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on Industrial Organization |
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Issue of 2024‒01‒15
five papers chosen by |
| By: | Martimort, David; Sand-Zantman, Wilfried |
| Abstract: | We analyze the effect of media mergers in a model that stresses, on the one hand, the fact that media are two-sided platforms willing to attract advertisers and viewers and, on the other hand, that strong competitors have emerged to challenge traditional media on both sides. We show that a merger has two conflicting effects on traditional media’s incentives to invest in quality programs and to exploit their market power. When competition is primarily between traditional media, a Business-Stealing Effect dominates, and the merger is detrimental to advertisers and viewers. When the competition is mainly between the traditional media and their new competitors, an Ecosystem Effect dominates, and the merger benefits advertisers and viewers. We extend this setting to discuss the role of financial constraints that might limit investments in the quality of programs and show that the same effects are at play. |
| Keywords: | Media; competition; merger |
| JEL: | L82 L22 G34 |
| Date: | 2023–12–05 |
| URL: | http://d.repec.org/n?u=RePEc:tse:wpaper:128764&r=ind |
| By: | Elisabeth Honka; Stephan Seiler; Raluca Ursu |
| Abstract: | Researchers are increasingly able to observe consumers’ behavior prior to a purchase, such as their navigation through a store or website and the products they consider. Such pre-purchase (or search) data can be valuable to researchers in a variety of ways: as an additional source of information to estimate consumer preferences, to understand how firms can influence the search process through marketing mix variables, and to analyze how limited information about products shapes market outcomes. We provide an overview of these three areas with a particular emphasis on online and offline retailing. |
| Keywords: | consumer search, limited information, consideration sets, retailing |
| JEL: | D43 D83 L13 |
| Date: | 2023 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_10786&r=ind |
| By: | Jarkko Harju (Tampere University and Finnish Center of Excellence in Tax Systems Research); Toni Juuti (Labour Institute for Economic Research LABORE, Tampere University and Finnish Center of Excellence in Tax Systems Research); Tuomas Matikka (VATT Institute for Economic Research and Finnish Center of Excellence in Tax Systems Research) |
| Abstract: | Using detailed full-population data from Finland, we provide evidence on selection into entrepreneurship and the dynamic implications of establishing a new business. Individuals at the very top of the personal income distribution are much more likely to start a new incorporated business compared to others. There is no similar selection based on parental income, but more than half of new entrepreneurs have entrepreneurial parents. Entrepreneurship is associated with a similar average income gain of 20% relative to comparable wage earners throughout both personal and parental income distributions. However, key firm-level outcomes such as productivity and job creation are positively linked with personal income. This suggests that high-income individuals do not only benefit from entrepreneurship personally, but their businesses are associated with the largest positive spillovers in the economy. In contrast, we find no significant differences in the outcomes of new firms by parental income or parental background in entrepreneurship. |
| Keywords: | entrepreneurship; income mobility; inequality; productivity |
| JEL: | L26 J24 J3 |
| Date: | 2023–12 |
| URL: | http://d.repec.org/n?u=RePEc:fit:wpaper:17&r=ind |
| By: | Frédéric Marty; Thierry Warin |
| Abstract: | This paper examines algorithmic collusion from legal and economic perspectives, highlighting the growing role of algorithms in digital markets and their potential for anti-competitive behavior. Using bandit algorithms as a model, traditionally applied in uncertain decision-making contexts, we illuminate the dynamics of implicit collusion without overt communication. Legally, the challenge is discerning and classifying these algorithmic signals, especially as unilateral communications. Economically, distinguishing between rational pricing and collusive patterns becomes intricate with algorithm-driven decisions. The paper emphasizes the imperative for competition authorities to identify unusual market behaviors, hinting at shifting the burden of proof to firms with algorithmic pricing. Balancing algorithmic transparency and collusion prevention is crucial. While regulations might address these concerns, they could hinder algorithmic development. As this form of collusion becomes central in antitrust, understanding through models like bandit algorithms is vital, since these last ones may converge faster towards an anticompetitive equilibrium. Cet article examine la collusion algorithmique du point de vue juridique et économique, mettant en évidence le rôle croissant des algorithmes dans les marchés numériques et leur potentiel comportement anticoncurrentiel. En utilisant les algorithmes de bandit comme modèle, traditionnellement appliqués dans des contextes de prise de décision incertaine, nous mettons en lumière la dynamique de la collusion implicite sans communication explicite. Sur le plan juridique, le défi réside dans le discernement et la classification de ces signaux algorithmiques, en particulier en tant que communications unilatérales. Sur le plan économique, la distinction entre une tarification rationnelle et des schémas collusifs devient complexe avec les décisions pilotées par des algorithmes. L'article met l'accent sur l'impératif pour les autorités de la concurrence d'identifier les comportements de marché inhabituels, laissant entendre un transfert du fardeau de la preuve aux entreprises pratiquant la tarification algorithmique. Équilibrer la transparence algorithmique et la prévention de la collusion est crucial. Bien que la réglementation puisse traiter ces préoccupations, elle pourrait entraver le développement des algorithmes. À mesure que cette forme de collusion devient centrale dans le domaine de la concurrence, la compréhension à travers des modèles tels que les algorithmes de bandit est essentielle, car ces derniers peuvent converger plus rapidement vers un équilibre anticoncurrentiel. |
| Keywords: | Algorithmic Collusion, Bandit Algorithms, Antitrust Enforcement, Unilateral Signals, Pricing Strategies, Collusion algorithmique, algorithmes de bandits, Application du droit de la concurrence, signaux unilatéraux, Stratégies de tarification |
| JEL: | L13 L41 K21 |
| Date: | 2023–12–22 |
| URL: | http://d.repec.org/n?u=RePEc:cir:cirwor:2023s-26&r=ind |
| By: | Monique Champion; Chris Edmond; Jonathan Hambur |
| Abstract: | Do variable profit margins play a substantial role in amplifying inflationary dynamics? Using detailed administrative micro data for Australia we find that: (i) there is some evidence that prices tended to increase by more in industries that had increasing markups over the 2004-2017 period, but (ii) passthrough from cost shocks to prices appears to be incomplete with no statistically significant increase in passthrough in the recent period, and (iii) there is evidence that passthrough is lower in less competitive industries. Viewed through the lens of macroeconomic models with variable markups, these facts are inconsistent with substantial inflation amplification. To generate substantial inflation amplification requires both that average passthrough is higher than is observed in Australian data and that passthrough is higher in less competitive industries. We calibrate a model with variable markups to match key facts from the Australian data. For our benchmark parameterization we find that, if anything, variable markups are predicted to dampen inflation. |
| Keywords: | inflation; markups; microdata; cost shocks; pass-through; industry concentration; competition |
| Date: | 2023–11 |
| URL: | http://d.repec.org/n?u=RePEc:rba:rbaacp:acp2023-05&r=ind |