ABSTRACT This paper investigates the interplay between interoperability and the incentives to invest in cybersecurity in digital markets. We develop a two‐sided symmetric duopoly model in which cyberattacks create a congestion‐like externality, and interoperability amplifies hackers' incentives to target connected platforms. We show that interoperability affects cybersecurity investment through multiple channels, potentially producing a non‐monotonic relationship: Low interoperability promotes risk‐mitigation efforts, whereas high interoperability may discourage investment due to a public good effect. We then compare private and social incentives to adopt interoperability, identifying potential sources of misalignment. Finally, we extend the baseline model to account for additional factors shaping the desirability of interoperability, including platforms' business models, users' awareness of cyber risk, asymmetries in user bases, and the role of alternative compensation schemes.
ABSTRACT Favoritism as a mode of corruption is a major concern in public procurement (PP) in many countries. We propose a regression discontinuity design (RDD) test arguing that the winning history of marginal winners and losers can be used to detect favoritism. We apply the empirical test to PP of cleaning services in Finland and find evidence of favoritism even in this relatively low corruption environment. First, winners of close races in terms of win margin tend to have won more also in the past, which is in contrast to competitive environment. Second, to rule out an alternative explanation of collusion based on incumbency, we show that these winners also tend to submit their bids the last, indicating information sharing about rival bids from the buyer to the favored bidder.
ABSTRACT We revisit the standard regularity assumption used to ensure uniqueness of the optimal price in monopoly models, namely that the Virtual Value (VV) function is monotone. This condition is typically imposed through strong distributional assumptions, such as log‐concavity, that restrict the model's flexibility and implicitly discipline the sign of comparative statics. We show that these assumptions can be relaxed without compromising tractability or uniqueness. Our main contribution is to introduce ‐Regularity, a weaker condition that requires monotonicity of the VV only beyond the threshold where marginal revenue becomes nonnegative. We demonstrate that many common non‐regular, unimodal distributions satisfy this local condition. This shift in focus allows standard first‐order methods to remain valid, and it enlarges the set of tractable demand primitives in applied IO. As an implication, when hazard rates are not monotone over the relevant pricing range, comparative statics need not follow the direction imposed by log‐concavity. The framework also reduces the need for ironing when modeling with heavy‐tailed demand.
This paper studies the effect of media market competition on confirmatory bias, the tendency to confirm common priors to appear competent, while accounting for both single- and multi-homing. It finds that competition helps sustain informative reporting when priors are relatively precise, but has the opposite effect when priors are diffuse. The reason is that when competing outlets are perceived as similarly competent, consumers optimally multi-home. This creates strategic complementarity in informative reporting and helps sustain it when the priors are relatively precise. However, when perceived competencies diverge, consumers single-home with the outlet they view as most competent, creating incentives for confirmatory reporting when the priors are diffuse.
This paper analyzes optimal licensing contracts when a licensee faces the risk of future infringement claims by unknown patent holders. In a setting where a noncompeting licensor contracts with a monopolistic manufacturer, fixed-fee licensing is optimal absent such claims. We show that the possibility of future patent claims makes it optimal to include a per-unit royalty. The royalty reduces the surplus available to potential third-party claimants and serves as a rent-protection device, trading off allocative inefficiency against hold-up risk. Restrictions on the contracting space can be justified when more realistic features of demand uncertainty or stochastic patent arrival are considered.
Firms can share data to discover potential synergies between their data sets and algorithms, eventually leading to more efficient mergers and acquisitions (M&A) decisions. However, data sharing also modifies the competitive balance when firms do not merge, and a company may be reluctant to share data with potential rivals. Under general conditions, we show that firms benefit from (partially) sharing data. By doing so, they can merge conditionally based on high synergies. Compared to a laissez-faire situation, the presence of a regulator allowing or refusing the M&A may increase or decrease data sharing, with a concomitant increase or decrease in consumer surplus. Hence, regulation can reduce the surplus of consumers it is willing to protect. We revisit the Google/Fitbit acquisition through the lens of this interplay between strategic data sharing and antitrust policy.
We propose a new approach to production function estimation that integrates the strengths of the proxy-variable (PV) and dynamic panel data (DPD) methods. Our framework augments the set of instruments for the level equation in Blundell and Bond [8] with a Berkson-type instrument motivated by economic theory, following Olley and Pakes [28], Levinsohn and Petrin [24], and Ackerberg et al. [4]. This modification allows unobserved productivity to include both a time-invariant ("fixed-effect") component and a time-varying component that follows a potentially nonlinear Markov process. Whereas the PV approach accommodates nonlinear Markov dynamics but not fixed effects, and the DPD approach accounts for fixed effects but only with linear Markov dynamics, our method relaxes both restrictions. Our estimator is straightforward to implement using GMM. Monte Carlo simulations demonstrate that it outperforms the canonical PV and DPD estimators when productivity persistence is low and fixed-effect heterogeneity is substantial.
Delaying bill payments to public utilities may provide an important strategy for households with volatile incomes to smooth their consumption. At the same time, allowing late payments may reduce net revenues for utilities, which often leads to higher prices to cover costs. Using billing records from a large water utility in Manila, this paper estimates a household consumption and savings model to evaluate counterfactual payment policies. A popular proposal to ensure upfront payments-prepaid metering-recoups less revenue than is needed to compensate households for their loss of consumption smoothing. Alternatively, a revenue-neutral policy allowing more late payments increases welfare by encouraging greater consumption smoothing.
Consider suppliers whose comparative advantages, which are unknown to a buyer, depend on the quantity procured. The distortions of the buyer purchase policy differs depending on the market characteristics. In a large market, either it overbuys to suppliers with steep marginal costs, who are better at producing a small volume; or it withholds the demand it addresses to suppliers with flatter marginal costs, who are better at producing a large volume. The latter policy is implemented through a concave tariff offered to the less capacity constrained suppliers. In a small market, demand withholding prevails and some suppliers can be excluded.
This paper examines the effects of incentivizing industrial users to reduce their electricity consumption using demand response auctions, in which rewards for curtailment depend on auction outcomes. Because true baseline consumption is unobserved, firms can strategically adjust both bids and consumption, leading to upward-biased estimates of program effectiveness. Using data on bids, auction outcomes, and hourly electricity consumption from steel producers in Taiwan, this paper employs a regression discontinuity design to show that not accounting for firms' strategic bidding behavior can lead to an overestimation of electricity reductions by at least 50%.
How does antitrust enforcement affect innovation when patents are the main barrier to entry? I address this question by empirically studying the US antitrust case against Xerox, the former monopolist in the market for plain-paper copiers. In 1975, Xerox accepted a consent decree whose primary remedy was compulsory licensing of all its copier-technology patents in the US and abroad. I show that this antitrust intervention promoted innovation by other firms in the copier industry, measured by a disproportionate increase in patenting in technology classes with a higher propensity for containing copier-related inventions. This effect is driven by Japanese competitors, whose patenting became more novel and diverse as they started developing smaller desktop copiers.
We study optimal simple rating systems that partition sellers into a finite number of tiers. We show that optimal ratings must be threshold partitions, and that for linear supply and Cournot competition with constant marginal cost, optimal thresholds solve a k-means clustering problem requiring only the quality distribution. For convex (concave) supply functions, optimal thresholds are higher (lower) than the k-means solution. For log-concave distributions, two-tier certification captures at least 50% of maximum welfare gains from full disclosure, with five tiers typically achieving over 90%. Applications to eBay and Medicare Advantage data illustrate our method.
We focus on the determinants of pharmaceutical drug prices. Using data from the Brazilian pharmaceutical market, we find large variations in drug prices across buyers, drug classes, and time periods. Our estimation results provide evidence that transaction-specific determinants between buyers and sellers (e.g., transaction volume, buyer's loyalty, multiple drug purchases from the same seller) exert strong effects on drug prices. Our counterfactuals show that group purchasing organizations achieve price reductions that vary across drug classes and that these price reductions primarily depend on buyer price sensitivity.
Electric vehicle (EV) drivers experience range anxiety (RA) due to a gap between latent travel demand and battery range. Low fuel prices or limited range exacerbate RA. Range relevance diminishes under high fuel prices, as driving demand is suppressed, while low fuel prices have small effects on RA when range is sufficiently high. We formalize and estimate RA, leveraging the implicit interaction between local electricity prices and range. Results suggest average prospective EV consumers expect $2500–3400/year welfare costs through the RA mechanism. These estimates have strong implications for policies targeting EV ownership, underscoring another channel EV costs exceed conventional vehicles.
We study RPM and vertical integration in a common agency setting with two differentiated manufacturers and one retailer, where consumer demand depends on both the manufacturers' and retailer's noncontractible efforts. Under vertical separation, the adoption of maximum RPM by both manufacturers is an equilibrium and intensifies competition, since manufacturing margins are positive to incentivize manufacturing effort. This benefits consumers and may lower industry profits relative to a scenario where RPM is not available. Vertical integration between the retailer and one of the manufacturers increases industry profits and, when retail effort is also important, may benefit consumers by mitigating double marginalization.
In this paper, we investigate how competition among NGOs to attract donations shapes the incentives that NGOs provide to their employees. NGOs hire workers to undertake development projects, which are horizontally and vertically differentiated. Workers perform constructive activities that enhance project quality, but can also engage in non-observable destructive activities that harm the employing organization. NGOs offer monetary incentives to encourage constructive effort, but also need monitoring to curb destructive behavior. Our analysis yields the following results: (i) a high mission orientation on the part of NGOs makes workers' misconduct harder to eliminate; (ii) increased competition in the market for donations leads to higher constructive effort and project quality, but also to greater destructive effort; (iii) relative to the social optimum, the market outcome entails inadequate monitoring and excessive destructive behavior.
We provide a novel empirical analysis of the role of technology licensing, between competitors, for genetically engineered (GE) traits in the US seed industry. We extend the standard differentiated-product Bertrand pricing model to include trait licensing, which permits us to recover marginal costs and (otherwise unobserved) royalty rates. Estimation relies on a large dataset of farm-level seed purchases. We find that markups over marginal cost are sizeable, and royalties for GE traits contribute a non-trivial amount to these markups. Licensing GE traits to competitors benefits all seed sellers and, notwithstanding its strategic effect on pricing, also increases total market surplus.
A data analytics company delivers an efficiency by supplying a pricing algorithm that allows prices to more effectively respond to demand variation. In this setting, I consider a new form of hub-and-spoke collusion: A data analytics company (hub) coordinates the prices of competitors (spokes) through its pricing algorithm. A novel finding is that the data analytics company's efficiency is a facilitating factor for collusion; a rise in this efficiency increases the supracompetitive markup and the incremental profit from collusion. Thus, markets in which a third party's services are solidly grounded in efficiency still warrant scrutiny by competition authorities because they are more prone to the emergence of collusion and anticompetitive harm.
We study an agency model with two sequential tasks, an initial task (e.g., development), which requires unverifiable effort, and a final task (e.g., production), whose environment is privately known only to the agent. The principal can either perform the initial task herself (hands-on management) or delegate it to the agent (hands-off management). We show that when the cost of effort for the initial task is low, hands-on management is optimal, as it mitigates the distortion caused by agent shirking. However, as the cost of effort increases, hands-off management becomes preferable. Under hands-on management, the principal's inability to commit leads her to overinvest in the initial task, which in turn exacerbates inefficiencies in the final task due to the agent's information rent. In contrast, hands-off management, despite the agent's shirking incentive, helps better target effort toward favorable project environments. Our analysis also reveals how effort costs can create systematic biases toward one management style over the other.
Platform interoperability is considered a powerful tool to promote competition in digital markets when network effects are at play. We study the effect of interoperability on competition between two ad-financed platforms, allowing for endogenous multi-homing of consumers. When the platforms are symmetric and decide non-cooperatively on their level of interoperability, interoperability emerges in equilibrium if the value of multi-homers relative to single-homers is sufficiently low for advertisers. From a welfare perspective, the equilibrium level of interoperability can be either too low or too high. When one (“large”) platform has an installed base of customers, its incentive to make its services interoperable is lower than for the other, smaller platform. However, mandating interoperability between the asymmetric platforms is not always socially optimal.
