Contract design and architecture is an important topic within economics, finance, and law. However, attempts to study it are significantly constrained by the limited availability of public, high quality data. In this paper, we introduce a new corpus of 7929 Definitive Merger Agreements submitted to the SEC between 2000 and 2020 involving a transaction in excess of $100 million. Through a combination of machine learning and human evaluation, we associate these agreements with other metadata, such as deal size, industry classification, and advising law firms. In addition, we identify and make available the text of individual clauses contained in these agreements. In a final step, we provide an illustration of how these data can be used to generate novel insights into M&A contract design and drafting practices.

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This article investigates the reaction to a much-heralded 2022 legal reform in Delaware that permitted a corporation’s charter to exculpate its officers from monetary exposure for breaching their fiduciary duty of care. To isolate reactions to this statutory reform, we make extensive use of generative AI tools to identify and interpret charter amendments that introduce officer-facing waivers. We find a surprisingly tepid rate of uptake among Delaware corporations through the end of the first post-reform year, notwithstanding widespread predictions that corporate entities would quickly storm the exculpation exits once permitted to do so. Our study makes two contributions to the empirical study of law—one methodological and the other substantive. Methodologically, we develop a novel and powerful use case for deploying large language models as a tool for distilling and extracting technical provisions from legal texts (in this case corporate charters), allowing us to accelerate and streamline an endeavor that would have consumed substantial time and resources using traditional human-labeling protocols. Notably, and in a significant departure from previous machine learning tools, ChatGPT accomplishes this set of tasks without the need for training data specifically tailored for this purpose. Perhaps most impressive is the accuracy with which ChatGPT can operate: we perform several validation exercises, which generally indicate that our proposed method yields highly accurate results. Substantively, we demonstrate that Delaware’s statutory invitation attracted few takers in its first year of effectiveness: specifically, we show that only a modest minority of eligible corporations amended their charters to include officer-facing waivers. This tepid rate of uptake, moreover, persists even in corporations that went public after the reform’s effective date, suggesting that transaction costs are unlikely to be the culprit for the listless response. Furthermore, we show that stock market investors also exhibited a muted response to the reform, raising doubts about whether firms feared amendments would trigger an adverse market reception. Our results seem more consistent with alternative explanations, ranging from the plausible irrelevance of Delaware’s reform, to a risk-averse reticence among corporate managers who rationally adopt a “wait and see” approach to gauge how such waivers are received by both courts and corporate stakeholders while keeping their options open.

Post-merger appraisal rights have been the focus of heated controversy within mergers and acquisitions circles in recent years. Traditionally perceived as an arcane and cabalistic proceeding, the appraisal action has recently come to occupy center stage through the ascendancy of appraisal arbitrage —whereby investors purchase target-company shares shortly after an announcement principally to pursue appraisal. Such strategies became more feasible and profitable a decade ago, on the heels of two seemingly technocratic reforms in Delaware: (i) the statutory codification of pre-judgment interest, pegging a presumptive rate at five percent above the federal discount rate; and (ii) the Transkaryotic opinion, which effectively sanctified appraisal claims trading. Several commenta-tors have decried appraisal arbitrage as visiting unnecessary risks and costs on deal certainty and pricing, advancing the position that it reduces / destroys target shareholder value. This paper in-terrogates such claims both theoretically and empirically, testing the predictions of an auction-design model that delivers testable implications about appraisal’s price and welfare implications. We find—consistent with the comparative statics of our model—that the appraisal-liberalizing events of 2007 were associated with a significant increase in deal premia , as the enhanced credibility of appraisal had the effect of raising the de facto “reserve price” associated with M&A auctions. We further find little evidence that liber-alized appraisal rights stifled the incidence of appraisal eligible deals. Moreover, when interpreted through the lens of our auction-design model, our findings suggest that target-company shareholders of all stripes likely benefited ex ante from liberalized appraisal.

Although debt finance and restructuring rarely command headlines, they collectively comprise some of the most heated corporate battles in recent history. The field’s contemporary participants, including private equity sponsors, banks, and distressed debt investors have increasingly become embroiled in cantankerous conflicts over the division of assets and cash flows of distressed firms. Many of those battles resemble multiplayer chess matches, with parties scouring debt contracts for loopholes and landmines that either enrich themselves or undercut their rivals. The costs of these battles have grown precipitously, even as their outcomes have become less predictable—resulting in undesirable consequences for borrowers, lenders, intermediaries, stakeholders, and the economy at large. In this paper, we advance the thesis that much of our ongoing corporate credit conundrum has been aided and abetted by an unlikely co-conspirator: contract law. In particular, we highlight and document courts’ progression over fifty years towards a sweeping embrace of textualism to interpret credit agreements, and their concomitant rejection of other interpretive schema. Whatever its merits might have been a half century ago, “debt textualism” has catalyzed and fueled an onslaught of inter-creditor warfare, rendering its continued justification questionable. We propose several prescriptions for addressing the current state of play, ranging from doctrinal reform, to legislative/regulatory intervention, to private contractual innovation. If such measures prove unable to dislodge debt textualism from its entrenched perch, however, we also suggest strategies for marshaling it for the greater good, spotlighting the role that debt textualism might play in securing more credible corporate commitments on decarbonization and climate change.

In a noteworthy recent paper, Mitts (2020) presents empirical evidence that published attacks on publicly-traded companies by certain presumed short-sellers generate “V”-shaped pricing patterns, whereby targeted companies’ stock prices fall precipitously when a negative report is published, but later substantially rebound. Mitts associates these dynamics with manipulative practices by the reports’ authors and their confederates. In a recent response, Block (2022) criticizes Mitts (2020) on several fronts (both academic and otherwise), taking particular issue with the fact that the “V” emerges out of a data restriction imposed by Mitts (2020), whereby issuers with less than $2 billion in market capitalization were excluded from the baseline analysis. When one introduces smaller size cutoffs, the empirical effect dissipates. This note develops a theoretical model to study the valuation of financial assets in the presence of short sellers who may issue false reports about targeted companies, as well as targeted companies who may choose to fight back. I derive equilibria of the model, and show that (a) “V”-shaped pricing paths for targeted firms can (and do) emerge along the equilibrium path; (b) when they emerge, such paths are symptomatic of an inaccurate report; (c) “V”-shaped paths are always part of a unique equilibrium for “large” firms; and (d) “V”-shaped paths are never part of a unique equilibrium for “small” firms. Jointly, these results provide theoretical support and a helpful interpretive lens for Mitts (2020)’s data restriction and findings. At the same time, the model also predicts that “V”-shaped patterns for wrongly-attacked firms would be difficult to discern from aggregated market data that was generated via equilibrium play. Consequently, additional research is needed to assess whether the sub-groups analyzed by Mitts (2020) constitute a sufficiently diagnostic screen to pinpoint manipulative practices.

In this discussion, corporate governance legend Ira M. Millstein reflects on the impact of Milton Friedman and his adherents on our corporate governance system and economy generally, as well as the path forward to an economy that functions better for the many. Millstein takes an historical perspective in conversation with former Chief Justice and Chancellor of Delaware, Leo E. Strine, Jr., moderated by Professor Eric Talley of Columbia Law School. Millstein situates the evolution of our corporate governance system, including the effect of Friedman and the Chicago school on it, within the political dynamics of the last fifty years since the New York Times published the essay, “A Friedman Doctrine—The Social Responsibility Of Business Is to Increase Its Profits.”

Although empirical scholarship dominates the field of law and finance, much of it shares a common vulnerability: an abiding faith in the accuracy and integrity of a small, specialized collection of corporate governance data. In this paper, we unveil a novel collection of three decades’ worth of corporate charters for thousands of public companies, which shows that this faith is misplaced. We make three principal contributions to the literature. First, we label our corpus for a variety of firm- and state-level governance features. Doing so reveals significant infirmities within the most well-known corporate governance datasets, including an error rate exceeding eighty percent in the G-Index, the most widely used proxy for “good governance” in law and finance. Correcting these errors substantially weakens one of the most well-known results in law and finance, which associates good governance with higher investment returns. Second, we make our corpus freely available to others, in hope of providing a long-overdue resource for traditional scholars as well as those exploring new frontiers in corporate governance, ranging from machine learning to stakeholder governance to the effects of common ownership. Third, and more broadly, our analysis exposes twin cautionary tales about the critical role of lawyers in empirical research, and the dubious practice of throttling public access to public records.

Despite its massive size, the corporate debt market is often considered a sleepy refuge for the risk-averse. Yet, corporate debt contracts are often mind-numbingly detailed. That complexity—when coupled with the financial stakes in play—can be a recipe for calamity. And in late 2020, calamity struck in the form of an accidental $1 billion payoff sent to Revlon Inc.’s distressed creditors—not by Revlon itself but rather by Citibank, the administrative agent for the loan. When several lenders refused to return the cash, Citibank commenced what many reckoned would be a successful (if embarrassing) lawsuit to claw it back. But in a dramatic 2021 opinion, a New York federal court sided with the creditors, applying an obscure equitable doctrine known as the “Discharge for Value” defense. The lenders could keep their wayward windfall, and Citibank got stuck with a sizeable write-down. Regardless of how it comes out on appeal, the case seems destined to feature prominently in contracts classes and textbooks for years to come. Against this backdrop, this Article makes three contributions: First, it spotlights several doctrinal and logical irregularities in the District Court’s opinion. Second, it builds on these inconsistencies to critique the opinion from an economic policy perspective. Third (and most substantially), it presents novel empirical data to analyze how market participants have reacted to the opinion. Consistent with the policy critique, I document a rapid, precipitous trend towards writing and/or amending debt contracts to nullify the Citibank opinion in its entirety, manifested in a variety of “Revlon blocker” provisions that have appeared in hundreds of publicly disclosed contracts. The firms that adopt Revlon blockers are systematically the largest and most sophisticated companies in the public markets, and their rejection of Citibank appears to have met with general market approval. Beyond demonstrating how legal theory and empirical evidence can helpfully interact, this analysis underscores the critical role that default rules play in contract law and policy, and the high stakes involved in getting them right.

Conventional wisdom portrays contracts as static distillations of parties’ shared intent at some discrete point in time. In reality, however, contract terms evolve in response to their environments, including new laws, legal interpretations, and economic shocks. While several legal scholars have offered stylized accounts of this evolutionary process, we still lack a coherent, general theory that broadly captures the dynamics of real-world contracting practice. This paper advances such a theory, in which the evolution of contract terms is a byproduct of several key features, including efficiency concerns, information, and sequential learning by attorneys who negotiate several deals over time. Each of these factors contributes to the underlying evolutionary process, and their relative prominence bears directly on the speed, direction, and desirability of how contractual innovations diffuse. Using a formal model of bargaining in a sequence of similar transactions, we demonstrate how different evolutionary patterns can manifest over time, in both desirable and undesirable directions. We then take these insights to real-world dataset of over 2,000 merger agreements negotiated over the last two decades, tracking the adoption of several contractual clauses, including pandemic-related terms, #MeToo provisions, CFIUS conditions, and reverse termination fees. Our analysis suggests that there is not a “one size fits all” paradigm for contractual evolution; rather, the constituent forces affecting term evolution appear manifest in varying strengths across differing circumstances. We highlight several constructive applications of our framework, including the study of contract negotiation unfolds when price cannot easily be adjusted, and how to incorporate other forms of cognitive and behavioral biases into our general framework.

The ongoing COVID-19 pandemic has led to acute supply shortages across the country as well as concerns over price increases amid surging demand. In the process, it has reawakened a debate about whether and how to regulate “price gouging.” Animating this controversy is a longstanding conflict between laissez-faire economics (which champions price fluctuations as a means to allocate scarce goods) and perceived norms of consumer fairness (which are thought to cut strongly against sharp price hikes amid shortages). This article provides a new, empirically grounded perspective on the price gouging debate that challenges several aspects of conventional wisdom. We report results from a survey experiment administered to a large, nationally representative sample during the height of the pandemic’s initial wave. We presented participants with a variety of vignettes involving price increases, eliciting their reactions along two dimensions: the degree of unfairness they perceived, and the legal response they favored. Overall, we find that participants are more tolerant of price increases than either the existing behavioral economics literature predicts or most state price gouging statutes countenance. But we also find that price fairness perceptions can be highly sensitive to context. For example, participants are much more tolerant of moderate price increases if they previously are asked to contemplate large price increases. Moreover, participants are substantially more willing to accept a price increase when it is accompanied by an apology and/or a public-minded rationale (such as supporting furloughed employees). We explore the implications of our findings for behavioral economics, pricing practices, and legal reform.

This Article is the first to use computational methods to investigate the ideological and partisan structure of constitutional discourse outside the courts. We apply a range of machine-learning and text-analysis techniques to a newly available data set comprising all remarks made on the U.S. House and Senate floors from 1873 to 2016, as well as a collection of more recent newspaper editorials. Among other findings, we demonstrate: (1) that constitutional discourse has grown increasingly polarized over the past four decades; (2) that polarization has grown faster in constitutional discourse than in nonconstitutional discourse; (3) that conservative-leaning speakers have driven this trend; (4) that members of Congress whose political party does not control the presidency or their own chamber are significantly more likely to invoke the Constitution in some, but not all, contexts; and (5) that contemporary conservative legislators have developed an especially coherent constitutional vocabulary, with which they have come to “own” not only terms associated with the document’s original meaning but also terms associated with textual provisions such as the First Amendment. Above and beyond these concrete contributions, this Article demonstrates the potential for computational methods to advance the study of constitutional history, politics, and culture.

Autonomous vehicles (AVs) are inevitably entering our lives with potential benefits for improved traffic safety, mobility, and accessibility. However, AVs' benefits also introduce a serious potential challenge, in the form of complex interactions with human-driven vehicles (HVs). The emergence of AVs introduces uncertainty in the behavior of human actors and in the impact of the AV manufacturer on autonomous driving design. This paper thus aims to investigate how AVs affect road safety and to design socially optimal liability rules in comparative negligence for AVs and human drivers. A unified game is developed, including a Nash game between human drivers, a Stackelberg game between the AV manufacturer and HVs, and a Stackelberg game between the lawmaker and other users. We also establish the existence and uniqueness of the equilibrium of the game. The game is then simulated with numerical examples to investigate the emergence of human drivers' moral hazard, the AV manufacturer's role in traffic safety, and the lawmaker's role in liability design. Our findings demonstrate that human drivers could develop moral hazard if they perceive their road environment has become safer and an optimal liability rule design is crucial to improve social welfare with advanced transportation technologies. More generally, the game-theoretic model developed in this paper provides an analytical tool to assist policy-makers in AV policymaking and hopefully mitigate uncertainty in the existing regulation landscape about AV technologies.

We develop a model of venture capital contracting and use it to evaluate an emergent set of judicial precedents in corporate law, which we label the Trados doctrine. In our model, founders hold common stock, while venture capital investors hold convertible preferred stock. We show that preferred shareholders have inefficient incentives to liquidate low-valued firms and to continue high-valued firms, while common shareholders inefficiently favor the opposite. The extent of incentive misalignment depends on the firm's intrinsic and outside valuations, and it is most severe around preferred shareholders' liquidation preference and conversion point. Although legal liability rules can rectify these misalignments, they can only do so categorically when management prioritizes preferred shareholders' interests. The Trados doctrine, however, generally obligates management to prioritize common shareholders' interests. Our model offers a precise mechanism for how capital structure, corporate governance, and legal doctrine jointly determine firms' value.

Changes in the global climate are having profound impacts on business operations, governance, and organizational management around the world. Boards of directors are searching for ways to account for these changes as they help guide their organizations, and investors are increasingly concerned about how these changes might impact their portfolios. This global survey, conducted by a team of researchers at the Ira M. Millstein Center for Global Markets and Corporate Ownership at Columbia Law School and experts at LeaderXXchange, seeks to understand how — if at all — institutional investors and board directors incorporate climate-related issues in their investment decision making and their oversight responsibilities, respectively. It is among the first global survey of its kind targeting both investors and directors to probe their responses on climate risk management using two tracks aggregated in a single survey. The survey collected data on a broad range of topics, including demographic information of respondents and their views on issues such as materiality of climate change, training on climate change issues, disclosure of climate risks, climate risk management, board oversight and engagement and proxy voting on climate-related issues. We find a strong majority of respondents across groups rank climate issues high up on their list of important considerations. That said, climate issues appear to attract stronger attention among investors (as opposed to directors), women, younger respondents, and European respondents.

This paper surveys the use of pandemic-related provisions in Material Adverse Effects ("MAE") provisions in a large data set of publicly disclosed MA but when an RTF is present, its magnitude tends to be smaller in the absence of any pandemic-specific carve-out, suggesting some degree of observational complementarity between these terms.

An emerging consensus in certain legal, business, and scholarly communities maintains that corporate managers are pressured unduly into chasing short-term gains at the expense of superior long-term prospects. The forces inducing manage- rial myopia are easy to spot, typically embodied by activist hedge funds and Wall Street gadflies with outsized appetites for current quarterly earnings. Warnings about the dangers of “short termism” have become so well established, in fact, that they are now driving changes to mainstream practice as courts, regulators and practitioners fashion legal and transactional constraints designed to insulate firms and managers from the influence of investor short-termism. This Article draws on ac- ademic research and a series of case studies to advance the the- sis that the emergent folk wisdom about short-termism is in- complete. A growing literature in behavioral finance and psychology now provides sound reasons to conclude that corpo- rate managers often fall prey to long-term bias—excessive op- timism about their own long-term projects. We illustrate sev- eral plausible instantiations of such biases using case studies from three prominent companies where managers have argua- bly succumbed to a form of “long-termism” in their own corpo- rate stewardship. Unchecked, long-termism can impose sub- stantial costs on investors that are every bit as damaging as short-termism. Moreover, we argue that long-term managerial bias sheds considerable light on the paradox of why short- termism evidently persists among supposedly sophisticated fi- nancial market participants: shareholder activism—even if unambiguously myopic—can provide a symbiotic counter-bal- last against managerial long-termism. Without a more defini- tive understanding of the interaction between short- and long- term biases, then, policymakers should be cautious about em- bracing reforms that focus solely on half of the problem.

A significant debate within mergers and acquisitions law concerns the explosive popularity of the “merger objection lawsuit” (MOL), a shareholder action seeking to enjoin an announced deal on fiduciary duty grounds. MOLs blossomed during the Financial Crisis, becoming popularly associated with “shareholder shakedowns,” whereby quick-triggered plaintiff attorneys would file against — and then rapidly settle with — acquirers, typically on non-monetary terms containing modest added disclosures in exchange for blanket class releases and attorney fee awards. This practice unleashed a torrent of criticism from lawyers, commentators, academics, and (ultimately) judges, culminating in a doctrinal shift in Delaware law in the January 2016 Trulia opinion, which virtually prohibited disclosure-only settlements. This paper investigates the implications of this doctrinal shock from a shareholder welfare perspective. We argue that — notwithstanding the intuitive appeal of prohibiting / discouraging disclosure settlements — it is far from clear whether doing so helps or hurts target shareholders ex ante, since the threat of MOLs interacts with other intra-corporate agency costs (such as those of managers and buyers negotiating deals). Reducing the credibility of a litigation threat may deter shakedowns at the cost of reduced deal premia and shareholder value — consequences inconsistent with conventional commitments of corporate law. We develop a theoretical model of company acquisitions formally demonstrating that the competing equilibrium effects of Trulia are indeterminate, an insight that hoists a flag of caution regarding the doctrinal innovation. Moreover, our model delivers testable implications related to Trulia, which we investigate empirically. Our empirical analysis suggest that the recent doctrinal shock does not appear to have resulted in a discernible increase to target shareholder welfare.