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Increasingly, algorithms are supplanting human decision-makers in pricing goods and services. To analyze the possible consequences, we study experimentally the behavior of algorithms powered by Artificial Intelligence (Q-learning) in a workhorse oligopoly model of repeated price competition. We find that the algorithms consistently learn to charge supracompetitive prices, without communicating with one another. The high prices are sustained by collusive strategies with a finite phase of punishment followed by a gradual return to cooperation. This finding is robust to asymmetries in cost or demand, changes in the number of players, and various forms of uncertainty.

We propose a new theory of exclusive dealing. The theory is based on the assumption that a dominant firm has a competitive advantage over its rivals, and that the buyers' willingness to pay for the product is private information. In this setting, the dominant firm can impose contractual restrictions on buyers without necessarily compensating them, implying that exclusive dealing contracts can be both profitable and anticompetitive. We discuss the general implications of the theory for competition policy and illustrate by examples its applicability to antitrust cases.

Pricing decisions are increasingly in the “hands” of artificial algorithms. Scholars and competition authorities have voiced concerns that those algorithms are capable of sustaining collusive outcomes more effectively than can human decision makers. If this is so, then our traditional policy tools for fighting collusion may have to be reconsidered. We discuss these issues by critically surveying the relevant law, economics, and computer science literature.

This article unifies various approaches to the analysis of exclusive dealing that so far have been regarded as distinct. The common element of these approaches is that firms depart from efficient pricing, raising marginal prices above marginal costs. We show that with distorted prices, exclusive dealing can be directly profitable and anticompetitive provided that the dominant firm enjoys a competitive advantage over rivals. The dominant firm gains directly, rather than in the future, or in adjacent markets, thanks to the boost in demand it enjoys when buyers sign exclusive contracts. We discuss the implication of the theory for antitrust policy.

We analyze firms that compete by means of exclusive contracts and market-share discounts (conditional on the seller's share of customers' total purchases). With incomplete information about demand, firms have a unilateral incentive to use these contractual arrangements to better extract buyers' informational rents. However, exclusive contracts intensify competition, thus reducing prices and profits and (in all Pareto undominated equilibria) increasing welfare. Market-share discounts, by contrast, produce a double marginalization effect that leads to higher prices and harms buyers. We discuss the implications of these results for competition policy.

Endogenous growth models may exhibit either under or over-investment in R&D. The possibility of over-investment is generally attributed to a business stealing effect that arises as the latest innovator destroys and/or appropriates previous incumbent's rents. We argue that this conventional wisdom is misleading. In standard models, business stealing by itself cannot result in excessive R&D. We explain the other effects that must be at work here, thus contributing towards a better understanding of when and why the market may be biased towards excessive R&D.

We study a quality-ladder model of endogenous growth that produces stochastic leadership cycles. Over a cycle, industry leaders can innovate several successive times in the same sector before being replaced by a new entrant. Initially, new leaders do much of the research but they then tend to rest on their laurels and are eventually overtaken. The model generates a skewed firm size distribution and a deviation from Gibrat's law that accord with the empirical evidence. We also find conditions under which policy should favour R&D by incumbents, not outsiders, and show that stronger patent protection may reduce innovation and growth.

The innovation competition effect follows the basic logic of unilateral effects, which is equally applicable to product market competition and to innovation competition.5 Having articulated the view that horizontal mergers generally stifle innovation, the Commission concludes that a merger may have a negative impact on innovation, reducing R& amp;D investment and slowing down technological progress, independently of the more traditional effects on product market competition.® Thus, even mergers for which the static effects are benign could be regarded as anticompetitive in a dynamic perspective. [...]in a companion article, we have shown that Federico et al.'s analysis rests on a restrictive assumption that they overlook, namely that the retums to R& amp;D not only decrease with the level of R& amp;D expenditure (which is what the authors effectively assume) but that the rate of decrease is a large enough amount.12 This stronger condition is needed because, in addition to internalizing the externality, the merged firm can also better coordinate the R& amp;D activity of its research units.13 We show that when the retums to R& amp;D decrease with R& amp;D expenditure by a small enough amount, the merged firm's better coordination may increase total R& amp;D investment and the rate of innovation. Even abstracting from R& amp;D spillovers and dynamic efficiency gains, mergers that would expand output (for a given level of technology), have a positive impact on the incentive to innovate. [...]even in the worst-case scenario, Motta and Tarantino's model does not suggest that a merger with benign static effects can be blocked owing to its negative impact on innovation. [...]Motta and Tarantino's extended analysis allows for R& amp;D spillovers and efficiency gains in research.

We study the effect of the competitive selection process on the economy's rate of growth. In an extension of standard quality-ladder models of endogenous growth, we allow for the possibility that in each period several asymmetric firms (representing an endogenously determined number of past innovators) may be simultaneously active in an industry. Stronger competitive pressure then has conflicting effects on the incentive to innovate, lowering prices but also selecting the more efficient firms. We show that the market selection effect of competition always increases the incentive to innovate and find circumstances in which it can outweigh the traditional negative effect of lower prices.

I analyze the optimal degree of forward patent protection in a two-stage patent race framework. I compare three patent regimes, as the second innovation may be unpatentable and infringing (UI), patentable and infringing (PI), or patentable and not infringing (PN). Forward protection is highest in regime UI and lowest in regime PN. I identify a fundamental inefficiency affecting regime UI, namely that it always leads to underinvestment in the second innovation, and I note various determinants of the welfare ranking of the regimes. Specifically, strong forward protection becomes less attractive as the relative profitability of the first innovation increases and the relative difficulty of obtaining it decreases.