Screen for collusive behavior: A machine learning approach
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References listed on IDEAS
- Carsten J. Crede, 2019. "A Structural Break Cartel Screen for Dating and Detecting Collusion," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 54(3), pages 543-574, May.
- Abrantes-Metz, Rosa M. & Froeb, Luke M. & Geweke, John & Taylor, Christopher T., 2006. "A variance screen for collusion," International Journal of Industrial Organization, Elsevier, vol. 24(3), pages 467-486, May.
- Stephanie Assad & Robert Clark & Daniel Ershov & Lei Xu, 2020.
"Algorithmic Pricing and Competition: Empirical Evidence from the German Retail Gasoline Market,"
CESifo Working Paper Series
8521, CESifo.
- Stephanie Assad & Robert Clark & Daniel Ershov & Lei Xu, 2020. "Algorithmic Pricing and Competition: Empirical Evidence from the German Retail Gasoline Market," Working Paper 1438, Economics Department, Queen's University.
- David P. Byrne & Nicolas de Roos, 2019. "Learning to Coordinate: A Study in Retail Gasoline," American Economic Review, American Economic Association, vol. 109(2), pages 591-619, February.
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More about this item
Keywords
Machine Learning; Cartel Screens; Fuel Retail Market;All these keywords.
JEL classification:
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- K21 - Law and Economics - - Regulation and Business Law - - - Antitrust Law
- L44 - Industrial Organization - - Antitrust Issues and Policies - - - Antitrust Policy and Public Enterprise, Nonprofit Institutions, and Professional Organizations
NEP fields
This paper has been announced in the following NEP Reports:- NEP-BIG-2024-04-08 (Big Data)
- NEP-CMP-2024-04-08 (Computational Economics)
- NEP-COM-2024-04-08 (Industrial Competition)
- NEP-ENE-2024-04-08 (Energy Economics)
- NEP-IND-2024-04-08 (Industrial Organization)
- NEP-LAW-2024-04-08 (Law and Economics)
- NEP-REG-2024-04-08 (Regulation)
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