nep-com New Economics Papers
on Industrial Competition
Issue of 2021‒11‒22
fourteen papers chosen by
Russell Pittman
United States Department of Justice

  1. Regulating big tech: From competition policy to sector regulation? By Budzinski, Oliver; Mendelsohn, Juliane
  2. Price effects of horizontal mergers: A retrospective on retrospectives By Stöhr, Annika
  3. Algorithmic and human collusion By Werner, Tobias
  4. Analysis of Competition Policies between U.S. and EU in the Era of Inter-Industry Convergence By Kang, Gusang; Jang, Yungshin; Oh, Taehyun; Rim, Jeewoon
  5. Organizational Structure and Pricing: Evidence from a Large U.S. Airline By Ali Hortacsu; Olivia R. Natan; Hayden Parsley; Timothy Schwieg; Kevin R. Williams
  6. Measuring Oligopsony Market Power in Kazakh Grain-Processing Industry: Converging Evidence from Two Structural Approaches By Perekhozhuk, Oleksandr; Chezhia, Giorgi; Glauben, Thomas
  7. Towards efficient information sharing in network markets By Bertin Martens; Geoffrey Parker; Georgios Petropoulos; Marshall Van Alstyne
  8. Digitalisation of Production: Industrial Additive Manufacturing and its Implications for Competition and Social Welfare By Julian Schwierzy
  9. Incorporating Search and Sales Information in Demand Estimation By Ali Hortacsu; Olivia R. Natan; Hayden Parsley; Timothy Schwieg; Kevin R. Williams
  10. How Does Market Power Affect Fire-Sale Externalities? By Thomas M. Eisenbach; Gregory Phelan
  11. Negotiating Networks in Oligopoly Markets for Price-Sensitive Products By Naman Shukla; Kartik Yellepeddi
  12. Moment Inequalities and Partial Identification in Industrial Organization By Brendan Kline; Ariel Pakes; Elie Tamer
  13. Taxes, corporate takeovers, and step transactions By Kazuki Onji; Roger H. Gordon
  14. The Economics of Medical Procedure Innovation By David Dranove; Craig Garthwaite; Christopher Heard; Bingxiao Wu

  1. By: Budzinski, Oliver; Mendelsohn, Juliane
    Keywords: big tech,digital economy,digital ecosystems,GAFAM,competition policy,antitrust,Digital Markets Act (DMA),sector-specific regulation,law and economics
    JEL: K21 K23 K24 L40 L50 L81 L86
    Date: 2021
  2. By: Stöhr, Annika
    Abstract: In this comprehensive review of ex-post merger studies price effects of horizontal transactions are evaluated. By combining and further analyzing the results of 52 retrospective studies on 82 mergers or merger-like transactions it can be shown that the industry alone is no strong indication for the direction of price-related merger effects. However, the "size" or "importance" of a transaction as well as market concentration pre-merger and change in concentration due to the transaction seem to have an impact on post-transaction price development.
    Keywords: Antitrust,Merger Control,Industrial Economics,Retrospective Studies,Ex-Post Studies,Competition Law Enforcement
    JEL: D49 K21 L13 L40
    Date: 2021
  3. By: Werner, Tobias
    Abstract: As self-learning pricing algorithms become popular, there are growing concerns among academics and regulators that algorithms could learn to collude tacitly on non-competitive prices and thereby harm competition. I study popular reinforcement learning algorithms and show that they develop collusive behavior in a simulated market environment. To derive a counterfactual that resembles traditional tacit collusion, I conduct market experiments with human participants in the same environment. Across different treatments, I vary the market size and the number of firms that use a self-learned pricing algorithm. I provide evidence that oligopoly markets can become more collusive if algorithms make pricing decisions instead of humans. In two-firm markets, market prices are weakly increasing in the number of algorithms in the market. In three-firm markets, algorithms weaken competition if most firms use an algorithm and human sellers are inexperienced.
    Keywords: Artificial Intelligence,Collusion,Experiment,Human-Machine Interaction
    JEL: C90 D83 L13 L41
    Date: 2021
    Abstract: In the era of inter-industry convergence, abuses of substantial market power by large digital platforms such as Google, Apple, Facebook, and Amazon, and their increasing number of acquisitions towards small- and medium-sized tech-firms suspicious of eliminating potential competitors are recent representative issues in the ICT sector. Alternative competition policies have been discussed to effectively deal with those firms' anti-competitive behaviors in a changing environment of competition such as a digital platform economy instead of traditional policies. In this regard, we examine the U.S. and EU competition policy responses to ICT firms' anti-competitive behaviors in order to provide policy implications to our competition authority. According to our case studies, the U.S. and EU competition and legal authorities consider characteristics of the digital platform economy when they conclude whether firm behaviors are anti-competitive. Furthermore, we find that Facebook's acquisition of WhatsApp leads to a tipping effect and harms market competition. Given these results, we suggest that our competition authority has to consider the balance between innovation and competition when they implement competition policies in the era of inter-industry convergence.
    Keywords: U.S.; EU; convergence; competition; ICT
    Date: 2021–04–15
  5. By: Ali Hortacsu (University of Chicago and NBER); Olivia R. Natan (University of California, Berkeley); Hayden Parsley (University of Texas, Austin); Timothy Schwieg (University of Chicago, Booth); Kevin R. Williams (Cowles Foundation, Yale University)
    Abstract: We study how organizational boundaries affect pricing decisions using comprehensive data from a large U.S. airline. We document that the ï¬ rm’s advanced pricing algorithm, utilizing inputs from different organizational teams, is subject to multiple biases. To quantify the impacts of these biases, we estimate a structural demand model using sales and search data. We recover the demand curves the ï¬ rm believes it faces using forecasting data. In counterfactuals, we show that correcting biases introduced by organizational teams individually have little impact on market outcomes, but coordinating organizational outcomes leads to higher prices/revenues and increased deadweight loss in the markets studied.
    Keywords: Pricing Frictions, Organizational Inertia, Dynamic Pricing, Revenue Management, Behavioral IO
    JEL: C11 C53 D22 D42 L10 L93
    Date: 2021–11
  6. By: Perekhozhuk, Oleksandr; Chezhia, Giorgi; Glauben, Thomas
    Keywords: Marketing, Crop Production/Industries
    Date: 2021–08
  7. By: Bertin Martens; Geoffrey Parker; Georgios Petropoulos; Marshall Van Alstyne
    Abstract: Our paper has benefitted from inspiring discussions with Erik Brynjolfsson, Luis Cabral, Rebecca Christie, Maria Demertzis, Erika Douglas, Nestor Duch-Brown, Justus Haucap, Jan Krämer , Maciej Sobolewski, Sebastian Steffen, Tommaso Valletti, Reinhilde Veugelers, Guntram Wolff as well as participants at Ascola 2021, Yale University’s Big Tech and Antitrust Conference 2020, OECD Competition Committee Hearing Dec. 2020, Bruegel, Digital Markets Competition Forum at Copenhagen Business School 16 June 2021, and the...
    Date: 2021–11
  8. By: Julian Schwierzy (Technical University of Munich)
    Abstract: The production flexibility of digital factories has the potential to revolutionise traditional manufacturing (TM) and thereby unlock a paradigm shift in production. In particular, the role of additive manufacturing (AM) technologies is gaining increased attention. Most experts consider AM as a complement to traditional manufacturing technologies. In this paper, I examine how the adoption of AM changes competition and how the coexistence with TM affects social welfare in the long-run. The results of my game-theoretical model indicate a decline in the number of companies with TM and an increase in market concentration. I show that the effect of AM adoption on prices and welfare depends on the cost structure of AM technologies. Unless the cost of AM is below a certain cut-off, its adoption is associated with a rise in prices and a decline in social welfare. The coexistence of both technologies in the same product market is therefore not necessarily beneficial for society. Based on these findings, I discuss policy implications for the stimulation of the digital transformation in the manufacturing industry. I argue that marginal cost reducing policy measures lead to a higher welfare effect than fixed cost reducing programmes.
    Keywords: Digital factories, Technology adoption, Market structure, Social welfare, Product differentiation, Digitalisation, Industrial Additive Manufacturing
    JEL: L11 L22 L23 O33
    Date: 2021–11
  9. By: Ali Hortacsu (University of Chicago and NBER); Olivia R. Natan (University of California, Berkeley); Hayden Parsley (University of Texas, Austin); Timothy Schwieg (University of Chicago, Booth); Kevin R. Williams (Cowles Foundation, Yale University)
    Abstract: We propose an approach to modeling and estimating discrete choice demand that allows for a large number of zero sale observations, rich unobserved heterogeneity, and endogenous prices. We do so by modeling small market sizes through Poisson arrivals. Each of these arriving consumers then solves a standard discrete choice problem. We present a Bayesian IV estimation approach that addresses sampling error in product shares and scales well to rich data environments. The data requirements are traditional market-level data and measures of consumer search intensity. After presenting simulation studies, we consider an empirical application of air travel demand where product-level sales are sparse. We ï¬ nd considerable variation in demand over time. Periods of peak demand feature both larger market sizes and consumers with higher willingness to pay. This ampliï¬ es cyclicality. However, observed frequent price and capacity adjustments offset some of this compounding effect.
    Keywords: Discrete Choice Modeling, Demand Estimation, Zeros, Bayesian Methods, Cyclical Demand, Airline Markets
    JEL: C10 C11 C13 C18 L93
    Date: 2021–11
  10. By: Thomas M. Eisenbach; Gregory Phelan
    Abstract: An important role of capital and liquidity regulations for financial institutions is to counteract inefficiencies associated with “fire-sale externalities,” such as the tendency of institutions to lever up and hold illiquid assets to the extent that their collective actions increase financial vulnerabilities. However, theoretical models that study such externalities commonly assume perfect competition among financial institutions, in spite of high (and increasing) financial sector concentration. In this post, which is based on our forthcoming article, we consider instead how the effects of fire-sale externalities change when financial institutions have market power.
    Keywords: financial institution; fire sale; concentration; market power
    JEL: G1 G2 E2
    Date: 2021–11–10
  11. By: Naman Shukla; Kartik Yellepeddi
    Abstract: We present a novel framework to learn functions that estimate decisions of sellers and buyers simultaneously in an oligopoly market for a price-sensitive product. In this setting, the aim of the seller network is to come up with a price for a given context such that the expected revenue is maximized by considering the buyer's satisfaction as well. On the other hand, the aim of the buyer network is to assign probability of purchase to the offered price to mimic the real world buyers' responses while also showing price sensitivity through its action. In other words, rejecting the unnecessarily high priced products. Similar to generative adversarial networks, this framework corresponds to a minimax two-player game. In our experiments with simulated and real-world transaction data, we compared our framework with the baseline model and demonstrated its potential through proposed evaluation metrics.
    Date: 2021–10
  12. By: Brendan Kline; Ariel Pakes; Elie Tamer
    Abstract: We review approaches to identification and inference on models in Industrial Organization with partial identification and/or moment inequalities. Often, such approaches are intentionally built directly on assumptions of optimizing behavior that are credible in Industrial Organization settings, while avoiding the use of strong modeling and measurement assumptions that may not be warranted. The result is an identified set for the object of interest, reflecting what the econometrician can learn from the data and assumptions. The chapter formally defines identification, reviews the assumptions underlying the identification argument, and provides examples of their use in Industrial Organization settings. We then discuss the corresponding statistical inference problem paying particular attention to practical implementation issues.
    JEL: C18 L22 L25
    Date: 2021–10
  13. By: Kazuki Onji (Graduate School of Economics, Osaka University); Roger H. Gordon
    Abstract: Taxes affect the size of a corporate takeover market in theory; the extant empirical studies from the US data offer limited such evidence. We consider Japan after 2001, which offers an alternative setting in which a tax system implicitly subsidizes mergers that follow a particular sequence of steps ("step transactions"). We construct a novel dataset on step transactions from a list of takeover deals from 1996 through 2013 and examine their utilization rates before and after Japan's tax reform of 2001. We find a statistically and economically significant discontinuity across the two regimes. We also examine tax payments using a panel dataset of firms from 1997 through 2013 and find a strong association between unexplained falls in tax payments and step transactions. The Japanese tax system provided subsidies to marginal as well as infra-marginal mergers among domestic corporations: we estimate tax expenditure to be \172.3 billion.
    Keywords: Tax Avoidance, M&A, Corporate Restructuring
    JEL: H25 H26 G34 H32
    Date: 2021–11
  14. By: David Dranove; Craig Garthwaite; Christopher Heard; Bingxiao Wu
    Abstract: This paper explores the economic incentives for medical procedure innovation. Using a proprietary dataset on billing code applications for emerging medical procedures, we highlight two mechanisms that could hinder innovation. First, the administrative hurdle of securing permanent, reimbursable billing codes substantially delays innovation diffusion. We find that Medicare utilization of innovative procedures increases nearly nine-fold after the billing codes are promoted to permanent (reimbursable) from provisional (non-reimbursable). However, only 29 percent of the provisional codes are promoted within the five-year probation period. Second, medical procedures lack intellectual property rights, especially those without patented devices. When appropriability is limited, specialty medical societies lead the applications for billing codes. We indicate that the ad hoc process for securing billing codes for procedure innovations creates uncertainty about both the development process and the allocation and enforceability of property rights. This stands in stark contrast to the more deliberate regulatory oversight for pharmaceutical innovations.
    JEL: I0 I1 O3
    Date: 2021–10

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