Archive for the ‘ Dynamic Regulation ’ Category

Innovation and Legislation: The Changing Relationship – Evidence from 1984 to 2015


Wulf A. Kaal

University of St. Thomas, Minnesota – School of Law

Nick Farris

University of St. Thomas – School of Law (Minnesota)

Date Written: November 29, 2017


We examine the relationship between innovation as measured by annual utility patents granted and two datasets for legislation: (1) the U.S. Code and (2) the Code of Federal Regulations from 1984 to 2015. We show that the historical relationship between innovation and legislation has changed, especially for computer and communication patents. The evidence suggests that the existing regulatory infrastructure has a diminishing capacity to react to innovation. The evolving empirical relationship between innovation and legislation has implications for the legal system and rulemaking processes in the existing regulatory framework.

Keywords: Innovation, Measures of Innovation, Legislation, Measures of Legislation, CFR, U.S. Code, Patents, Data, Matching

JEL Classification: K20, K23, K32, L43, L5, O31, O32

Kaal , Wulf A. and Farris, Nick, Innovation and Legislation: The Changing Relationship – Evidence from 1984 to 2015 (November 29, 2017). Available at SSRN:

Blockchain Technology for Horizontal Agriculture Innovation 

Delighted to participate in the first Davos on the Delta Conference organized by ISelect Fund’s Carter Williams. Fantastic event in Memphis TN – the Silicone Valley for #Agriculture #Entrepreneurship #Innovation. All leading player in the agriculture business and leading AG startups in various financing stages are present and it is extremely energizing to talk about AG innovation. Most interesting – how can we create trust through technology between different AG players, farmers, among other participants to created healthier and more sustainable food for society and transition from vertical to more horizontal integration ? Answer: #Blockchain #ML #bigdata #platform #Business. 

Dynamic Regulation Via Contingent Capital

Dynamic Regulation Via Contingent Capital

16 Pages Posted:

Wulf A. Kaal

University of St. Thomas, Minnesota – School of Law

Date Written: April 24, 2017


Contingent capital securities are a largely overlooked dynamic regulatory mechanism. This essay evaluates the use of contingent capital securities in a dynamic regulatory context, including the use of feedback effects for optimized timing and information for regulation and anticipatory regulation.

Keywords: Dynamic Regulation, Contingent Capital, CoCos, Feedback Effects, Optimized Information for Regulation, Anticipatory Regulation

JEL Classification: K20, K23, K32, L43, L5, O31, O32

Kaal , Wulf A., Dynamic Regulation Via Contingent Capital (April 24, 2017). Review of Banking and Financial Law, Vol. 36, 2017. Available at SSRN:

Blockchain Solutions for Agency Problems in Corporate Governance


Blockchain technology allows for decentralized networked governance that allows for the removal of internal and external monitoring mechanisms previously necessitated by agency problems in corporate governance. Blockchain technology creates formal immutable guarantees in agency relationships that build the trust needed to overcome the agency problems in corporate governance. It facilitates a substantial increase in efficiency in the agency relationship and lowers agency costs in orders of magnitude.
(An extended and fully cited version of this article is forthcoming)


Agency theory (Jensen and Meckling (1976)) is still today the leading theory for governance conflicts between shareholders, corporate managers, and debt holders. A vast literature attempts to explain the nature of the agency conflicts in corporate governance and possible ways to resolve such conflicts. However, the core agency conflicts emanating from the separation of ownership (shareholder principal) and control (manager agent) cannot be fully addressed by the existing theoretical and legal framework. Attempts to monitor agents is inevitably costly and transaction costs abound. The literature has overlooked the unprecedented efficient solutions offered by blockchain technology for agency problems in corporate governance.

Agency Problems

Agency problems originate from the lacking trust between principals and agents. The agency relationship can be defined as a contract between principal and agent whereby the agent acts on principals’ behalf because principal delegated a modicum of decision-making authority to the agent (Jensen and Meckling (1976)). Because of the delegated authority, the agents’ decisions affect both the agents’ welfare and the principals’ welfare. The agency model at its very basic level suggests that information asymmetries between the principal and the agent and agents’ opportunistic behavior resulting from self interest leads to principals’ lacking trust in agents. Because of bounded rationality, incomplete foresight, and information asymmetries between principal and agent, it is impossible for principals to contract for every possible action or inaction of the agent in order to induce the agent to act in the best interests of the principal (Brennan (1995)).

Agency Costs

Agency costs arise because the principal attempts to control, monitor, and supervise the agent. As a result of lacking trust in the integrity of the principal agent relationship, and in an attempt to minimize information asymmetries, principals are forced to put into place costly mechanisms to align their interest with those of the agents. Most prominently, such control mechanism involve periodic reporting, compensation structures for agents, bonding, among others. In the corporate context, agency costs can be seen as the lost value to shareholders (loss in corporation’s share price) that results from diverging interests between shareholders (principal) and corporate managers (agents). As such, agency costs is the sum of monitoring costs, bonding costs, and residual loss (Jensen and Meckling (1976)).

Monitoring costs are costs to the principal resulting from observing, measuring, and controlling an agent’s behavior. Monitoring costs can include the cost of audits, executing executive compensation contracts, and cost of hiring/firing manager agents. While such monitoring costs are generally paid by the principal, agents may be responsible for such costs as well because agents’ compensation is subject to adjustments to cover monitoring costs (Fama and Jensen (1983)).

Bonding costs are the cost of establishing and adhering to system structures that allow agents to act in shareholder principal’s best interests or compensate shareholder principals appropriately if agents do not act in their best interest. While bonding costs are typically paid by the agents, they may in addition to financial costs include the cost of increased disclosures to shareholder principals. If the marginal reduction in monitoring equals the marginal increase in bonding costs, agents no longer incur bonding costs.


The agency relationship in modern finance and corporate governance is characterized by attempts to optimize incentives between principals and agents, control costs, minimize information asymmetries, control adverse selection and moral hazard, optimize risk preferences between principals and agents, and engage in monitoring.

Agency Problems in Corporate Governance


The lacking trust in the agent’s performance of her duties creates the underlying problems in corporate governance. Despite best efforts at monitoring and bonding, the interest of manager agents and shareholder principals in corporate governance are never fully aligned and agency losses inevitably arise from conflicts of interest between principals and agents, known as residual loss. Residual loss arises because the cost of enforcing suboptimal contracts between principals and agents always exceed the benefits of performing the contractual obligations.

Existing Governance Mechanisms

Existing governance mechanism sub-optimally address the agency problems in corporate governance. To name only a few of many approaches that are beyond this short illustration, a standard approach much touted by the literature for effective corporate governance involved outside independent directors on corporate boards. Another prominent example involves firms’ capital structures with emphasis on higher debt levels. While these and many other attempts at optimizing corporate governance and addressing the agency problems in corporate governance helped optimize the agency problems, many examples suggest that the core underlying agency problems cannot fully be resolved within the existing theoretical and legal infrastructure.

A standard approach for effective corporate governance involved outside independent directors on corporate boards who hold managerial positions in other companies, thus separating the problems of decision management and decision control (Fama and Jensen (1983)). However, CEOs who often dominate the board make the separation of these functions much more difficult, which hurts shareholders. Furthermore, outside directors’ separation of decision management and decision control depends on their concern over reputation as an incentive, which is insufficient in most cases.

Another much touted governance mechanism for firms involved firms’ capital structures with emphasis on higher debt levels. Higher levels of insider ownership by increasing debt and reducing equity (Jensen and Meckling (1976)) in the firm’s capital structure acts as a bonding mechanism for manager agents (Jensen (1986)). Management by issuing debt rather than paying dividends creates contractual obligations to pay out future cash flows in ways unattainable through dividends. Debt financing can also help create external capital market monitoring which incentivizes managers’ avoidance of personal utility maximization and increases value maximizing strategies for shareholders (Easterbrook (1984)).

Despite the unresolved substantive problems associated with the division of ownership (shareholders) and control (agent), the corporate form with the diffused share ownership that leads to such conflicts, and the incomplete and suboptimal rules that govern such conflicts, remains the most popular form of a governance mechanism. The popularity of existing mechanisms to address the agency problems in corporate governance may be related to path dependencies created by the evolution of internal and external monitoring mechanisms in corporate governance and the evolution of governance mechanisms designed to limit the scope of agency problems, instituted to address the agency problems in corporate governance.

Existing universal governance solutions are often ineffective because agency conflicts and the specific scope of agency conflicts differ across firms. Governance mechanisms and the effectiveness of governance mechanisms in reducing agency conflicts in firms differ from firm to firm. Each type of governance mechanism and combinations of governance mechanisms can help reduce aspects of agency costs associated with the separation of ownership (principal shareholder) and control (manager agent). However, existing governance mechanisms work well in some firms but are ineffective in others. The literature today is still lacking a comprehensive understanding of workable governance mechanisms and solutions across a broad spectrum of firms.

Blockchain Solutions for Agency Problems in Corporate Governance


Blockchain offers unprecedented solutions for agency problems in corporate governance. Supervisory tasks that were traditionally performed by principals to control their agents can now be delegated to decentralized computer networks that are highly reliable, secure, immutable, and independent of fallible human input and discretionary human goodwill. Blockchain technology provides an alternative governance mechanism that eliminates agency costs – the principal’s cost of supervising agents – by creating trust in the contractual relationship between the principal and the agent.

Blockchain Technology

A blockchain is a shared digital ledger or database that maintains a continuously growing list of transactions among participating parties regarding digital assets – together described as “blocks.” The linear and chronological order of transactions in a chain will be extended with another transaction link that is added to the block once such additional transactions is validated, verified and completed. The chain of transactions is distributed to a limitless number of participants, so called nodes, around the world in a public or private peer-to-peer network. The central elements of blockchain technology include: transaction ledger, electronic, decentralized, networked, immutable, cryptographic verification, among several others. Vitalik Buterin, the founder of Ethereum perhaps most prominently defined blockchain as follows:

“Public blockchains: a public blockchain is a blockchain that anyone in the world can read, anyone in the world can send transactions to and expect to see them included if they are valid, and anyone in the world can participate in the consensus process – the process for determining what blocks get added to the chain and what the current state is. As a substitute for centralized or quasi-centralized trust, public blockchains are secured by cryptoeconomics – the combination of economic incentives and cryptographic verification using mechanisms such as proof of work or proof of stake, following a general principle that the degree to which someone can have an influence in the consensus process is proportional to the quantity of economic resources that they can bring to bear. These blockchains are generally considered to be “fully decentralized”.”

Smart contracts and smart property are blockchain enabled computer protocols that verify, facilitate, monitor, and enforce the negotiation and performance of a contract. The term “smart contract” was first introduced by Nick Szabo, a computer scientist and legal theorist, in 1994. An often-cited example for smart contracts is the purchase of music through Apple’s iTunes platform. A computer code ensures that the “purchaser” can only listen to the music file on a limited number of Apple devices.

More complex smart contract arrangements in which several parties are involved require a verifiable and unhackable system provided by blockchain technology. Through blockchain technology, smart contracting often makes contractual legal contracting unnecessary as smart contracts often emulate the logic of legal contract clauses. Ethereum, the leading platform for smart contracting, describes smart contracting in this context as follows:

”Ethereum is a decentralized platform that runs smart contracts: applications that run exactly as programmed without any possibility of downtime, censorship, fraud or third party interference. These apps run on a custom built blockchain, an enormously powerful shared global infrastructure that can move value around and represent the ownership of property. This enables developers to create markets, store registries of debts or promises, move funds in accordance with instructions given long in the past (like a will or a futures contract) and many other things that have not been invented yet, all without a middle man or counterparty risk.”

Blockchain Guarantees Create Trust in the Agency Relationship

Blockchain technology creates a platform for trust through truth and transparency for parties. Because the blockchain (at the least the public blockchain) is in fact public and immutable, the technology increases transparency, while at the same time significantly reducing transaction costs.

Blockchain technology provides formal guarantees to participating principals and agents that address agency problems in corporate governance comprehensively. Because of the blockchain guarantees, the technology allows a qualitatively different solution for agency problems in corporate governance, especially if compared with the existing finance infrastructure that is riddled with agency problems (see credit rating, executive compensation etc).

The immutability of the blockchain and its cryptographic security systems provide transactional guarantees and create trust between principals and agents in the integrity of their contractual relationship. Such guarantees ensure no participant can circumvent the rules embedded in blockchain code. Blockchain guarantees include contract execution between principal and agent only if and when all contract parameters were fulfilled by both parties and verified by a majority of miners/nodes in the system. Hence, in the blockchain infrastructure, there is no need for the principal to institute oversight and monitoring with the associated agency costs. Because of the governance guarantees embedded in code, blockchain addresses the inherent agency problems in modern finance and corporate governance comprehensively.

Blockchain technology secures the integrity of principal agent relationships by removing fraudulent transactions. Compared with existing methods of verifying and validating transactions by third party intermediaries (banking, lending, clearing etc.), blockchain’s security measures make blockchain validation technologies more transparent, faster, and less prone to error and corruption. While blockchain’s use of digital signatures helps establish the identity and authenticity of the parties involved in the transaction, it is the completely decentralized network connectivity via the Internet that allows the most protection against fraud. Network connectivity allows multiple copies of the blockchain to be available to all participants across the distributed network. The decentralized fully distributed nature of the blockchain makes it practically near impossible to reverse, alter, or erase information in the blockchain. Blockchains’ distributed consensus model, e.g. the network “nodes” verify and validate chain transactions before transaction execution, makes it extremely rare for a fraudulent transaction to be recorded in the blockchain. Blockchain’s distributed consensus model allows node verification of transactions without comprising the privacy of the parties. Blockchain transactions are therefore arguably safer than a traditional transaction model that requires third-party intermediary validation of transactions. Blockchain technology is also substantively faster than traditional third-party intermediary validation of transactions.

Cryptographic hashes used in blockchain technology further increase blockchain security and removes trust barriers in agency relationships that require monitoring of agents and create agency costs. Cryptographic hashes are complex algorithms that use details of the existing entirety of transactions of the existing blockchain before the next block is added to generate a unique hash value. That hash value ensures the authenticity of each transaction before it is added to the block. The smallest change to the blockchain, even a single digit/value, results in a different hash value. A different hash value in turn makes any form of manipulation immediately detectable. As such, hash cryptology provides another level of guarantee in a agency relationship executed through blockchain technology.

Smart contracts enabled by blockchain technology allow for the comprehensive, error free, and zero transaction/agency cost coordination of agency relationships. Smart contracts and smart property are blockchain enabled computer protocols that facilitate, verify, monitor, and enforce the negotiation and performance of a contract between principal and agent. Agency relationships in smart contracts run exactly as coded without any possibility of opportunistic behavior of the agent. Information asymmetries between principal and agent, censorship, opportunism of agents, breaches of fiduciary duties, liability rules for principals and agents, fraud or third party interference are removed entirely. All contractual terms are public and fully transparent. Accordingly, a company’s finances, for instance, are visible on the blockchain to anyone, not just to the company’s accounting department. Smart agency contracts run on a custom built blockchain, that enables principals and agents to store registries of debts or promises, create entire markets, among many other aspects that have not yet been considered.

Agency related governance in the blockchain takes place without intermediaries, counterparty risk, and principal’s control mechanisms. Blockchain technology simply does not require the layers of control and verification that prior financial systems necessitated. Control mechanisms such as regular management (agent) meetings with shareholders (e.g. at the AGM etc.), financial disclosures, management agent scrutiny through analyst reports and financial press, pressure on management from stock market performance, hedge fund investors, and other institutional and private investors, are no longer part of the blockchain enabled agency relationship in corporate governance.

Blockchain technology facilitates a substantial increase in the efficiency of agency relationships in orders of magnitude and lowers agency costs equally substantial in orders of magnitude. The removal of checks and balances in corporate governance, monitoring of agents, audit requirements, disclosure regimes, market pressure, executive agent compensation schemes, among many others, provides a qualitative shift in efficiency in the agency relationship and in corporate governance overall.


Self-validating blockchain transactions can help resolve the agency issues between most of the stakeholders and constituents of modern corporations. In addition to addressing the traditional agency problem in corporate governance between shareholder principals and manager agents, blockchain enabled smart contracting allows for the public and fully transparent, secure, and completely networked exchange between the corporation and customers, owners and investors, other stakeholders, staff, regulators, strategic partners, suppliers and service providers.

Blockchain Removes Agents

Blockchain technology can facilitate the removal of agents as intermediaries in corporate governance through code, peer-to-peer connectivity, crowds, and collaboration. While it is still difficult to imagine a world without governance structures facilitated by agency constructs, Decentralized Autonomous Organizations (DAOs) have started to challenge the core believe that governance necessitates agency.

The first DAO, launched in May 2016, in the founders’ attempt to set up a corporate-type organization without using a conventional corporate structure, had a governance structure that was entirely built on software, code, and smart contracts that ran on the public decentralized blockchain platform Ethereum. Because if was pure computer code it had no physical address, no jurisdiction that could claim jurisdiction/control over it, and it was not an organization with a traditional hierarchy as we know it from traditional corporate structures. The DAO did not use a traditional corporate structure that necessitated formal authority and empowerment flowing top down from investors/shareholders through a board of directors to management and eventually staff. Indeed, it had no directors, managers or employees. In essence, all the core control mechanisms typically employed by principals in agency relationships were entirely removed in the DAO.

While the first DAO was subject to many limitations and ended in quite some controversy, future DAOs may be less prone to problems. Fundamental flaws in the DAO code enabled hackers to transfer one third of the total funds to a subsidiary account. This hack in combination with additional technological limitations brought down the first DAO initiative. Yet, future DAOs are already created and DAO enthusiasts never stopped testing it. A new DAO is currently being developed that is not set up as a Venture Capital Fund but rather as a donation DAO where participants donate and don’t expect returns. DAO enthusiasts and the DAO community in general are constantly improving the DAO and it seems possible that future DAOs may improve agency problems in corporate governance much more thoroughly than is currently fathomable.


Brennan, M.J. (1995), ‘Corporate Finance Over the Past 25 Years’, Financial Management 24, 9-22.

Fama, E.F. and M.C. Jensen. (1983), ‘Separation of Ownership and Control’, Journal of Law and Economics 88 (2), 301-325.

Easterbrook, F.H. (1984), ‘Two Agency Cost Explanations of Dividends’, American Economic Review 74 (4), 650-659.

Jensen, M.C. and W.H. Meckling. (1976), ‘Theory of the Firm: Managerial Behaviour, Agency Costs and Ownership Structure’, Journal of Financial Economics 3 (4), 305-360.

Jensen, M.C. (1986), ‘Agency Costs of Free Cash Flow, Corporate Finance and Takeovers’, American Economic Review 76 (2), 323-329.

Dynamic Regulation Via Investment Data as a Remedy for Law’s Diminishing Capacity to React to Innovation

First published at:’s-diminishing-capacity

Key words: Disruptive Innovation, Venture Capital, Venture Investments, Dynamic Regulation, Feedback Effects, Optimized Information for Regulation, Anticipatory Regulation, Big Data

In a series of recent papers – ‘Dynamic Regulation for Innovation’, ‘Regulation Tomorrow: What Happens When Technology Is Faster Than the Law?’, and ‘How to Regulate Disruptive Innovation – From Facts to Data’ – I evaluate the diminishing relationship between regulation and innovation. The so-called ‘pacing problem’ between innovation and regulation suggests that innovation driven by science and technology is accelerating, yet, simultaneously, federal and state agencies’ regulatory processes have slowed down.

Several factors contribute to this pacing problem. Some consensus exists that the legal and evidentiary burdens placed on regulatory authorities have increased substantially over time, precipitating the remarkable slowdown in rulemaking by regulatory agencies. The growing divergence between the time cycles of technological innovation and the time cycles of governments around the world contributes significantly to the pacing problem. Systemic factors such as the political and ideological structures in the rulemaking process, the political gridlock in a two-party system that impedes the passing of legislation, legislators’ disagreement on how outdated statutes should be updated, and the need for crises to precipitate legislative action also help to explain the pacing problem.


The existing regulatory infrastructure contributes significantly to this problem. In the existing regulatory framework, the regulatory challenges presented by disruptive innovation are largely associated with facts-based, ex-post, trial-and-error rule-making, with stable and presumptively optimal rules. In essence, some evidence exists that governments mostly regulate to react ex-post, after problems arose in the existing regulatory framework but rules are always assumed to be optimal even though optimality is unattainable in a rapidly innovating and increasingly complex world. Other regulatory challenges are presented by the slow speed of regulation, and ever-increasing unknown future contingencies in rulemaking. Because facts-based, ex-post, trial-and-error rule-making cannot anticipate regulatory issues created by innovation, rule-makers may not – or may much too late – realize what new regulatory demands apply to a given innovation. Rule-makers’ near exclusive reliance on stable and presumptively optimal rules created to attain permanent solutions for perceived regulatory issues ignores the ever-changing environment for rules driven by the exponential growth of technology, and the associated exponential growth of innovation.  The timing of regulation in an environment of exponential innovation is a primary problem for regulators. Formal rulemaking in the existing regulatory infrastructure is almost always too time-consuming because the speed of product innovation often makes regulations pertaining to an innovative product obsolete before such regulations are finalized. Finally, the existing regulatory infrastructure, with stable and presumptively optimal rules, is largely incapable of addressing the ever-increasing unknown future contingencies associated with disruptive innovation. Given the pace of innovation, future contingencies in rulemaking are likely to increase substantially, making the dynamic anticipation of future contingencies more important for rulemaking.

Lawmaking and regulatory design need to become more dynamic and anticipatory in their efforts to address this pacing problem. Increased reliance on different sources of data surrounding new technologies can provide some signals or clues about what, when and, to a certain extent, how to regulate.

Here, I show that data relating to investment in new technology and innovation is of particular importance in this context. A plethora of investment data is readily available to make accurate predictions regarding what the next ‘big thing’ is likely to be.  Such data can be used as an index or proxy for the necessity of regulation. Because start-up companies are the ones that usually challenge existing rules, laws and regulations, private data sources are widely available. The proliferation of the better hand-collected global databases on the market, such as CB Insights, PitchBook and Mattermark, can make an important contribution to a ‘data-driven’ regulatory approach.

Investment data can help to develop a list of technologies and issues that need to be the focus of regulatory attention. From such data, rule-makers can get a better – and earlier – sense of which technologies are developing and which technologies need regulatory attention. This might then allow regulators to be more pro-active and avoid wasting resources on technologies that are unlikely to make it to market. It would also allow regulators to more accurately define the scope of a technology by focusing on the type of firm that is attracting attention.

Wulf A. Kaal is an Associate Professor at the University of Saint Thomas School of Law (Minneapolis).

How to Regulate Disruptive Innovation

How to Regulate Disruptive Innovation – from Facts to Data by Wulf A. Kaal , Erik P. M. Vermeulen :: SSRN

Wulf A. Kaal  
University of St. Thomas, Minnesota – School of Law; European Corporate Governance Institute (ECGI)

Erik P. M. Vermeulen 
Tilburg University – Department of Business Law; Philips Lighting – Legal Department; Tilburg Law and Economics Center (TILEC); Kyushu University – Graduate School of Law


Disruptive innovation creates increasing regulatory challenges. The reason for this is simple: Regulation is usually reactive, responding to facts. However, we currently live in a world of data, not facts. Regulation must therefore be proactive and dynamically responsive to data and trends. This paper discusses the following questions: (1) Why should regulators be proactive?, (2) When should regulators respond?, (3) What should regulators respond to? and (4) How should regulators respond? Using a dataset comprising over 77,000 venture capital deals with over 35,000 companies in the United States from 2005 to 2015, the paper shows how investment data can provide important feedback on innovation trends and associated risks for regulators, optimize the timing of regulation, and support anticipatory rulemaking.

Number of Pages in PDF File: 42

Keywords: Disruptive Innovation, Venture Capital, Venture Investments, Dynamic Regulation, Feedback Effects, Optimized Information for Regulation, Anticipatory Regulation, Big Data

JEL Classification: K20, K23, K32, L43, L5, O31, O32

The Effect of Non- and Deferred Prosecution Agreements on Corporate Governance: Evidence from 1993-2013

Non- and Deferred Prosecution Agreements (N/DPAs) are controversial because prosecutors, not judges or the legislature, are changing the governance of leading public corporations and entire industries. To analyze N/DPAs’ corporate governance implications and provide policy makers with guidance, the authors code all publicly available N/DPAs (N=271) from 1993 to 2013, identifying 215 governance categories and subcategories. The authors find evidence that the execution of N/DPAs is associated with significant corporate governance changes. The study categorizes mandated corporate governance changes for entities that executed an N/DPA as follows: (1) Business Changes, (2) Board Changes, (3) Senior Management, (4) Monitoring, (5) Cooperation, (6) Compliance Program, and (7) Waiver of Rights. The authors supplement the analysis of governance changes in these categories with a more in depth evaluation of the respective subcategories of governance changes. The authors also code and analyze preemptive remedial measures, designed by corporations to preempt the execution of an N/DPA or corporate criminal indictment. The paper evaluates the implications of the empirical evidence for boards, management, and legal practitioners.

Keywords: Non Prosecution Agreement, Deferred Prosecution Agreement, Panel Data, Corporate Governance

JEL Classification: G3, K14, K22

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