, Elsevier, vol. 99(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. Ni, Junwei & Gao, Yidan, 2025. "Opportunities for higher education for children, financial literacy and household capital," Finance Research Letters, Elsevier, vol. 78(C).
    2. Wang, Pengcheng & Yang, Xuelin, 2024. "Social trust and household financial decision-making: An empirical study based on the usage of household financial technology," Finance Research Letters, Elsevier, vol. 70(C).
    3. Hu, Siyang & Liu, Dongyang, 2025. "Digital economy, financial literacy, and financial risk-taking in rural households," International Review of Economics & Finance, Elsevier, vol. 98(C).
    4. Xiong, Wei & Jiang, Mengzhen & Liu, Yingying, 2024. "Digital economy, risk attitudes, and entrepreneurial decision-making in urban and rural households in China," International Review of Financial Analysis, Elsevier, vol. 96(PA).
    5. Li, Qianqian & Zhao, Zhengtang & Chen, Tingting, 2024. "The effect of public pension insurance integration on income disparities between urban-rural households: Evidence from a quasi-experiment in China," Finance Research Letters, Elsevier, vol. 66(C).
    6. He, Wei & Ling, Wenhao & Chen, Ziyi, 2025. "Financial literacy, old-age dependency ratio and household fraud risk," Finance Research Letters, Elsevier, vol. 75(C).
    7. Liu, Zhixiao & Zhang, Xue, 2025. "Commercial pension insurance and risky financial asset allocation: Evidence from elderly Chinese families," Finance Research Letters, Elsevier, vol. 77(C).
    8. Guo, Wei, 2024. "Income volatility and household commercial insurance allocation," Finance Research Letters, Elsevier, vol. 66(C).
    9. Liu, Chenyingzi & Zhang, Lei, 2024. "Retirement, confucian culture, and household financial asset allocation for older adults," International Review of Economics & Finance, Elsevier, vol. 95(C).
    10. Xie, Da & Zhang, Min & Bing, Pijing, 2025. "Manual task intensity and male-female wage gap: Evidence from China," Finance Research Letters, Elsevier, vol. 76(C).
    11. Qu, Bowen, 2025. "Pension levels, social activities, and household consumption," Finance Research Letters, Elsevier, vol. 75(C).
    12. Zhao, Dongfang & Gao, Genghe & Liu, Tao & Zhao, Zhenkun, 2024. "Population aging, digital divide, and household financial asset choices—An empirical study based on prefecture-level population census data," Finance Research Letters, Elsevier, vol. 66(C).
    13. Liu, Jiankun & Zhang, Yunliang & Ding, Chante Jian, 2024. "Political background, digital finance, and risky financial asset allocation," International Review of Economics & Finance, Elsevier, vol. 96(PA).
    14. Liu, Pingfen & Cai, Peifeng & Wang, Jing, 2025. "The dual driving mechanism of financial literacy and risky financial assets on household entrepreneurial decision-making," Finance Research Letters, Elsevier, vol. 72(C).
    15. Wang, Xinjian & Ding, Yihao & Dong, Qiang & Sun, Shuai & Chen, Zhixiao, 2025. "Impact of digital divide on household consumption: Role of mental health and happiness," International Review of Economics & Finance, Elsevier, vol. 99(C).
    16. Sun, Zhongyu & Li, Jun, 2025. "The impact of economic policy uncertainty on household portfolios effectiveness: Evidence from China," Finance Research Letters, Elsevier, vol. 78(C).
    17. Jiao, Lei & Lu, Sijin & Chen, Changchun & Feng, Yu, 2024. "Social security, relative deprivation, digital capacity, and household financial investment behavior," International Review of Financial Analysis, Elsevier, vol. 96(PB).
    18. Yang, Liuhui & Li, Ruoyi, 2025. "Government governance, family financial support, and financial well-being of the elderly: Evidence from CHARLS Data," Finance Research Letters, Elsevier, vol. 74(C).
    19. Li, Chao & Lao, Wenyu & Li, Xiang & Zhang, Yuhan, 2024. "Automated workforce, financial precarities and family consumption: The importance of demand-side policies under the background of automation applications," Economic Analysis and Policy, Elsevier, vol. 84(C), pages 1287-1308.
    20. Dong, Jingxuan, 2024. "Digital finance’s impact on household portfolio diversity: Evidence from Chinese households," Finance Research Letters, Elsevier, vol. 70(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    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:finlet:v:77:y:2025:i:c:s1544612325003332. 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/frl .

    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.