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The Predictability of DOJ Cartel Fines
Connor, John M. - 2016
Justice has great latitude in recommending corporate cartel fines to the federal courts, and its recommendations are nearly … Antitrust Division of the DOJ on 124 corporate participants of hard-core global cartels. Our behavioral model provides the first … direct test of the optimal deterrence theory of antitrust crimes.Regressions are fitted to a sample of the corporations that …
Persistent link: https://www.econbiz.de/10012979998
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The Predictability of Global Cartel Fines
Miller, Douglas J. - 2010
case of cartel violations, both the United States and the EU have introduced guidelines for calculating fines that are … intended to make fining decisions more transparent and to deter cartel formation. The research summarized in this paper finds …-deterrence theory dictates. We do find rather large differences in temporal patterns between U.S. and EC fines: the former do not …
Persistent link: https://www.econbiz.de/10013143320
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Carbon prices forecasting in quantiles
Ren, Xiaohang; Duan, Kun; Tao, Lizhu; Shi, Yukun; Yan, Cheng - In: Energy economics 108 (2022), pp. 1-15
Persistent link: https://www.econbiz.de/10013202748
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Collusion by algorithm: the role of unobserved actions
Martin, Simon; Rasch, Alexander - 2022
We analyze the effects of better algorithmic demand forecasting on collusive profits. We show that the comparative statics crucially depend on the whether actions are observable. Thus, the optimal antitrust policy needs to take into account the institutional settings of the industry in question....
Persistent link: https://www.econbiz.de/10013093034
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Collusion by Algorithm : Does Better Demand Prediction Facilitate Coordination Between Sellers?
Miklós-Thal, Jeanine - 2018
We build a game-theoretic model to examine how better demand forecasting due to algorithms, machine learning and artificial intelligence affects the sustainability of collusion in an industry. We find that while better forecasting allows colluding firms to better tailor prices to demand...
Persistent link: https://www.econbiz.de/10012910026
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Collusion by algorithm : the role of unobserved actions
Martin, Simon; Rasch, Alexander - 2022
We analyze the effects of better algorithmic demand forecasting on collusive profits. We show that the comparative statics crucially depend on the whether actions are observable. Thus, the optimal antitrust policy needs to take into account the institutional settings of the industry in question....
Persistent link: https://www.econbiz.de/10012990230
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Collusive compensation schemes aided by algorithms
Martin, Simon; Schmal, W. Benedikt - 2021
observed in detected cartels. We show formally why these schemes are useful for dampening deviation incentives when colluding …
Persistent link: https://www.econbiz.de/10012704975
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Collusive compensation schemes aided by algorithms
Martin, Simon; Schmal, W. Benedikt - 2021
observed in detected cartels. We show formally why these schemes are useful for dampening deviation incentives when colluding …
Persistent link: https://www.econbiz.de/10012698813
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Collusion by algorithm : does better demand prediction facilitate coordination between sellers?
Miklós-Thal, Jeanine; Tucker, Catherine - In: Management science : journal of the Institute for … 65 (2019) 4, pp. 1552-1561
Persistent link: https://www.econbiz.de/10012022643
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Demand forecasting, signal precision, and collusion with hidden actions
Martin, Simon; Rasch, Alexander - In: International journal of industrial organization 92 (2024), pp. 1-22
Persistent link: https://www.econbiz.de/10014549730