Making the Rules
Should platforms be allowed to sell on their own marketplaces?
Andrei Hagiu, Tat-How Teh & Julian Wright
RAND Journal of Economics, Summer 2022, Pages 297-327
A growing number of digital platforms operate in a dual mode: running marketplaces for third-party products, while selling their own products on those marketplaces. We build a model to explore the implications of this controversial practice. We analyze the tradeoffs that arise from a regulatory ban on the dual mode, showing how such a ban can harm consumer surplus and welfare even when the platform would otherwise engage in product imitation and self-preferencing. In the empirically most relevant scenarios, policies that prevent platform imitation and self-preferencing generate better outcomes than an outright ban on the dual mode.
Shota Ichihashi & Byung-Cheol Kim
Management Science, forthcoming
We study competition for consumer attention in which platforms can sacrifice service quality for attention. A platform can choose the "addictiveness" of its service. A more addictive platform yields consumers a lower utility of participation but a higher marginal utility of allocating attention. We provide conditions under which increased competition can harm consumers by encouraging platforms to offer low-quality services. In particular, if attention is scarce, increased competition reduces the quality of services because business-stealing incentives induce platforms to increase addictiveness. Restricting consumers' platform usage may decrease addictiveness and improve consumer welfare. A platform's ability to charge for its service can also decrease addictiveness.
Specialization in a Knowledge Econom
University of Pennsylvania Working Paper, March 2022
Using firm-level data from the US Census Longitudinal Business Database (LBD), this paper exhibits novel evidence about a wave of specialization experienced by US firms in the 1980s and 1990s. Specifically: 1) Firms, especially innovating ones, decreased production scope, i.e., the number of industries in which they produce. 2) Small firms increased innovation relative to production while large firms increased production relative to innovation. A new hypothesis is proposed to explain these phenomena. Pro-patent reforms in the 1980s and 1990s make firms' innovations more commodified and tradable. Trading provides another channel for firms to monetize their innovation besides production, especially when innovations are mismatched with a firm's production. Production scope then contributes less to the value of a firm's innovation, enabling innovation to shift to small firms with limited production scope. To gauge the importance of the new hypothesis, an endogenous growth model is developed with potential mismatches between innovation and production. Calibrating the model to data suggests that increasing tradability of innovation output can explain 25% of the observed production scope decrease and 58% of the reallocation of innovation activities. It results in a 0.64 percent point increase in the annual economic growth rate. Using regional and firm-level differences in exposure to patent policies, difference-in-difference analysis confirms causality from the pro-patent reforms to firms' production scope shrinkage.
AI in the Government: Responses to Failures
Chiara Longoni, Luca Cian & Ellie Kyung
Journal of Marketing Research, forthcoming
Artificial Intelligence (AI) is pervading the government and transforming how public services are provided to consumers - from allocation of government benefits to enforcement of the law, monitoring of risks, and provision of services. Despite technological improvements, AI systems are fallible and may err. How do consumers respond when learning of AI's failures? In thirteen preregistered studies (N = 3,724) across policy areas, we show that algorithmic failures are generalized more broadly than human failures. We term this effect algorithmic transference, as it is an inferential process that generalizes (i.e., transfers) information about one member of a group to another member of that same group. Rather than reflecting generalized algorithm aversion, algorithmic transference is rooted in social categorization: it stems from how people perceive a group of AI systems versus a group of humans. Because AI systems are perceived as more homogeneous than people, failure information about one AI algorithm is transferred to another algorithm at a higher rate than failure information about a person is transferred to another person. Assessing AI's impact on consumers and societies, we show how the premature or mismanaged deployment of faulty AI technologies may undermine the very institutions that AI systems are meant to modernize.
Optimal Standards of Proof in Antitrust
Murat Mungan & Joshua Wright
International Review of Law and Economics, forthcoming
Economic analyses of antitrust institutions have thus far focused predominantly on optimal penalties and the design of substantive legal rules, and have largely ignored the standard of proof used in trials as a policy tool in shaping behavior. This neglected tool can play a unique role in the antitrust context, where a given firm may have the choice to engage in exceptional anticompetitive or procompetitive behavior, or simply follow more conventional business practices. The standard of proof used in determining the legality of a firm's conduct affects not only whether the firm chooses to engage in pro- versus anticompetitive behavior, but also whether it chooses to remain passive. We introduce a model to investigate the effects of this additional tradeoff on the optimal standard of proof. The nature of these effects depends upon the relationship between the beneficial impact of procompetitive behavior versus the harmful impacts of anticompetitive behavior, since this relationship is what determines the costs associated with Type I and Type II error. Adopting Judge Easterbrook's presumption that preventing procompetitive behavior is more harmful than allowing anticompetitive behavior, we show that the standard of proof facing plaintiffs in antitrust cases ought to be stronger than preponderance of the evidence.
Sunk Cost Bias and Time Inconsistency: A Strategic Analysis of Pricing Decisions
Sanjay Jain & Haipeng (Allan) Chen
Management Science, forthcoming
It is generally acknowledged that sunk cost bias leads to suboptimal decisions, such as escalation of commitment. Some researchers, however, suggest that sunk cost bias can be beneficial when consumers have self-control problems. In this paper we explore the case when consumers with sunk cost bias have time-inconsistent preferences and, therefore, suffer from self-control problems. We experimentally demonstrate that sunk costs can make subjects better off by inducing higher effort. We then develop an analytical model to explore the implications of sunk cost bias for firm's pricing strategy. We find that, in the presence of sunk cost bias, higher prices can lead to higher experienced quality. We show that sunk cost bias can sometimes improve firm's profits, lead to lower prices, and increase welfare. Our results suggest that, when consumers use a product for multiple periods, pricing policies such as 0% financing, which are often viewed as exploitative, can instead lead to lower total prices, higher profits, and higher welfare.
Estimating Discrete Games with Many Firms and Many Decisions: An Application to Merger and Product Variety
Ying Fan & Chenyu Yang
NBER Working Paper, June 2022
This paper presents a new method for estimating discrete games based on bounds of conditional choice probabilities. The method does not require solving the game and is scalable to models with many firms and many discrete decisions. We apply the method to study merger effects on firm entry and product variety in the retail craft beer market in California. We simulate an acquisition of multiple craft breweries by a large brewery and find that the acquisition would induce firm entry and product entry by non-merging firms. However, these changes are insufficient to offset the negative welfare effects resulting from the higher prices and decreased product offerings by the merging firms.
Michael Gmeiner & Robert Gmeiner
Journal of Labor Research, June 2022, Pages 163-202
This paper compares the effectiveness of two mechanisms of regulation enforcement: (1) the frequency of inspections and (2) penalties for violations. Threat effects of increased penalties and inspection rates, rather than corrective effects upon receiving an inspection or penalty, are the focus of analysis. Mining industry data from 2004-2009 are used to analyze the responses of mines to separate increases in inspections and citation penalties regarding regulations of safety standards. Mines did not improve safety in response to increased penalties at the ex-ante inspecting rates; however, mines significantly reduced accidents under increased inspections when implemented at those higher penalty rates. The identification strategy results in a local average treatment effect that implies increasing inspection rates from current levels would likely increase social welfare. Results are shown to be robust to bandwidth changes and model specification. The interpretation of the estimated local effect in the context of selection is analyzed. Robustness checks regarding selection exploit staffing changes and restrict to similar samples of treated and non-treated mines, justifying that results are representative.
The Hidden Costs of Securing Innovation: The Manifold Impacts of Compulsory Invention Secrecy
Management Science, forthcoming
One of the most commanding powers of the U.S. Patent and Trademark Office (USPTO) is to compel inventions into secrecy, withholding patent rights and prohibiting disclosure, to prevent technology from leaking to foreign competitors. This paper studies the impacts of compulsory secrecy on firm invention and the wider innovation system. In World War II, USPTO issued secrecy orders to more than 11,000 patent applications, which it rescinded en masse at the end of the war. Compulsory secrecy caused implicated firms to shift their patenting away from treated classes, with effects persisting through at least 1960. It also restricted commercialization and impeded follow-on innovation. Yet it appears it was effective at keeping sensitive technology out of public view. The results provide insight into the effectiveness of compulsory secrecy as a regulatory strategy and into the roles, and impacts, of formal intellectual property in the innovation system.
Testing the Hayek hypothesis: Recent theoretical and experimental evidence
Omar Al-Ubaydli, Peter Boettke & Brian Albrecht
PLoS ONE, July 2022
Economists well understand that the work of Friedrich Hayek contains important theoretical insights. It is less often acknowledged that his work contains testable predictions about the nature of market processes. Vernon Smith termed the most important one the 'Hayek hypothesis': that gains from trade can be realized in the presence of diffuse, decentralized information, and in the absence of price-taking behavior and centralized market direction. Vernon Smith tested this prediction by surveying data on laboratory experimental markets and found strong support. We extend Smith's work first by showing how subsequent theoretical advances provide a theoretical foundation for the Hayek Hypothesis. We then test the hypothesis using recent field experimental market data. Using field experiments allows us to test several other predictions from Hayek, such as that market experience increases the realized gains from trade. Generally speaking, we find support for Hayek's theories.