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on Corporate Finance |
| By: | Rachel Cho; Christoph Görtz; Danny McGowan; Max Schröder |
| Abstract: | We propose a new approach to identify firm-level financial constraints by applying artificial intelligence to text of 10-K filings by U.S. public firms from 1993 to 2021. Leveraging transformer-based natural language processing, our model captures contextual and semantic nuances often missed by traditional text classification techniques, enabling more accurate detection of financial constraints. A key contribution is to differentiate between constraints that affect firms presently and those anticipated in the future. These two types of constraints are associated with distinctly different financial profiles: while firms expecting future constraints tend to accumulate cash preemptively, currently constrained firms exhibit reduced liquidity and higher leverage. We show that only firms anticipating financial constraints exhibit significant cash flow sensitivity of cash, whereas currently constrained and unconstrained firms do not. This calls for a narrower interpretation of this widely used cash-based constraints measure, as it may conflate distinct firm types – unconstrained and currently constrained – and fail to capture all financially constrained firms. Our findings underscore the critical role of constraint timing in shaping corporate financial behavior. |
| Keywords: | financial constraints, artificial intelligence, expectations, cash, cash flow, corporate finance behavior |
| JEL: | G31 G32 D92 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_12054 |
| By: | Werdaningtyas, Hesti; Achsani, Nur Azam; Ratnawati, Anny; Irawan, Tony |
| Abstract: | This research investigates the factors that influence the capital structure of manufacturing companies in Indonesia. The novelty of this study lies in its advanced methodology, utilising a dynamic model, system-generalised methods of moments (Sys-GMM) estimation, and post-estimation analysis. Our study employs data from 159 publicly traded manufacturing firms. We focus on firm-specific factors, including leverage, profitability, sales, equity, and non-debt tax shields. Our findings suggest that determinant of leverage in Indonesian manufacturing firms, influenced by firm-specific factors and time-varying variables, particularly profitability, which has a negative impact on leverage. Firms with high profits are more likely to use internal sources of finance, whereas firms with low profitability are more likely to use loans, as they often lack sufficient retained earnings. Leverage among manufacturing firms exhibits persistence, as reflected by the significantly positive coefficient of the lagged leverage variable. This suggests that leverage decisions are path-dependent and gradually adjusted toward a long-term target. The time effect (year dummies) is significantly positive, indicating an upward trend in corporate leverage over time, which reflects the influence of macroeconomic conditions and fiscal/monetary policies on financing decisions. The practical implications of our research are significant, as it provides valuable insights into the capital structure and economic constraints of manufacturing companies in Indonesia, aiding management and other relevant stakeholders in making informed policy decisions. |
| Date: | 2025–08–06 |
| URL: | https://d.repec.org/n?u=RePEc:osf:osfxxx:grx8v_v1 |
| By: | Laura Álvarez-Román (Banco de España); Sergio Mayordomo (Banco de España); Carles Vergara-Alert (IESE Business School); Xavier Vives (IESE Business School) |
| Abstract: | We study a model of the impact of climate risk on credit supply and test its predictions using data on all wildfires and corporate loans in Spain. Our findings reveal a significant decrease in credit following climate-driven events. This result is driven by outsider banks (large and diversified), which reduce lending significantly to firms in affected areas. By contrast, due to their access to soft information, local banks (geographically concentrated) reduce their loans to opaque affected firms to a lesser extent without increasing their risk. We also find that employment decreases in affected areas where local banks are not present. |
| Keywords: | wildfire, asymmetric information, bank heterogeneity, firm lending. |
| JEL: | Q54 G21 G32 |
| Date: | 2024–02 |
| URL: | https://d.repec.org/n?u=RePEc:bde:wpaper:2406 |
| By: | Resendiz, Jose L.; Ranger, Nicola; Sulaeman, Johan; Broadstock, David C. |
| Abstract: | This paper examines Southeast Asia’s sustainability-linked finance (SLF) market—an emerging class of instruments that tie borrowing costs to sustainability outcomes—and its treatment of risks such as deforestation and biodiversity loss. Using market analysis and a retrieval-augmented generation approach to extract corporate-report data, we assess the alignment between Sustainability Performance Targets (SPTs), firms’ disclosed KPIs and the TNFD’s global guidance across 2017-2024, covering over 200 deals worth nearly USD 20 billion. Companies frequently report performance that exceeds their SPTs; although this appears positive, the excess metrics are not subject to SPT-level verification, weakening accountability and increasing greenwashing risk. We find that over 60% of nature-related KPIs—especially water and waste—are omitted from SPTs, exposing inconsistencies between what firms monitor and what their financiers reward. Sustainability-linked loans dominate activity, led by Singapore, Thailand and Indonesia, while other SLF instruments lag behind. We recommend aligning disclosures with SLF SPTs using emerging standards, accrediting financial institutions that act as sustainability coordinators to vet SPTs in the SLF deals, and introducing fiscal incentives like tax exemptions and credit guarantees to mobilise investment and reduce greenwashing risks. |
| Keywords: | nature-related risks; corporate reporting; sustainability-linked finance; key performance indicators |
| JEL: | G18 Q56 G32 K32 Q51 |
| Date: | 2025–06–26 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:129042 |
| By: | Xiaoyong (Jack) Fu; Lucian A. Taylor |
| Abstract: | How do investors choose the intensity of their due diligence, and how does that choice affect investment outcomes? Using cell phone signal data, we measure the duration of pre-investment meetings between venture capitalists (VCs) and startup employees. This measure captures one important component of VC due diligence. Less due diligence is associated with hotter deals and markets, busier investors, and greater distance, consistent with a theory of costly learning. Also consistent with that theory, less due diligence is associated with more volatile investment performance, as VCs allocate capital under greater uncertainty. Overall, VCs appear to trade off the costs of due diligence with its improvements to capital allocation. |
| JEL: | E22 G11 G24 |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:33987 |
| By: | Blaufus, Kay; Bock, Julian; Peuthert, Benjamin |
| Abstract: | Using unique tax audit data of 499 German firms, we analyze whether family firms, public firms, financially constrained firms, and those firms with managers with low tax morale substitute two tax strategies, book-tax conforming and nonconforming tax avoidance strategies, and examine the effect on overall tax avoidance. The empirical results are in line with family firms and those firms with low tax morale managers substituting conforming for nonconforming tax avoidance strategies, whereas public and financially constrained firms do the opposite. Moreover, we find that family firms differ from nonfamily firms only in their strategic implementation but not in the overall amount of tax avoidance. With respect to public, financially constrained firms and those firms with low tax morale managers, we find a positive association with the total level of tax avoidance. |
| Keywords: | conforming tax avoidance, tax planning, nontax costs, book-tax conformity |
| JEL: | H26 M41 G32 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:arqudp:323205 |
| By: | Joshua S. Gans |
| Abstract: | This paper examines how entrepreneurs strategically design experiments to convince venture capitalists (VCs) to fund their projects when investors interpret data through heterogeneous statistical frameworks. Drawing on Liang (2021)'s model of games with incomplete information played by statistical learners, we translate her abstract theoretical framework into a practical venture capital setting. We characterise how entrepreneurs balance funding plausibility against equity dilution by strategically choosing experiments along two critical dimensions: sample size (precision) and dimensionality (breadth of metrics). Our analysis reveals that for genuinely high-quality projects, increased precision helps by forcing VC beliefs to converge toward true quality. For low-quality projects, funding depends on preserving disagreement through sparse, high-dimensional experiments. The entrepreneur's optimal design depends critically on their prior beliefs: confident entrepreneurs choose high-precision, low-dimensional experiments that minimise equity dilution, while uncertain entrepreneurs opt for sparse, high-dimensional experiments that maximise the probability some VC will hold sufficiently optimistic beliefs. The framework provides a rigorous foundation for understanding how entrepreneurs and investors can rationally disagree when observing identical evidence, with significant implications for strategic information design in entrepreneurial settings. |
| JEL: | D83 G24 L26 |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34085 |