Christine Liu
Research
Research Interests
Financial Accounting: Credit Markets, Restructuring, Insolvency and Distress; Machine Learning, AI, Big Data and Alternative Sources of Information; Investment.
Working Papers
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Zombie firms—those whose operating profits persistently fail to cover debt servicing costs—crowd out healthy competitors, yet their survival mechanisms remain understudied. Using financial statement analysis and FinBERT-based textual analysis of corporate disclosures, we examine their restructuring activities. We find that operational restructuring, not financial restructuring alone, drives zombie firm recovery and leads to superior efficiency. Our findings extend the accounting literature on corporate disclosure and offer insights for managers, regulators, and policymakers.
[2] Creditor Rights and Related-Party Transactions: Evidence from the Implementation of the Insolvency Reforms in India
(with Ole-Kristian Hope and Dushyant Vyas) [SSRN]
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Revise and Resubmit (3rd Round at the Accounting Review)
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Using the enactment of the Insolvency and Bankruptcy Code (IBC) in 2016 as a quasi-experiment, we investigate whether enhanced creditor rights affect RPT levels for firms in India. We find that firms with greater reliance on unsecured credit (treatment firms) reduce their reliance on RPTs following the implementation of IBC.
[3] Out-of-Court Public Debt Restructuring and Debtholder-focused Investor Communication
(with Stacey Choy and Dushyant Vyas) [SSRN]
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We examine whether debtholder-focused investor communication activities (Debt IC), primarily conducted through in-person fixed income conferences, affect public debt out-of-court restructuring (OCR) outcomes. Successfully conducting OCR is challenging, as it generally requires near-unanimous consent from dispersed bondholders. Using a sample of financially distressed U.S. firms from 2006 to 2021, we find that Debt IC activities are positively associated with the likelihood of OCR over costly Chapter 11 bankruptcy, while generic and historical financial reporting information or untargeted investor outreach show no such effect. Our findings support two non-mutually exclusive channels through which Debt IC enhances OCR likelihood: (i) by reducing information frictions when future firm and macro-level uncertainty is high, and (ii) by mitigating coordination frictions among dispersed debtholders. Additionally, we find that companies increase Debt IC as distress levels rise, with its effectiveness on OCR success primarily concentrated among more distressed firms. Overall, our findings underscore the importance of Debt IC for financially distressed firms in increasing the likelihood and effectiveness of public debt OCR. We contribute to policy debates on efficient restructuring mechanisms that mitigate socioeconomic disruptions from business failures. Furthermore, the context of our study allows us to more generally shed light on the efficacy of targeted stakeholder communication during crisis periods.
[4] The Effects of Mandatory Supplier Finance Program Disclosure: Evidence from the Credit Markets
(with Philip G. Berger and Minjia Li)
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We examine mandatory Supplier Finance Program disclosure's impact on credit markets using FASB's 2022 amendment. Following mandated disclosure, firms with higher SFP dependence face increased bond yields, especially those with greater default risk. Affected firms reduce SFP usage, shift toward public debt, and experience credit downgrades, highlighting disclosure's market consequences.
[5] Voluntary or Forced CEO Turnover? Asymmetric Information, Disclosure Strategies, and Market Reactions
(with Kose John, Xu Tian, and Haofei Zhang)
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Abstract: Using a hand-collected sample of 1419 CEO turnover announcements gathered from Factiva News, we study the market reaction to CEO turnover announcements in the presence of information frictions. Our results suggest that firms act strategically when disclosing information about CEO turnover to avoid a negative market reaction.
[6] Signals or Smoke? The Determinants and Informativeness of Corporate Artificial Intelligence (AI) Disclosures
(with John M. Barrios, John L. Campbell, and Ryan G. Johnson) (SSRN)
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Abstract: Artificial Intelligence (AI) has emerged as a transformative General Purpose Technology (GPT), yet significant uncertainty around firms’ AI investments remains due to their intangible and opaque nature. We examine the characteristics of firms that disclose AI activities, and whether these disclosures provide credible signals of firms’ underlying AI investments and their future economic outcomes. Using advanced textual analysis of corporate disclosures and detailed firm-level data on AI employment, we document four key findings. First, firms that disclose AI activities are generally innovative, operate in AI-intensive industries, and face greater investor scrutiny. Second, AI disclosures are positively associated with subsequent operational efficiency and AI patent filings, even after accounting for firms’ investment in AI human capital. This indicates that disclosure not only signals AI investment but also managers’ confidence in its expected returns. Third, firms that align high AI disclosures with substantial AI employment exhibit greater operational benefits than those with mismatches. Finally, these aligned firms significantly outperform peers in long-term stock returns, highlighting the crucial role of complementary human capital investment in unlocking AI’s potential. Our findings underscore that AI disclosures provide investors with a signal about firms’ underlying investments as well as managers’ confidence in those investments, thereby facilitating the market’s assessment of firms’ technological adoption and growth prospects.
[7] Value Relevance of Corporate Consumer Data: Evidence from Website Cookies (with Junhao Liu and Jennifer Tucker)
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Abstract: We examine how Big Data, specifically website cookies and traffic data, relate to firm value and performance. We find that the volume of cookie-collected data positively associates with stock value beyond traditional accounting measures, and with common Wall Street valuation multiples. The data volume also predicts current and future financial performance, while being negatively associated with SG&A expenses and unrelated to recognized intangible assets. These findings contribute to discussions about accounting for intangibles in the digital economy.
Other Publications
An Empirical Study of the Impact of Demographics on Growth and Inflation in Japan (Link)
(with Niklas Westlius, IMF Working Paper 16/237, December 2016; Journal of International Commerce, Economics and Policy, Volume 08, Issue 02, June 2017)
Abstract: Is Japan’s aging and, more recently, declining population hampering growth and reflation efforts? Exploiting demographic and economic variation in prefectural data between 1990 and 2007, we find that aging of the working age population has had a significant negative impact on total factor productivity. Moreover, prefectures that aged at a faster pace experienced lower overall inflation, while prefectures with higher population growth experienced higher inflation. The results give strong support to the notion that demographic headwinds can have a non-trivial impact on total factor productivity and deflationary pressures.
Advancing financial inclusion in Micronesia (Link)
(IMF 2016 Article IV Consultation, Republic of Timor-Leste, IMF Country Report. No. 16/183)
Abstract: Financial inclusion appears more conducive to economic growth at an early stage. Higher financial inclusion impacts financial stability, enabling banks to build solid liquidity buffers, especially during periods of stress, while indirectly boosting firms’ resilience. This box analyzes the position of Micronesia on macro-finance and provides policy advice to the country authority.
Transition to Sustainable Development Goals (Link)
(IMF 2016 Article IV Consultation, Republic of Timor-Leste, IMF Country Report. No. 16/183)
Abstract: The note evaluates the development of the social sector in Timor-Leste, applying the framework of the United Nations’ Sustainable Development Goals which transited from the previous Millennium Development Goals. It also describes the role that the IMF could play to help TLS achieve SDG through both policy support and technical assistance.