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Does opening high-speed railways affect the cost of debt financing? A quasi-natural experiment

Author

Listed:
  • Hongling Guo
  • Keping Wu

Abstract

Purpose - This study aims to investigate how opening high-speed railways affects the cost of debt financing based on China's background. Design/methodology/approach - Using panel data on Chinese listed firms from 2008 to 2017, this study constructs a quasi-natural experiment and adopts a difference-in-difference model with multiple time periods to empirically examine the relation between the high-speed railway openings and debt financing cost. Findings - Our results show that opening high-speed railways reduces the cost of debt financing, and this negative correlation is more significant in non-state firms, firms with weaker internal control, and firms that hire non-Big Four auditors. Besides, we explore the impact mechanisms and find that opening high-speed railways improves analyst attention, institutional investor participation, and information disclosure quality, which in turn lowers the cost of debt financing. Research limitations/implications - The results imply that the opening of high-speed railways helps to alleviate the information asymmetry and adverse selection between firms and creditors and ultimately reduces the cost of corporate debt financing. Practical implications - This paper can inform firms and stakeholders about the impact of opening high-speed railways on debt financing cost: it improves the information environment, reduces the geographical location restrictions of debt financing, ensures the reasonable pricing of corporate debt, and thus promotes the healthy and sound development of the debt market. Originality/value - This paper provides theoretical support and empirical evidence for the impact of infrastructure construction on the information environment of the debt market in China, which enriches the research on the “high-speed railway economy.” In addition, as an exogenous event, the opening of high-speed railways instantly shortens the time distance between firms and external stakeholders, which gives us a natural environment to conduct empirical research, thus providing a new perspective for financial research on firms' geographical location.

Suggested Citation

  • Hongling Guo & Keping Wu, 2020. "Does opening high-speed railways affect the cost of debt financing? A quasi-natural experiment," China Finance Review International, Emerald Group Publishing Limited, vol. 10(4), pages 473-496, May.
    • Handle: RePEc:eme:cfripp:cfri-06-2019-0083
    DOI: 10.1108/CFRI-06-2019-0083
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    Citations

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    Cited by:

    1. Chen, Kejing & Guo, Wenqi & Jiang, Lin & Xiong, Xiong & Yang, Mo, 2022. "Does time-space compression affect analyst forecast performance?," Research in International Business and Finance, Elsevier, vol. 62(C).
    2. Ye, Yongwei & Zeng, Lin & Tao, Yunqing & Yun, Feng, 2023. "Tax authority monitoring and corporate information disclosure quality in China," International Review of Financial Analysis, Elsevier, vol. 90(C).
    3. Huang, Yingshan & Ouyang, Haiqin & Pan, Weihua & He, Xiaogang, 2023. "Role of high-speed rail services in China’s economic recovery: Evidence from manufacturing firm inventories," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 389-405.
    4. Chen, Yu & Wang, Yuandi & Zhao, Changyi, 2023. "How do high-speed rails influence city carbon emissions?," Energy, Elsevier, vol. 265(C).
    5. Xie, Linlin & Liu, Yangbo & Jiang, Tianhao, 2024. "Executives with business education background and cost of debt financing: Evidence from China," International Review of Economics & Finance, Elsevier, vol. 90(C), pages 283-296.
    6. Lin, Chunpeng & Yang, Jinqiang, 2022. "Entrepreneur’s incentives for risk-taking and short-term debt," International Review of Financial Analysis, Elsevier, vol. 84(C).
    7. Sun, Wenhao & Gao, Jijun & Jacoby, Gady & Wu, Zhenyu, 2024. "Access to capital and energy efficiency: How high-speed rail investments benefit high-tech firms," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 91(C).
    8. Wang, Li & Wu, Yiqi & Chen, Yaxin & Dai, Yunhao, 2023. "Distance produces the fear of loss: Customer geographic proximity and corporate cash holdings," International Review of Financial Analysis, Elsevier, vol. 87(C).
    9. Liang, Dawei & Pan, Yukun & Du, Qianqian & Zhu, Ling, 2022. "The information content of analysts’ textual reports and stock returns: Evidence from China," Finance Research Letters, Elsevier, vol. 46(PB).
    10. Liu, Guangqiang & Wang, Shenghua, 2023. "Digital transformation and trade credit provision: Evidence from China," Research in International Business and Finance, Elsevier, vol. 64(C).
    11. Si, Deng-Kui & Wan, Shen & Li, Xiao-Lin & Kong, Dongmin, 2022. "Economic policy uncertainty and shadow banking: Firm-level evidence from China," Research in International Business and Finance, Elsevier, vol. 63(C).
    12. Li, Wanli & Lai, Yin & Wang, Chaohui & Tan, Bowen, 2022. "How do emerging debt market participants recognize firm internationalization?Evidence from effects on credit ratings," Emerging Markets Review, Elsevier, vol. 53(C).
    13. Lee, Chien-Chiang & Wang, Chih-Wei, 2022. "Liquidation threat: Behavior of CEO entrenchment," Finance Research Letters, Elsevier, vol. 47(PA).

    More about this item

    Keywords

    High-speed railway; Debt financing; Information asymmetry; H63; L92;
    All these keywords.

    JEL classification:

    • H63 - Public Economics - - National Budget, Deficit, and Debt - - - Debt; Debt Management; Sovereign Debt
    • L92 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Railroads and Other Surface Transportation

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