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While two-sided platforms (e.g., video game consoles) depend on complements (e.g., games) for their success, the success of complements is also influenced by platform-level dynamics. Research suggests that greater platform adoption benefits complements by providing more potential users, but this assumes that platform adopters are homogeneous. We build on extensive research exploring the heterogeneity between early and late platform adopters to identify counterintuitive dynamics for complements. Complements launched early in a platform’s life cycle face an audience entirely of early platform adopters, whereas later-launching complements face a mixed audience of both early and late adopters, and we argue that differences in preferences and behavior between early and late adopters affect whether complements will succeed and which types will be most successful. We explore these dynamics in the context of the console video game industry using a unique data set of 2,918 video games released in the United Kingdom from 2000 to 2007. We show that despite the increase in the potential user pool as the platform evolves, video games launched later in the platform life cycle realize lower sales than those launched earlier. While increased competition explains part of this effect, we show substantial evidence consistent with our theory of preference differences between early and late adopters. This includes the finding that the negative effect is stronger for novel games and that the gap between popular and less popular complements widens as later adopters move into the platform, consistent with late adopters being risk averse and seeking to avoid purchasing mistakes. The e-companion is available at https://doi.org/10.1287/orsc.2017.1183 .

A major result in the study of two-sided platforms is the strategic interdependence between the two sides of the same platform, leading to the implication that a platform can maximize its total profits by subsidizing one of its sides. We show that this result largely depends on assuming that at least one side of the market single-homes. As technology makes joining multiple platforms easier, we increasingly observe that participants on both sides of two-sided platforms multihome. The case of multihoming on both sides is mostly ignored in the literature on competition between two-sided platforms. We help to fill this gap by developing a model for platform competition in a differentiated setting (a Hotelling line), which is similar to other models in the literature but focuses on the case where at least some agents on each side multihome. We show that when both sides in a platform market multihome, the strategic interdependence between the two sides of the same platform will diminish or even disappear. Our analysis suggests that the common strategic advice to subsidize one side in order to maximize total profits may be limited or even incorrect when both sides multihome, which is an important caveat given the increasing prevalence of multihoming in platform markets.

We show that supply-side financial shocks have a large impact on firms’ investment. We develop a new methodology to separate firm borrowing shocks from bank supply shocks using a vast sample of matched bank-firm lending data. We decompose aggregate loan movements in Japan for the period 1990–2010 into bank, firm, industry, and common shocks. The high degree of financial institution concentration means that individual banks are large relative to the size of the economy, which creates a role for granular shocks as in Gabaix’s (2011) study. We show that idiosyncratic granular bank supply shocks explain 30–40 percent of aggregate loan and investment fluctuations.

In a model with endogenous number of innovating firms, we show that whether patent protection increases R&D investment is ambiguous, and depends on the market demand function and the cost of R&D. If the market size increases with number of firms, patent protection reduces R&D investment if the cost of R&D is sufficiently high, and higher product differentiation increases the possibility of lower R&D investment under patent protection. If the market size does not increase with number of firms, patent protection never reduces R&D investment. We find that welfare is lower under patent protection than under no patent protection.

This article considers the problem of testing many moment inequalities where the number of moment inequalities, denoted by p, is possibly much larger than the sample size n. There is a variety of economic applications where solving this problem allows to carry out inference on causal and structural parameters; a notable example is the market structure model of Ciliberto and Tamer (2009) where p = 2m+1 with m being the number of firms that could possibly enter the market. We consider the test statistic given by the maximum of p Studentized (or t-type) inequality-specific statistics, and analyse various ways to compute critical values for the test statistic. Specifically, we consider critical values based upon (1) the union bound combined with a moderate deviation inequality for self-normalized sums, (2) the multiplier and empirical bootstraps, and (3) two-step and three-step variants of (1) and (2) by incorporating the selection of uninformative inequalities that are far from being binding and a novel selection of weakly informative inequalities that are potentially binding but do not provide first-order information. We prove validity of these methods, showing that under mild conditions, they lead to tests with the error in size decreasing polynomially in n while allowing for p being much larger than n; indeed p can be of order exp(nc ) for some c > 0. Importantly, all these results hold without any restriction on the correlation structure between p Studentized statistics, and also hold uniformly with respect to suitably large classes of underlying distributions. Moreover, in the online supplement, we show validity of a test based on the block multiplier bootstrap in the case of dependent data under some general mixing conditions.

Bitcoin provides its users with transaction-processing services which are similar to those of traditional payment systems. This article models the novel economic structure implied by Bitcoin’s innovative decentralized design, which allows the payment system to be reliably operated by unrelated parties called miners. We find that this decentralized design protects users from monopoly pricing. Competition among service providers within the platform and free entry imply no entity can profitably affect the level of fees paid by users. Instead, a market for transaction-processing determines the fees users pay to gain priority and avoid transaction-processing delays. The article (i) derives closed-form formulas of the fees and waiting times and studies their properties, (ii) compares pricing under the Bitcoin Payment System to that under a traditional payment system operated by a profit-maximizing firm, and (iii) suggests protocol design modifications to enhance the platform’s efficiency. The Appendix describes and explains the main attributes of Bitcoin and the underlying blockchain technology.

Because the literature on platform competition emphasizes the role of network effects, it prescribes rapidly expanding a network of platform users and complementary applications to capture entire markets. We challenge the unconditional logic of a winner-take-all (WTA) approach by empirically analyzing the dominant strategies used to build and position platform systems in the U.S. video game industry. We show that when platform firms pursue two popular WTA strategies concurrently and with equal intensity (growing the number and variety of applications while also securing a larger fraction of those applications with exclusivity agreements), it diminishes the benefits of each strategy to the point that it lowers platform performance. We also show that a differentiation strategy based on distinctive positioning improves a platform's performance only when a platform system is highly distinctive relative to its rivals. Our results suggest that platform competition is shaped by important strategic trade-offs and that the WTA approach will not be universally successful.

The markets for electricity, gas and temperature have distinctive features, which provide the focus for countless studies. For instance, electricity and gas prices may soar several magnitudes above their normal levels within a short time due to imbalances in supply and demand, yielding what is known as spikes in the spot prices. The markets are also largely influenced by seasons, since power demand for heating and cooling varies over the year. The incompleteness of the markets, due to nonstorability of electricity and temperature as well as limited storage capacity of gas, makes spot-forward hedging impossible. Moreover, futures contracts are typically settled over a time period rather than at a fixed date. All these aspects of the markets create new challenges when analyzing price dynamics of spot, futures and other derivatives.

Peer-to-peer markets such as eBay, Uber, and Airbnb allow small suppliers to compete with traditional providers of goods or services. We view the primary function of these markets as making it easy for buyers to find sellers and engage in convenient, trustworthy transactions. We discuss elements of market design that make this possible, including search and matching algorithms, pricing, and reputation systems. We then develop a simple model of how these markets enable entry by small or flexible suppliers, and how they impact existing firms. Finally, we consider the regulation of peer-to-peer markets and the economic arguments for different approaches to licensing and certification, data, and employment regulation.

We develop a model of advertising markets in an environment where consumers may switch (or “multi-home”) across publishers. Consumer switching generates inefficiency in the process of matching advertisers to consumers, because advertisers may not reach some consumers and may impress others too many times. We find that when advertisers are heterogeneous in their valuations for reaching consumers, the switching-induced inefficiency leads lower-value advertisers to advertise on a limited set of publishers, reducing the effective demand for advertising and thus depressing prices. As the share of switching consumers expands (e.g., when consumers adopt the Internet for news or increase their use of aggregators), ad prices fall. We demonstrate that increased switching creates an incentive for publishers to invest in quality as well as extend the number of unique users, because larger publishers are favored by advertisers seeking broader “reach” (more unique users) while avoiding inefficient duplication.