Abstract

Using online lending microdata, I show that sleep has important consequences for household financial outcomes. I find that insufficient sleep has a significant impact on credit risk, particularly for loans that are applied for in the early morning. This effect diminishes as the day progresses, with applications submitted later in the afternoon and evening being unaffected. For identification, I apply a spatial regression discontinuity design leveraging exogenous discontinuities in sunset time across time zone boundaries, supplemented by additional identification strategies, including daylight savings time shifts. The results also suggest that the psychological mechanism behind this effect is increased levels of heuristic thinking resulting from the cognitive deficits commonly associated with sleep loss. Overall, the evidence indicates sleep has important implications for household financial behavior and welfare

Abstract

This paper constructs and studies a comprehensive data set comprised of corporate executive presentations. Executive presentations are unique in that they provide an abundance of visual information about a firm’s project designs and production plans. In the aggregate, these presentations allow us to explore the value of visual information and examine how market participants with varying levels of technological access respond to such information. Using a state-of-the-art deep learning model, we extract forward-looking operational information from presentation slide images. We find that short-term abnormal returns are positively associated with forward-looking operational information, but not with backward-looking or financial information. AI-equipped financial institutions respond strongly to visual signals, whereas other institutions and retail investors do not. Our study provides novel evidence that AI adoption rewards investors with an informational advantage, creating a potential AI divide among market participants.

Abstract

We analyze the effect of corporate investments in fintech startups on startup performance and on the future performance of investing firms. Corporate investment in fintech startups is associated with greater successful exit likelihood; more and higher quality innovation; and higher inflow of high-quality inventors. We establish causality using an IV analysis. A stacked difference-in-differences analysis shows that such investments enhance the product market performance and equity market valuation of corporate investors belonging to the financial services sector, but not those in the nonfinancial sector. We show that formation of strategic alliances between investors and fintech startups drive these performance improvements.

Abstract

Increasing levels of digitisation makes firms more susceptible to cyberattacks and privacy violations. In this paper, we quantify the impact of cybercrime on company stock returns, using a large international sample. In the day after the cyber event, stock returns are found to decrease by -0.25% but the effect reverses in about two weeks. The magnitude of the stock market decrease is greatest for companies which have experienced reoccurring events and for breaches deemed to be severe. Finally, we show that the extent of the stock market decline is related to company specific characteristics, including size, volatility, credit ranking and asset volatility. The empirical results highlight important policy and regulatory issues, not least the need for cyber risk disclosure requirements.

Abstract

We document that low cybersecurity risk firms are more likely to be involved in M&A transactions. Mergers are significantly less likely to be withdrawn if the target has a weak cybersecurity risk profile. Merger premium are higher for mergers involving low cybersecurity risk acquirers. Deals involving low cybersecurity risk firms yield superior post-merger operating performance and are less likely to trigger goodwill impairments. Announcement returns have also started to reflect cybersecurity risk in recent years. These findings offer novel evidence on the economic impact of cybersecurity risk on the market for corporate control.

Abstract

This paper uses ChatGPT, a large language model, to extract managerial expectations of corporate policies from disclosures. We create a firm-level ChatGPT investment score, based on conference call texts, that measures managers’ anticipated changes in capital expenditures. We validate the ChatGPT investment score with interpretable textual content and its strong correlation with CFO survey responses. The investment score predicts future capital expenditure for up to nine quarters, controlling for Tobin’s q, other predictors, and fixed effects, implying the investment score provides incremental information about firms’ future investment opportunities. The investment score also separately forecasts future total, intangible, and R&D investments. High-investment-score firms experience significant negative future abnormal returns adjusted for factors, including the investment factor. We demonstrate ChatGPT’s applicability to measure other policies, such as dividends and employment. ChatGPT revolutionizes our comprehension of corporate policies, enabling the construction of managerial expectations cost-effectively for a large sample of firms over an extended period.

Abstract

Conventional approaches to analyzing structural data have historically limited our economic understanding of innovation. This paper pushes the boundaries, taking an LLM approach to patent analysis with the novel ChatGPT technology. I develop deep learning predictive models that incorporate OpenAI’s textual embedding features to access complex, intricate information about the quality and impact of each invention. These models achieve an R-squared score of 42% predicting patent value, 23% for patent citations, and clearly isolate the worst and best applications. My techniques also enable a revision to the contemporary Kogan, Papanikolaou, Seru, and Stoffman (2017) valuation of patents with a median deviation of 1.5 times, accounting for potential institutional anticipation and generating substantial incremental value for economic applications. Furthermore, the application-based measures provide previously inaccessible latent information regarding corporate innovative productivity; a long-short portfolio based on predicted acceptance rates achieves significant abnormal returns of 3.3% annually. The models provide an opportunity to reinvent startup and small-firm corporate policy vis-à-vis patenting.

Abstract

This paper identifies the reallocation of human capital as a key channel of agglomeration spillovers for innovative firms. To measure agglomeration spillovers, I study how R&D labs in different local labor markets respond differently to scientific breakthroughs, which create large and unexpected shocks to innovation productivity in certain technology categories. Taking advantage of U.S. Census longitudinal establishment data matched with patent records, I systematically locate R&D labs in all local labor markets for each firm. I document four main findings. First, following scientific breakthroughs, affected labs in thicker local labor markets (i.e., commuting zones with more inventors innovating in a certain field) produce more patents and higher-quality patents, consistent with positive agglomeration spillovers. Second, the increase in patenting is mostly attributed to new hires rather than incumbent inventors. Third, the thick labor market effect is concentrated in states and industries where there is lower enforceability of non-compete agreements and labor is more mobile. Finally, using textual analysis to identify lab-level exposure to scientific breakthroughs, I find that inventors are reallocated to labs that are more favorably affected by shocks, which helps labs in thicker labor markets to more easily bring in inventors working in the same niche fields and having a diverse knowledge base. Taken together, these results point to labor mobility as a key force in explaining why innovative firms cluster, and suggest that the clustering of firms in thick labor markets can foster corporate innovation by facilitating productivity-enhancing reallocation of human capital following scientific breakthroughs.

Abstract

This study investigates the follow-on funding scenario of token-backed companies (e.g., companies that issued ICOs and STOs). Our sample comprises 523 successfully funded STOs and ICOs issued in the USA and Europe from 2015 to 2021 and combines data from token portals, CrunchBase, CryptoFund Research, and Orbis. 12% of the ventures failed after the token offerings while 31% went after at least one follow-on round, an IPO, or an M&A. Adopting competing risk proportional hazards models we investigate the determinants of follow-on rounds. Our results show that previous investment rounds, the presence of crypto funds during the token offerings, and the type of token issued affect the probability of raising additional money. In particular, utility token-backed companies are more attractive to subsequent investors than security-token-backed companies. Our results suggest different roles of token offering over the firm financing life cycle.

Abstract

This paper takes into account the differences between crypto-coins and crypto-tokens, and investigate the performances of cross-sectional return predictors based on a large sample solely consisting of utility tokens (over 1,000 ERC-20 tokens). Besides the most famous and longstanding predictors such as size and momentum, we thoroughly examine the fundamental-related predictors formed by using on-chain variables including dollar-value of transactions, transfer counts and unique active addresses, which reflect real economic activity on the blockchain and proxy intrinsic values of the tokens. We further construct a pricing-factor model including a quasi value factor, which is a counterpart of the value factor HML in equity market. By following Fama and French (1996), we found that the pricing model could to some extent explain the excess returns of 25 double-soring portfolios.

Abstract

Non-Fungible Tokens (NFTs) offer a unique opportunity to study market misconduct in an unregulated crowdfunding environment. This paper examines insider and wash trading in the NFT market using publicly accessible Ethereum blockchain data. Results reveal that insider purchases, particularly by those maintaining community ties, significantly predict future price returns. Despite over 422 million USD circulating in wash trades, their impact on market outcomes is negligible. This paper also highlights motivations behind wash trading, such as securing marketplace rewards or promoting emerging platforms.

Abstract

We document that the majority of venture-capital backed financing r ounds a re n ot accompanied by a Form D filing. We s how t hat fi ling be havior is pr edictable an d is re lated to both the ability to fly below the radar and the benefits of withholding in formation. Financing rounds that are harder to hide, larger offerings and those p reviously c overed by media, a re m ore likely file a Form D while financing rounds by firms with greater proprietary information, early stage firms o r c ompanies i n b iotech, p harmaceutical, a nd h igh t ech i ndustries, a re l ess l ikely t o file a Form D. We document one adverse outcome to the filing o f a Form D, p atent litigation, and show that protection from this type of litigation through the enactment of anti-patent trolling laws subsequently increases the rate of filing. F irms a re l ess l ikely t o fi le a Fo rm D on ce the form is required to be filed on E dgar. Finally, we note that reliance on Regulation D is stronger as the firm n ears a n e xit f rom t he p rivate m arket. O ur r esults s uggests t hat s ome fi rms view even minimal disclosure and regulatory oversight as costly.

Abstract

This paper provides the first empirical investigation of the information content of use of proceeds disclosure in private equity (PE)-backed initial public offerings (IPOs). We find evidence consistent with the idea that PE-backed issuers primarily use the IPO as a means of repaying claimholders. PE-backed issuers that state ‘repay debt’ as the use of proceeds occur frequently in our sample. These issuers have high ex-ante leverage ratios and use the IPO proceeds to revert to more normal leverage ratios after the IPO. This finding suggests that PE ownership only leads to a temporary increase in optimal leverage ratio. Further results indicate that the overwhelming importance of repaying claimholders in PE-backed IPOs has negative ripple effects on the implementation of other stated use-of-proceeds categories such as R&D. Finally, we document that the certification effect of PE-backing mitigates the adverse impact of vague use of proceeds on underpricing. Hence, in PE-backed IPOs there is no costly tradeoff between higher underpricing due to vagueness and the risk of revealing proprietary information due to specificity

Abstract

How much does firm intangibility amplify CEOs’ persistent private information and reduce firms’ public listing propensity? We develop a model of competing public and private investors financing firms heterogeneously exposed to persistent private cash flows. Equilibrium financing is driven by information rent differentials in CEO compensation. We validate and structurally estimate the model using firm listing and CEO compensation data. We find private (intangible) cash flows exhibit 63% higher persistence than their tangible counterparts. Further, if firm intangibility levels returned to those of 1980, mean listing propensities would increase 5 percentage points while mean CEO variable pay growth would decrease by 61%.

Abstract

The Consumer Financial Protection Bureau (CFPB) publicly disclosed consumer complaint narratives in 2015. Utilizing a difference-in-differences design, I discover that, following disclosure, CFPB-supervised banks whose complaint narratives are disclosed are less prone to discriminate against minority borrowers in the mortgage lending market, thereby reducing racial disparities in interest rates, default rates, and rejection rates. My findings reveal that disclosure saves $102 million for minority borrowers in interest rate payments and assists over 14,000 minority households in obtaining loans yearly. Furthermore, other stakeholders, such as peer banks and stock market investors, facilitate the disclosure’s effects on reducing discrimination.

Abstract

We discover that the social capital of the community in which households live positively influences the likelihood that their mortgage applications are approved, the terms of approved mortgages, and the subsequent performance on those mortgages. The results hold when conditioning on household and community characteristics and an array of fixed effects, including individual effects data permitting, and when employing instrumental variables and propensity score matching to address identification and selection concerns. Concerning causal mechanisms, evidence suggests that social capital enhances lender screening and monitoring of borrowers and increases the social costs to borrowers from defaulting on their debts.

Abstract

This paper proposes a mechanism to address the “monitoring with small stakes” puzzle in syndicated lending. We identify two sources that incentivize creditor monitoring: “skin in the game” and rent extraction from renegotiation. Renegotiation-based rent extraction serves as a substitute to banks’ loan stakes, facilitating institutional investors’ participation in syndicated lending. We use the passage of a tax policy that exogenously reduced renegotiation frictions to empirically identify this mechanism. we find that a less frictional renegotiation environment leads to more diligent monitoring, smaller bank shares in new loans, and improved borrower performance, particularly in pre-existing deals with lower bank shares.

Abstract

We study the impact of recent increases in mortgage lenders’ litigation risk on borrowers. In the last decade, the U.S. Department of Justice brought suits against many of the largest lenders in the FHA mortgage market, alleging fraud under the False Claims Act. These suits led to over $5.4 billion in settlements and caused targeted banks and their peers to precipitously exit the FHA market. A combination of difference-in-differences and triple differences tests exploiting geographic variation in exposure to exiting banks show a 19% reduction in aggregate FHA lending in heavily affected areas. Smaller non-bank lenders with higher historical misconduct rates partially filled the void in the FHA market, highlighting potential unintended consequences of aggressive consumer financial protection litigation.

Abstract

Information technology plays a key role in the consumer credit market, by shaping the way lenders underwrite borrowers. We study how the adoption of information technology by lenders affects approval decisions, pricing, and repayment in the U.S mortgage market. We assemble a loan-level dataset that covers the trajectory of mortgages from application to repayment and combine it with detailed information about information technology investment by lenders. We empirically identify that higher investment in information technology leads lenders to increase approval rates for loan applications, introduce greater granularity in their pricing, and create portfolios with better ex-post performance. A simple model of investment, underwriting and pricing is developed to explain our empirical findings.

Abstract

Low-income and Black households are less likely to visit bank branches than high-income and White households, despite the former two groups appearing to rely more on branches as means of bank participation. We assess whether unequal branch access can explain that disparity. We propose a measure of bank branch access based on a gravity model of consumer trips to bank branches, estimated using mobile device geolocation data. Residents have better branch access if branches are closer or have superior qualities that attract more visitors. Because the geolocation data is distorted to protect user privacy, we estimate the gravity model with a new econometric method that adapts the Method of Simulated Moments to handle high-dimensional fixed effects. We find no evidence that low-income communities lack access to bank branches and instead find that lower demand for bank branch products or services explains their lower branch use. But in Black communities, worse access explains their entire drop-off in branch use. For residents of these areas, weaker access is not from having lower quality branches, but from branches being located farther away from them. The results highlight parts of the country that would benefit the most from policies that expand access to banking.

Abstract

The prevailing agency theory framework in executive compensation studies highlights the conflict of interest between managers and shareholders. Our study extends the literature by examining the incorporation of debt-related performance metrics (DPMs). Using a manually collected dataset, we find that approximately 19% of US publicly traded firms incorporated DPMs in their compensation contracts. The likelihood of including DPMs increases after creditors’ monitoring incentives increase due to credit quality deterioration or debt maturity pressure. We demonstrate shareholders incorporate more non-debt metrics in their incentive programs in response to DPM inclusion. Our study contributes to understanding the agency costs of debt and debt-related factors in executive compensation

Abstract

We find that several non-promoted executives remain in their firm after losing CEO tournament contests and suffering a drastic reduction in their contract’s promotion-based component and a wider pay gap. We show that they use their private information to sell their holdings profitably, against the newly appointed CEOs’ optimistic and noisy buy trades. They do not trade on their private information in their rare purchases and before losing the contest, to maximize their CEO promotion probabilities, consistent with the substitution hypothesis. Those who stand to lose more from missing their promotion respond more negatively to a promotion pass-over and have a higher incentive to exploit their informational advantage in both voluntary and involuntary CEO turnover events. Their loss-averting sell transactions are more profitable than their peers who left the firm and are related to investors’ sentiments, their firm’s subsequent underperformance, board conservatism, industry tournament incentives, and their ability to implement dissimulation strategies to thwart outsiders and market regulators. Using instrumental variable to address the reverse causality concern, we show that this strategy weakens the well-documented positive relationship between tournament incentives and firm performance. Our results hold for various other specifications and robustness checks and highlight new implications of the tournament incentives models, compensation committees, and insider trading regulations.

Abstract

Narcissism is a multifaceted personality trait that profoundly influences individuals' cognition, emotions, and actions. This study investigates the relationship between narcissistic CEOs and their engagement in opportunistic insider trading. Utilizing a quantitative measure of CEOs’ narcissism derived from textual analysis, we find that CEOs with a higher level of narcissism engage in opportunistic insider trading more intensely, thereby supporting the hypothesis of exploitative personal benefit. To mitigate concerns of endogeneity, we employ various rigorous approaches, including matching, instrumental variable, Heckman’s two-step sample selection model, and falsification tests. Through cross-sectional analysis, we find that the impact of CEOs’ narcissism on opportunistic insider trading is more pronounced among CEOs with limited legal knowledge and weaker monitoring pressure. Collectively, our findings highlight narcissism as a significant personality trait that drives CEOs’ opportunistic insider trading behaviors, contributing to a deeper understanding of corporate governance dynamics.

Abstract

We examine the impact of early-life experiences of social violence on CEOs’ risk-taking attitudes, using the social violent events that CEOs experience as a child during the Chinese Cultural Revolution as a natural experiment. The evidence indicates that these CEOs engage in less acquisition activities, consistent with the notion that early violence experience fosters risk-aversion. We adopt multiple approaches to rule out alternative explanations and potential endogeneity, including using an instrument variable, a stringent set of fixed effcets, and falsification tests. Given that our treatment is distinct from the events in prior studies (e.g., natural disaster or economic degression), this study enriches our understanding on the origin of managerial risk-taking incentives.

Abstract

We examine the impact of environmental regulations and firms’ polluting behavior on CEO incentive compensation. Using the application of the National Ambient Air Quality Standards as an exogenous source of variation in regulatory stringency, we find that noncompliance prompts boards to reduce risk-taking incentives by decreasing the convexity of compensation payoffs. Higher regulation intensity and operating risk amplify the decrease in risk-taking incentives, while financially distressed firms exhibit a less pronounced reduction. Existing governance structures including CEO entrenchment, institutional investors, bargaining power, and overconfidence moderate the relationship between regulatory exposure and risk-taking incentives. Our findings highlight the active role of boards in adjusting incentive contracts to align the risk preferences between shareholders and managers in response to environmental regulations.

Abstract

Using granular barcode-level sales data from retail stores, we show that environmental and social ratings are positively related to local sales, especially in countries with more Democratic-leaning and higher-income households. Higher ratings of a firm’s product market rivals negatively affect a firm’s own sales. Controlling for product-year-level heterogeneity, monthly product sales decline after negative firm news on environmental and social issues. Finally, immediately after major natural and environmental disasters, sales in counties located close to the disasters become more sensitive to environmental ratings. Our study provides direct evidence that environmental and social activities affect the revenues of a firm.

Abstract

This paper delves into the primary association between corporate social responsibility (CSR) and hedging strategies. By employing textual analysis of 10-K filings to measure corporate hedging, we demonstrate that firms with higher levels of CSR are more inclined to engage in hedging practices and with greater intensity. We also show that a reduction in cash flow volatility and a decrease in the cost of debt are potential channels through which CSR firms increase hedging. Furthermore, the influence is more pronounced when robust corporate governance mechanisms are in place. Our estimates pass a number of endogeneity tests, including the entropy balancing method and instrumental variables approach that takes into account political and geographic considerations. Results remain robust to alternative measures and dimensions of CSR and hedging.

Abstract

We explore three ways to classify mutual funds as ESG-oriented: by their names, their voting records, and their holdings. ESG-named funds and ESG-voting funds tend to be smaller than non ESG funds, and spread their investment over more individual companies. They never control more than a quarter of aggregate assets under management. Even taking a broad view of judging funds by the ESG scores of their holdings only increases this to about 33% of AUM. Voting in favor of costly shareholder E&S proposals is still rare, and the portfolio additions and deletions of ESGoriented funds do not differ much from those of non-ESG funds. We conclude that it is surprisingly difficult to find evidence of any real impact of the talk about ESG-oriented investing, whether in voting or widespread and binding investment filters.

Abstract

This study investigates the relation between personally tax aggressive executives and corporate regulatory violations across a wide range of areas. We identify personally tax aggressive executives as those who consistently make uncommonly well-timed corporate stock donations, which prior work has shown are the result of insiders exploiting their private information and/or fraudulently backdating gifts to dates with a high stock price. We hypothesize and find evidence that executives with a propensity to “cut corners” on tax laws also make corporate-level decisions leading to more regulatory violations, such as underinvesting in workplace safety and environmental protection measures. We find the link between tax aggressive executives and corporate violations is mitigated in the presence of strong outside monitors and influential stakeholders. Moreover, we find that violations rise (fall) when a tax aggressive executive joins (leaves) the firm, supporting a causal interpretation. Our study contributes to the literature by 1) introducing a novel approach to identifying personally tax aggressive executives that continues to be useful in the post-SOX era, and 2) providing evidence that such executives drive increased regulatory violations in a wide range of areas.

Abstract

We study the effects of a 2016 U.S. Supreme Court decision that made it harder for prosecutors to bring corruption cases against public servants. We argue that this exogenous shock to anticorruption enforcement created a “protection racket”: regulated firms headquartered in high-corruption states increased cash reserves in the years after the decision, presumably to make illicit payments to local politicians. These firms experienced negative abnormal returns near the decision, indicating that reduced anticorruption enforcement decreased firm value. Consistent with the protection hypothesis, regulated firms in high-corruption states became less likely to be penalized by government agencies after the decision.

Abstract

Founder-CEO firms are associated with smaller discretionary accruals, higher return on assets, lower stock return volatility, and lower likelihood of shareholder litigation relative to non-founder CEO firms. Yet, we find that founder-CEO firms are 18% more likely than an average firm to be investigated in secrecy by the enforcement division of the Securities and Exchange Commission (SEC). This finding is robust to two instrumental variable regressions and a stacked difference-indifferences design, which alleviate the endogeneity concerns. Our channel analyses support the conjecture that the SEC’s interest in founder CEOs is primarily due to their idiosyncratic attributes, such as power, overconfidence, and risk-taking, highlighting the screening aspect of the SEC investigation as opposed to its punitive aspect. Further analyses show that founder CEOs’ visibility is positively associated with the likelihood of an SEC investigation against their firms. The SEC’s corporation finance division is also more likely to issue comment letters to founder-CEO firms. Overall, our findings are of potential interest to firms and investors interested in learning about SEC investigation risk, regulators concerned about founder-CEO firms, and academics studying SEC surveillance.

Abstract

Scam startups are on the rise in recent years. However, little is known about the impact of those startups on venture capitals’ (VC) investment activities. In this paper, we first construct a novel dataset of scam startups using the release of news from the Securities and Exchange Commission (SEC) and the U.S. Department of Justice (DOJ). We then investigate how venture capitalists react after they are cheated by scam startups using a difference-in-differences framework. The main finding is that VCs update their beliefs on new startups after the scams outbreak because the bad signals have been released. VCs reduce investments in new startups and the number of deals compared to a control group of VCs that have not been cheated. The effect is mainly driven by a decline in investment in the industries of scam startups. VCs strengthen screening and monitoring process afterwards. We also find that limited partners (LPs) provide less capital to VCs after they financed a scam startup.

Abstract

We find that following the debut of one of their peers on the Forbes 400 list of wealthiest Americans, corporate insiders start trading more aggressively as measured by the profitability, frequency, and size of their trades. The peer effect is long-lived and continues for at least 3 years following the inclusion event. Insiders’ reaction is stronger when the debutant appears higher on the Forbes list and becomes insignificant when the debutant drops out of the list the following year. Peer recognition exhibits stronger effect on corporate insiders when exposed insiders and the Forbes insider share the same ethnicity. Finally, insiders with fewer professional awards and recognitions react more strongly to their peer’s success.

Abstract

The Market Abuse Regulation (MAR)—which took effect in July 2016 in the European Union—prohibits corporate insiders from trading within 30 days prior to earnings announcements. Using country-level heterogeneity in pre-MAR regulation on closed periods to distinguish treated from control observations, we examine the effect of the mandate on corporate insider trading patterns and information asymmetry around earnings announcements. In terms of compliance, we find a statistically significant decrease in the incidence, amount, and profitability of insider trades in the 30 days preceding earnings announcements in treated relative to control countries. In terms of capital market effects, while we find an average decrease in bid-ask spread and illiquidity for treated relative to control countries, there is a significant relative increase during the 30-day window preceding earnings announcements. The latter effect is driven by firms with less transparent information environments. Hence, the evidence suggests that, while mandated closed periods are effective at curtailing corporate insider trading during information-sensitive windows, they do not reduce market-level information asymmetry. Overall, the evidence does not suggest that one-size-fits-all regulation of close periods achieves better capital market outcomes than firm- or country-specific policies.

Abstract

Anecdotal evidence suggests that firms anticipate regulatory actions long before the proposed regulations are finalized. Applying a novel machine-learning algorithm to a new dataset, we provide the first large-sample evidence of substantial anticipatory effects. The granular data set tracks the entire rulemaking activity of all federal agencies since 1995. Out of 41,000 rule proposals, only two-thirds converted into a final rule, and they did so after spending two years on average in the rulemaking pipeline. We track the timeline of each proposed rule, assign proposed rules to firms based on a machine-learning algorithm, and derive a firm-level measure of exposure to the regulatory pipeline: the amount of rule proposals which are relevant to the firm. We find that firm-level exposure to the regulatory pipeline has significant anticipatory effects. Firms with greater exposure express more concerns about future political risk, increase their overhead costs, and see lower profits. To prepare for the anticipated regulatory changes, firms spend more on lobbying, build up cash reserves, and reduce capital investment. The effects are independent of the firm’s current regulatory burden and are driven by rule proposals that are more likely to convert into final rules. Financially constrained and small firms are especially responsive to the regulatory pipeline, which highlights the role of budget constraints and economies of scale. Our results are the first to consistently document anticipatory effects based on the entire body of potential federal regulations

Abstract

We document that firms engage in opportunistic short-term ROA enhancing when they conduct business in an environment with a low probability of detection of financial misconduct. To proxy for a lax monitoring environment, we compute the percentage of local Securities and Exchange Commission (SEC) employees earning the exogenously imposed maximum salary, as these employees lack the monetary incentives to increase their monitoring efforts. We find that the percentage of local SEC employees at the salary cap correlates negatively with the detection rate of financial misconduct, and positively with the attrition rate of SEC employees. We also show that in environments with apparent lax SEC monitoring, firms engage in short-term ROA enhancements, principally by increasing their discretionary accruals, and the magnitude of the effect increases when peers of the focal firms also engage in financial misconduct.

Abstract

Using a hand-collected sample of non-financial firms’ financial portfolios, I examine how asymmetric cost behavior (or cost stickiness) affects risky financial investments. Sticky costs amplify the downward effect of sales decrease on profits because costs do not fall when sales decrease by as much as they rise when sales increase. I find that firms with sticky costs reduce risky financial investments because of expected liquidity needs and the trade-off between operating and financial risk. Oster’s delta, difference-in-differences analysis, and synthetic control method address endogeneity concerns. For non-financial firms with sticky costs, investing in risky securities subdues non-financial investments and increases a firm’s risk exposure without creating shareholder value.

Summary

This paper utilizes a large sample of detailed assets valuation data from M&A transactions to examine the impact of intangible assets on firms’ capital structure decisions. Contrary to conventional wisdom, the findings reveal that intangibles do not result in lower debt usage compared to tangible assets; instead, intangible assets can support debt financing to a comparable extent, with a greater association with cash flow-based rather than asset-based debt. Furthermore, the research highlights the importance of considering heterogeneity among intangibles, presenting a theoretical framework for categorization. A model is developed to elucidate the mechanism underlying the finding that demandshifter intangibles exhibit higher debt capacity than production intangibles.

Abstract

How do firms respond to changes in recession risk? We study a rich dynamic model with time-varying recession risk and heterogeneous firm size. In recessions, cash flows decrease, cash-flow volatility increases, external financing becomes unavailable, and liquidation costs increase. Recession risk leads to preemptive equity issuances by low-cash firms, investment cuts by intermediate-cash firms, and payout cuts by highcash firms. Interestingly, large firms’ policies and values co-vary more with changes in recession risk because small firms prepare more when recession risk is low. We provide empirical support for these predictions.

Abstract

There is little evidence to show that primary capital markets allocate capital to the most profitable uses. We bridge this gap by examining Indian IPOs. When market regulations are weak, more firms go public and firms with poor fundamentals raise more capital. Over time, primary markets do not necessarily allocate more capital to firms with higher profitability or to those with more growth opportunities. However, the probability of failure declines and the liquidity of IPOs improves. Our results suggest that capital market reforms are not uniformly effective in directing investments to firms with higher investment efficiency.

Abstract

We provide the first systematic evidence of contractual innovation in the terms of poison pill plans. In response to the increase in hedge fund activism, pills have changed to include anti-activist provisions, such as low trigger thresholds and actingin-concert provisions. Using unique data on hedge fund views of SEC filings as a proxy for the threat of activists’ interventions, we show that hedge fund interest predicts pill adoptions. Moreover, the likelihood of a 13D filing declines after firms adopt “antiactivist” pills, suggesting that pills are effective in deterring activists. The results are particularly strong for “NOL” pills that, due to tax laws, have a five percent trigger. Our analysis has implications for understanding the modern dynamics of market discipline of managers in public corporations and evaluating policies that regulate defensive tactics.

Abstract

This paper provides causal evidence of the effects of the M&A market on target firms’ corporate policies. Using antitrust regulatory thresholds to link the probability of a takeover to the size of the firm, we find evidence that firms intentionally reduce their size to elicit a takeover bid. They do so by limiting asset growth and increasing their payouts when they have excess cash. The treatment effect is stronger among firms with greater control over their market value and incentives to cash out via a merger. Our results reveal that antitrust exemptions can create perverse incentives that limit growth.

Abstract

Equity crowdfunding (CF) emerged as a new financing source for entrepreneurs and competes with early-stage financing professionals, e.g., venture capital (VC) investors. Entrepreneurs need to decide from who to raise capital and we develop a theory on this financing choice. We model two financing stages where both types of investors are in competition with each of them having competitive advantages. The respective advantages include transaction cost, return requirements, support quality, the efficiency of transaction monitoring and of abandonment decisions. Our model predicts the preferred choice for the entrepreneur contingent on these parameters, the resulting entrepreneurial effort and expected venture value. The model also suggests increased competition in the early-stage financial market and the necessity for VCs to focus on expertise, to specialize, and to move to later financing stages under certain circumstances.

Abstract

This study provides comparative empirical evidence on the fundraising outcomes and the post-funding performances of ventures supported by either business angels or crowdinvestors. Building on a multiyear original dataset combining repeated annual surveys on both the angel and the equity crowdfunding markets in Italy, we find that ECF-backed ventures raise less capital than BA-backed ones and crowd-investors acquire a smaller percentage of capital than BAs. Moreover, ventures that successfully raised ECF, subsequently, are less likely to raise follow-on equity financing compared to BA-backed companies. As a major contribution of the paper, we document the presence of systematic differences in the investigated backed ventures, in their fundraising outcomes and in their follow-on financing trajectories, supporting the view that crowd-investors and BAs, while apparently addressing the same need in the pre-VC financial ecosystem, act as substitutes: they represent different market screening mechanisms separating companies with unobservable, but intrinsically different characteristics that ultimately affect their future follow-on investment rounds and their growth potential

Abstract

Entrepreneurial ventures benefit substantially from close interactions with their resource environment, but dependence on resource providers can give rise to power imbalances. Prior studies have identified various defense mechanisms by which less powerful ventures reduce the risk of opportunistic behavior by more powerful equity investors. This study extends our understanding of resource dependence in entrepreneurial ventures by studying how and which ventures protect themselves in their first interaction with key equity investors when established defense mechanisms are scarce. Drawing from resource dependence theory, we theorize and show that ventures with higher ex-ante cash levels and prior experience with co-investments involving different investor types protect themselves by simultaneously attracting equity from a diverse set of investors in their first investment round. This strategy significantly facilitates follow-on funding. We extend Resource Dependence Theory by showing how a “Divide and Conquer”-strategy can shield a less powerful actor from opportunistic behavior by powerful resource providers.