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on Industrial Competition |
| By: | Hangcheng Zhao; Ron Berman |
| Abstract: | Online sellers have been adopting AI learning algorithms to automatically make product pricing and advertising decisions on e-commerce platforms. When sellers compete using such algorithms, one concern is that of tacit collusion - the algorithms learn to coordinate on higher than competitive. We empirically investigate whether these concerns are valid when sellers make pricing and advertising decisions together, i.e., two-dimensional decisions. Our empirical strategy is to analyze competition with multi-agent reinforcement learning, which we calibrate to a large-scale dataset collected from Amazon.com products. Our first contribution is to find conditions under which learning algorithms can facilitate win-win-win outcomes that are beneficial for consumers, sellers, and even the platform, when consumers have high search costs. In these cases the algorithms learn to coordinate on prices that are lower than competitive prices. The intuition is that the algorithms learn to coordinate on lower advertising bids, which lower advertising costs, leading to lower prices. Our second contribution is an analysis of a large-scale, high-frequency keyword-product dataset for more than 2 million products on Amazon.com. Our estimates of consumer search costs show a wide range of costs for different product keywords. We generate an algorithm usage and find a negative interaction between the estimated consumer search costs and the algorithm usage index, providing empirical evidence of beneficial collusion. Finally, we analyze the platform's strategic response. We find that reserve price adjustments will not increase profits for the platform, but commission adjustments will. Our analyses help alleviate some worries about the potentially harmful effects of competing learning algorithms, and can help sellers, platforms and policymakers to decide on whether to adopt or regulate such algorithms. |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2508.08325 |
| By: | Luca Lorenzini; Antonio Martner |
| Abstract: | We study how nonlinear pricing in supply chains shapes output, firm entry, and aggregate welfare. We develop a general equilibrium model in which firms both charge and pay nonlinear prices along the supply chain. Relative to linear pricing, nonlinear prices increase firm-level output but reduce firm entry by distorting the distribution of profits, yielding ambiguous welfare effects. Using transaction-level data from Chilean firms, we document robust evidence consistent with widespread nonlinear pricing across buyer groups. Calibrating the model to the data, we find that nonlinear pricing raises production but deters entry. In equilibrium, output gains dominate: aggregate welfare losses from market power are approximately 18% lower under nonlinear prices than under linear pricing, indicating that analyses based on linear pricing overstate the welfare costs of market power. |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:chb:bcchwp:1049 |
| By: | Christos Genakos; Mario Pagliero; Lorien Sabatino; Tommaso Valletti (Cambridge Judge Business School, University of Cambridge) |
| Abstract: | Fixed book price (FBP) agreements are a form of resale price maintenance applied to books in various countries. FBP restricts retail price competition with the aim of promoting book production variety. Yet, despite its popularity and adoption in many countries, there is no empirical evidence on its effects. We offer systematic evidence on the impact of FBP on book variety and prices using a detailed new dataset from Italy that includes the universe of books published and bought, before and after the introduction of FBP. Our results indicate that FBP raises prices without significantly affecting the number of new books published in the marketplace. However, it also increases considerably the variety of books actually bought, especially from independent bookstores. We estimate a structural demand model that accounts for both effects, finding that consumers overall benefit from the regulation. |
| Date: | 2025–03 |
| URL: | https://d.repec.org/n?u=RePEc:jbs:wpaper:202501 |
| By: | Jeremy Proz; Martin Huber |
| Abstract: | Collusion and capacity withholding in electricity wholesale markets are important mechanisms of market manipulation. This study applies a refined machine learning-based cartel detection algorithm to two cartel cases in the Italian electricity market and evaluates its out-of-sample performance. Specifically, we consider an ensemble machine learning method that uses statistical screens constructed from the offer price distribution as predictors for the incidence of collusion among electricity providers in specific regions. We propose novel screens related to the capacity-withholding behavior of electricity providers and find that including such screens derived from the day-ahead spot market as predictors can improve cartel detection. We find that, under complete cartels - where collusion in a tender presumably involves all suppliers - the method correctly classifies up to roughly 95% of tenders in our data as collusive or competitive, improving classification accuracy compared to using only previously available screens. However, when trained on larger datasets including non-cartel members and applying algorithms tailored to detect incomplete cartels, the previously existing screens are sufficient to achieve 98% accuracy, and the addition of our newly proposed capacity-withholding screens does not further improve performance. Overall, this study highlights the promising potential of supervised machine learning techniques for detecting and dismantling cartels in electricity markets. |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2508.09885 |
| By: | Cesare Carissimo; Fryderyk Falniowski; Siavash Rahimi; Heinrich Nax |
| Abstract: | This paper proposes a fresh `meta-game' perspective on the problem of algorithmic collusion in pricing games a la Bertrand. Economists have interpreted the fact that algorithms can learn to price collusively as tacit collusion. We argue instead that the co-parametrization of algorithms -- that we show is necessary to obtain algorithmic collusion -- requires algorithm designer(s) to engage in explicit collusion by algorithm orchestration. To highlight this, we model a meta-game of algorithm parametrization that is played by algorithm designers, and the relevant strategic analyses at that level reveal new equilibrium and collusion phenomena. |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2508.14766 |
| By: | Förster, Manuel (Center for Mathematical Economics, Bielefeld University); Närmann, Fynn Louis (Center for Mathematical Economics, Bielefeld University) |
| Abstract: | We study a dynamic game in which a monopolistic seller sequentially discloses information about a binary state to a consumer through priced experiments. The consumer privately observes a binary signal which influences her willingness to pay for information. We show that if buyer types favor different actions but their willingness to pay for a state-revealing test is sufficiently close, then the seller can commit to a sequence of priced experiments that extracts the entire surplus of both consumer types simultaneously. The optimal sequence of experiments is such that the high-valuation type assigns a higher probability to outcomes that trigger further information acquisition, thus creating a difference in expected costs. As a key element of the construction, we introduce an ‘encryption protocol’ under which the consumer faces a stopping problem. We then characterize situations in which the seller strictly benefits from a dynamic selling strategy when perfect price discrimination is not feasible. Finally, we illustrate our framework in the context of medical diagnostic testing, showing that a free test followed by a state-revealing test is often sufficient to improve revenue in comparison with a static approach. |
| Keywords: | Information design, dynamic mechanism, selling information, encryption, price discrimination |
| Date: | 2025–07–03 |
| URL: | https://d.repec.org/n?u=RePEc:bie:wpaper:749 |
| By: | Elías Albagli; Mr. Francesco Grigoli; Emiliano Luttini; Dagoberto Quevedo; Marco Rojas |
| Abstract: | This paper documents five empirical facts about the role of strategic complementarities in firms’ price-setting behavior, using administrative data from Chilean firms. (1) Strategic complementarities play a dominant role in price setting, exerting a stronger influence than changes in marginal costs. (2) While the strength of strategic complementarities varies across sectors, they consistently outweigh the role of cost changes. (3) In high-inflation environments, firms become more responsive to changes in the prices of their competitors. (4) Firms respond more strongly to competitor price increases than to decreases, mirroring the `rockets and feathers' phenomenon of costs. (5) Strategic complementarities are stronger among firms with fewer competitors, larger market shares, and broader customer bases. These findings suggest that strategic complementarities---a source of real rigidities---are sizable, state-dependent, asymmetric, and shaped by market structure. |
| Keywords: | Pass-through; price setting; strategic complementarities; state dependency; market structure |
| Date: | 2025–08–15 |
| URL: | https://d.repec.org/n?u=RePEc:imf:imfwpa:2025/164 |
| By: | Foros, Øystein (Dept. of Business and Management Science, Norwegian School of Economics and Business Administration); Kind, Hans Jarle (Dept. of Economics, Norwegian School of Economics and Business Administration); Shaffer, Greg (Simon Business School, University of Rochester) |
| Abstract: | This paper uses a Nash-in-Nash bargaining framework to consider why suppliers and retailers sometimes prefer to negotiate over linear contracts rather than over more sophisticated contracts such as two-part tariffs, and why, when they do negotiate over more sophisticated contracts, we often see negative fixed fees (slotting fees). We compare profits under the two forms of contracts and find under weak conditions that when negative fixed fees would arise in the case of two-part tari↵s, at least one side and often both sides will prefer this outcome to the outcome that would arise with linear contracts. In contrast, the opposite holds when positive fixed fees would arise in the case of two-part tariffs. Using linear demands, we demonstrate that retailers always favor negotiating over two-part tariffs when the fixed fees are negative, and prefer linear contracts when the fixed fees are positive. Suppliers generally share these preferences, unless they possess particularly strong bargaining power relative to retailers. Our findings have implications for retailer buyer power and are broadly consistent with stylized facts from the U.S. grocery industry. |
| Keywords: | Nash-in-Nash bargaining; Two-part tariffs; Linear contracts; Slotting fees; Retailer buyer power |
| JEL: | D04 L50 |
| Date: | 2025–08–17 |
| URL: | https://d.repec.org/n?u=RePEc:hhs:nhheco:2025_017 |
| By: | Wallenburg, Iris; Friebel, Rocco |
| JEL: | J1 |
| Date: | 2025–08–13 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:129134 |
| By: | Soheil Ghili; K. Sudhir; Nitish Jain; Ankur Garg |
| Abstract: | We build on theoretical results from the mechanism design literature to analyze empirical models of second-degree price discrimination (2PD). We show that for a random-coefficients discrete choice ("BLP") model to be suitable for studying 2PD, it must capture the covariance between two key random effects: (i) the "baseline" willingness to pay (affecting all product versions), and (ii) the perceived differentiation between versions. We then develop an experimental design that, among other features, identifies this covariance under common data constraints in 2PD environments. We implement this experiment in the field in collaboration with an international airline. Estimating the theoretically motivated empirical model on the experimental data, we demonstrate its applicability to 2PD decisions. We also show that test statistics from our design can enable qualitative inference on optimal 2PD policy even before estimating a demand model. Our methodology applies broadly across second-degree price discrimination settings. |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2507.13426 |
| By: | David Imhof; Emanuel W Viklund; Martin Huber |
| Abstract: | We propose a novel application of graph attention networks (GATs), a type of graph neural network enhanced with attention mechanisms, to develop a deep learning algorithm for detecting collusive behavior, leveraging predictive features suggested in prior research. We test our approach on a large dataset covering 13 markets across seven countries. Our results show that predictive models based on GATs, trained on a subset of the markets, can be effectively transferred to other markets, achieving accuracy rates between 80% and 90%, depending on the hyperparameter settings. The best-performing configuration, applied to eight markets from Switzerland and the Japanese region of Okinawa, yields an average accuracy of 91% for cross-market prediction. When extended to 12 markets, the method maintains a strong performance with an average accuracy of 84%, surpassing traditional ensemble approaches in machine learning. These results suggest that GAT-based detection methods offer a promising tool for competition authorities to screen markets for potential cartel activity. |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2507.12369 |
| By: | Francesco Amodio (McGill University); Emanuele Brancati (Sapienza University of Rome); Nicolás de Roux (Universidad de los Andes); Michele Di Maio (Sapienza University of Rome) |
| Abstract: | We measure firms’ wage-setting power in 16 Latin American and Caribbean countries. Exploiting variation in firms’ exposure to trade and exchange rates, we generate shocks to labor demand to trace out firm-level labor supply curves and quantify labor market power. We estimate an inverse labor supply elasticity of 0.82, implying that workers receive 55 cents per additional dollar produced. Wage-setting power is significantly higher among firms in countries with lower union density, limited collective bargaining, and no unemployment protection. This underscores the role of labor market institutions in shaping firms’ wagesetting power and the distribution of the gains from trade. |
| Keywords: | firms, labor market power, labor institutions |
| JEL: | J31 J50 O54 |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:col:000089:021499 |
| By: | Lindsey Raymond |
| Abstract: | While there is excitement about the potential for algorithms to optimize individual decision-making, changes in individual behavior will, almost inevitably, impact markets. Yet little is known about such effects. In this paper, I study how the availability of algorithmic prediction changes entry, allocation, and prices in the US single-family housing market, a key driver of household wealth. I identify a market-level natural experiment that generates variation in the cost of using algorithms to value houses: digitization, the transition from physical to digital housing records. I show that digitization leads to entry by investors using algorithms, but does not push out investors using human judgment. Instead, human investors shift toward houses that are difficult to predict algorithmically. Algorithmic investors predominantly purchase minority-owned homes, a segment of the market where humans may be biased. Digitization increases the average sale price of minority-owned homes by 5% and reduces racial disparities in home prices by 45%. Algorithmic investors, via competition, affect the prices paid by owner-occupiers and human investors for minority homes; such changes drive the majority of the reduction in racial disparities. The decrease in racial inequality underscores the potential for algorithms to mitigate human biases at the market level. |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2508.09513 |
| By: | Hideo Konishi (Boston College; National Chengchi University, Taiwan); Dimitar Simeonov (Bahçeşehir University) |
| Abstract: | In this paper, we formalize a market with a large number of competing production teams following Alchian and Demsetz (1974). We allow for wide-spread externalities which can affect players’ payoffs. These externalities include changes in market conditions and pollutions, and may generate a variety of equilibrium outcomes. There are finite types of atomless players, who can form team-firms with finite memberships using available technologies. Given an arbitrary set of feasible partnership contracts for each team type, we consider free entry equilibrium as our equilibrium concept—in a free entry equilibrium, no team type can attract its members from other teams by proposing any implementable partnership contract. Furthermore, in a free entry equilibrium, players of the same type may have different payoffs—unequal treatment of equals. We show that as long as each firm type’s implementable payoff set is compact and continuous in externality variables, there exists a free entry equilibrium. We provide several applications of our results. |
| Keywords: | competing teams, widespread externalities, unequal treatment of equals, free entry equilibrium, labor managed firms, coalition formation |
| JEL: | C71 C78 D2 D4 |
| Date: | 2025–08–21 |
| URL: | https://d.repec.org/n?u=RePEc:boc:bocoec:1095 |
| By: | Saeed Alaei; Shuchi Chawla; Zhiyi Huang; Ali Makhdoumi; Azarakhsh Malekian |
| Abstract: | We consider a mechanism design setting with a single item and a single buyer who is uncertain about the value of the item. Both the buyer and the seller have a common model for the buyer's value, but the buyer discovers her true value only upon receiving the item. Mechanisms in this setting can be interpreted as randomized refund mechanisms, which allocate the item at some price and then offer a (partial and/or randomized) refund to the buyer in exchange for the item if the buyer is unsatisfied with her purchase. Motivated by their practical importance, we study the design of optimal deterministic mechanisms in this setting. We characterize optimal mechanisms as virtual value maximizers for both continuous and discrete type settings. We then use this characterization, along with bounds on the menu size complexity, to develop efficient algorithms for finding optimal and near-optimal deterministic mechanisms. |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2507.04148 |
| By: | Voraprapa Nakavachara; Chanon Thongtai; Thanarat Chalidabhongse; Chanathip Pharino |
| Abstract: | This paper investigates whether climate-friendly food products command a price premium in consumer markets. Using product-level data from a supermarket in Sweden, we examine the relationship between front-of-package climate impact scores and retail prices, controlling for product size, nutritional content, and fixed effects. Contrary to the intuitive expectation of a positive green premium, we find no evidence that climate-friendly products are priced higher. In some product categories, products with better climate scores are in fact associated with lower prices, suggesting a negative premium, an outcome that gives rise to what we refer to as the green premium puzzle. We argue that market frictions such as competing consumer priorities, psychological distance from climate issues, and skepticism toward environmental labeling may suppress the price signals intended to reward sustainable consumption. These findings offer important insights for producers, retailers, and policymakers seeking to align climate goals with effective market incentives in the transition toward a more sustainable society. |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2507.10333 |
| By: | Serguey Braguinsky; Joonkyu Choi; Yuheng Ding; Karam Jo; Seula Kim |
| Abstract: | We provide evidence that mega firms have played an increasingly important role in shaping new technological trajectories in recent years. While the share of novel patents---defined as patents introducing new combinations of technological components---produced by mega firms declined until around 2000, it has rebounded sharply since then. Furthermore, we find that the technological impact and knowledge diffusion of novel patents by mega firms have grown relative to those by non-mega firms after 2001. We also explore potential drivers of this trend, presenting evidence that the rise in novel patenting by mega firms is tied to their disproportionate increase in cash holdings and the expansion of their technological scope. Our findings highlight an overlooked positive role of mega firms in the economywide innovation process. |
| Keywords: | Mega Firms; Innovation; Novel Patents; Knowledge Diffusion |
| JEL: | O31 O33 O34 L11 L25 |
| Date: | 2025–08–06 |
| URL: | https://d.repec.org/n?u=RePEc:fip:fedgfe:2025-60 |