Blocking Someone
The Corporate Power Trilemma
Michael Bennett & Rutger Claassen
Journal of Politics, forthcoming
Abstract:
Authors critical of corporate power focus almost exclusively on one solution: bringing it under democratic control. However important this is, there are at least two other options, which are rarely discussed: reducing powerful firms' size and influence, or accepting corporate power as a necessary evil. This article provides a comparative perspective for evaluating all three options. It argues that the trade-offs we face in responding to corporate power have a trilemmatic structure. The pure strategies of accepting powerful firms, breaking them up, or rendering them more accountable are each incompatible with one of three important values: power balance, economies of scale, and minimizing agency costs, respectively. While the latter two concepts are purely economic and efficiency-based, the value of power balance can be grounded in a variety of reasons. Different normative interpretations of power balance are discussed, along with their implications for policy choices within the trilemma.
Ideas, Idea Processing, and TFP Growth in the US: 1899 to 2019
Kevin James, Akshay Kotak & Dimitrios Tsomocos
London School of Economics Working Paper, July 2022
Abstract:
Innovativity - an economy's ability to produce the innovations that drive total factor productivity (TFP) growth - requires both ideas and the ability to process those ideas into new products and/or techniques. We model innovativity as a function of endogenous idea processing capability subject to an exogenous idea supply constraint and derive an empirical measure of innovativity that is independent of the TFP data itself. Using exogenous shocks and theoretical restrictions, we establish that: i) innovativity predicts the evolution of average TFP growth; ii) idea processing capability is the binding constraint on innovativity; and iii) average TFP growth declined after 1970 due to a constraints on idea processing capability, not idea supply.
Intransitivity of Consumer Preferences for Privacy
Geoff Tomaino, Klaus Wertenbroch & Daniel Walters
Journal of Marketing Research, forthcoming
Abstract:
Consumers frequently exchange their private personal data with companies in return for goods and services such as access to search results or social networks. We provide a normative criterion to help assess whether companies adequately compensate consumers for their private data in these exchanges. Across a series of eleven experiments, we find that individuals place a higher price on their private data when they sell them for money than when they barter them for goods. In an application of the compatibility principle in cognitive psychology, we also find in two additional experiments that this effect occurs because money is a more compatible medium for valuing private data than goods are, which increases the weight of the data in monetary valuations, raising the prices that participants demand for their private data in money compared to goods. This discrepancy in valuations constitutes a violation of procedure invariance and amounts to an intransitivity of participants' preferences for privacy. Our findings suggest that companies may not be compensating consumers adequately for their data and that the ubiquitous markets for privacy may not function efficiently. Accordingly, we point to a consumer welfare argument for antitrust regulation of technology companies.
Regulatory Arbitrage and the Persistence of Financial Misconduct
Colleen Honigsberg, Edwin Hu & Robert Jackson
Stanford Law Review, April 2022, Pages 737-792
Abstract:
Financial advisor misconduct often has devastating consequences, leading lawmakers to seek tightened investor protections at the federal level. But many advisors can choose whether to be federally regulated or instead overseen by state insurance regulators, giving advisors with a history of misconduct incentives to select the more lax, state-level regulatory environment. Despite significant debate over the regulation of financial advice, no prior work has examined those incentives. Using a novel dataset, this Article identifies thousands of financial advisors who have committed serious misconduct and exited the primary federal regulatory regime - yet continue to advise investors, often using state insurance licenses. Advisors who exit are disproportionately likely to harm investors in the future. And advisors who do this are overwhelmingly male: women with a history of serious misconduct are more likely to exit financial services entirely. Our analysis identifies a limit of federal lawmaking in this area: Federal regulators necessarily rely on state regulators, who may become beholden to the interests of the insurance industry itself rather than the public. We show that more than one in ten state legislators who oversee insurance regulation are now, or were previously, in the business of selling insurance. We argue that existing tools for federal regulation of advisor misconduct risk the unintended consequence of pushing the worst advisors into poorly regulated state regimes.
Compensating Differentials for the Risk of Reinjury - Lessons from Professional Boxing
Peter Anderson
Journal of Sports Economics, forthcoming
Abstract:
A neglected area in the compensating-differential literature is how wages compensate workers for the risk of reinjury, specifically the risk of a subsequent mild Traumatic Brain Injury (mTBI). Using a new, unbalanced panel of 1,211 professional boxers, this paper finds that boxers' purses price for the risk of knockout reinjury risk while those that have never lost by knockout earn economically and statistically insignificant knockout-risk premiums. These results are consistent across three measures of previous knockout loss and three robustness tests, implying that current values of a statistical injury (VSI) underestimate previously injured workers' willingness to pay for safety.
Does Occupational Licensing Reduce Value Creation on Digital Platforms?
Peter Blair & Mischa Fisher
NBER Working Paper, August 2022
Abstract:
We test whether occupational licensing undercuts a key goal of digital marketplaces - to increase social surplus by increasing the effectiveness of customer search. Our setting is a large online marketplace in the $500B home services industry where a platform converts customer search into sales leads that are accepted for purchase by service providers on the platform. For each of the 21 million observations in our data set, we observe task-level variation in the state licensing requirements that service providers must meet to operate on the platform. Exploiting two natural experiments, we find that licensing reduces the accept rate of sales leads by an average of 25 percent. The accept rate drops because licensing reduces the aggregate labor supply of workers on the platform and not because licensing increases the volume of customer search. We develop a model and derive analytic expressions for the impact of licensing on the welfare of consumers, service providers and the platform as a function of seven sufficient statistics which we estimate from the data. We find that licensing a task reduces service provider surplus and platform surplus without increasing consumer surplus.
Compromising Accuracy to Encourage Regulatory Participation
Scott Baker & Anup Malani
Journal of Legal Studies, January 2022, Pages 1-38
Abstract:
This paper examines the value of accuracy in voluntary or opt-in regulatory regimes. We show that if welfare depends primarily on the ability to identify noncompliant firms, tolerating mistakes in concluding that firms meet regulatory standards (false positives) can improve welfare. Consumers or investors anticipate the regulatory error rate and discount the positive message of a compliance finding. Welfare is nonetheless improved because the mistaken exoneration acts as an incentive for noncompliant firms to submit to regulatory scrutiny, and as a result some noncompliant firms are unmasked.
Corporate Capture of Blockchain Governance
Daniel Ferreira, Jin Li & Radoslawa Nikolowa
Review of Financial Studies, forthcoming
Abstract:
We develop a theory of blockchain governance. In our model, the proof-of-work system, the most common set of rules for validating transactions in blockchains, creates an industrial ecosystem with specialized suppliers of goods and services. We analyze the interactions between blockchain governance and the market structure of the industries in the blockchain ecosystem. We show that the proof-of-work system may lead to a situation in which some large firms in the blockchain industrial ecosystem - blockchain conglomerates - capture the governance of the blockchain.
GMO and Non-GMO Labeling Effects: Evidence from a Quasi-Natural Experiment
Aaron Adalja et al.
Marketing Science, forthcoming
Abstract:
The United States recently mandated disclosure labels on all foods that contain genetically modified organisms (GMOs), despite longstanding, widespread use of voluntary third-party non-GMO labeling. We leverage the earlier passage and implementation of a mandatory GMO labeling law in Vermont as a quasi-natural experiment to show that adding this mandatory labeling into a market with pre-existing voluntary non-GMO labels had no effect on demand. Instead, the legislative process made consumers aware of GMO topics and increased non-GMO product sales before the GMO labeling mandate went into effect. The GMO-related legislative processes also increased non-GMO product demand in other states that considered, but did not implement, GMO labeling mandates. We find that 36% of new non-GMO product adoption can be explained by differences in consumer awareness tied to legislative activity. Our findings suggest that voluntary non-GMO labels may have provided an efficient disclosure mechanism without mandatory GMO labels.
Depreciating Licenses
Glen Weyl & Anthony Lee Zhang
American Economic Journal: Economic Policy, August 2022, Pages 422-448
Abstract:
Many governments assign use licenses for natural resources, such as radio spectrum, fishing rights, and mineral extraction rights, through auctions or other market-like mechanisms. License design affects resource users' investment incentives as well as the efficiency of asset allocation. No existing license design achieves first-best outcomes on both dimensions. Long-term licenses give owners high investment incentives but impede reallocation to high-valued entrants. Short-term licenses improve allocative efficiency but discourage investment. We propose a simple new mechanism, the depreciating license, and we argue that it navigates this trade-off more effectively than existing license designs.
Legal Protection against Retaliatory Firing Improves Workplace Safety
Matthew Johnson, Daniel Schwab & Patrick Koval
Review of Economics and Statistics, forthcoming
Abstract:
Workplace safety policies are designed to ensure that employers internalize the costs of injuries, but employers can undermine these policies with threats of dismissal. We show that states' adoption of the public policy exception to at-will employment - an exception forbidding employers from firing workers for filing workers' compensation claims or for whistleblowing - led to a substantial reduction in injuries. The widespread adoption of the public policy exception explains 14 percent of the decline in fatal injury rates between 1979 and 1994. Statutory protections from retaliatory firing also improved safety, but only when employers faced sufficiently strong penalties for violating them.
Should Digital Platforms Share Data with Governments? Evidence from Airbnb
Hongchang Wang et al.
University of Texas Working Paper, June 2022
Abstract:
As digital platforms continue to thrive, data transparency has attracted significant interest from researchers and regulators. Advocates argue that digital platforms cannot be well governed without access to their user data, while proposals to grant governments access to user data are continuously rejected because of privacy concerns, cost, and the impact on innovation. In this paper, we explore a unique program initiated by Airbnb that grants local governments real-time access to their transactional data and study how sharing user data with governments affects market outcomes on digital platforms. First, we find that the total number of active listings decreased by about 5.9% after the program, which can be primarily attributed to exits and deterred entrances. In contrast, the total revenue on the platform did not change dramatically before and after. Second, we find evidence consistent with two underlying mechanisms (of the program impacts): compliance with regulations and hosts' privacy concerns. Our study is among the first to explore data sharing between digital platforms and governments, and our empirical findings have profound implications for regulators, market participants, and other stakeholders of digital platforms.