A Machine Learning Approach for Flagging Incomplete Bid-rigging Cartels
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- Wallimann, Hannes & Imhof, David & Huber, Martin, 2020. "A Machine Learning Approach for Flagging Incomplete Bid-rigging Cartels," FSES Working Papers 513, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
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Cited by:
- Deschênes, Sarah & Dumas, Christelle & Lambert, Sylvie, 2020.
"Household resources and individual strategies,"
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- Sarah Deschênes & Christelle Dumas & Sylvie Lambert, 2020. "Household resources and individual strategies," PSE-Ecole d'économie de Paris (Postprint) hal-02959962, HAL.
- Deschênes, Sarah & Dumas, Christelle & Lambert, Sylvie, 2020. "Household Resources and Individual Strategies," FSES Working Papers 517, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
- Sarah Deschênes & Christelle Dumas & Sylvie Lambert, 2020. "Household Resources and Individual Strategies," Working Papers halshs-02563367, HAL.
- Sarah Deschênes & Christelle Dumas & Sylvie Lambert, 2020. "Household resources and individual strategies," Post-Print hal-02959962, HAL.
- Sarah Deschênes & Christelle Dumas & Sylvie Lambert, 2020. "Household Resources and Individual Strategies," PSE Working Papers halshs-02563367, HAL.
- Silveira, Douglas & Vasconcelos, Silvinha & Resende, Marcelo & Cajueiro, Daniel O., 2022.
"Won’t Get Fooled Again: A supervised machine learning approach for screening gasoline cartels,"
Energy Economics, Elsevier, vol. 105(C).
- Douglas Silveira & Silvinha Vasconcelos & Marcelo Resende & Daniel O. Cajueiro, 2021. "Won't Get Fooled Again: A Supervised Machine Learning Approach for Screening Gasoline Cartels," CESifo Working Paper Series 8835, CESifo.
- Imhof, David & Wallimann, Hannes, 2021. "Detecting bid-rigging coalitions in different countries and auction formats," International Review of Law and Economics, Elsevier, vol. 68(C).
- Wallimann, Hannes & Imhof, David & Huber, Martin, 2020.
"A Machine Learning Approach for Flagging Incomplete Bid-rigging Cartels,"
FSES Working Papers
513, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
- Hannes Wallimann & David Imhof & Martin Huber, 2020. "A Machine Learning Approach for Flagging Incomplete Bid-rigging Cartels," Papers 2004.05629, arXiv.org.
- David Imhof & Hannes Wallimann, 2021. "Detecting bid-rigging coalitions in different countries and auction formats," Papers 2105.00337, arXiv.org.
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More about this item
JEL classification:
- C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
- C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
- D40 - Microeconomics - - Market Structure, Pricing, and Design - - - General
- K40 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - General
NEP fields
This paper has been announced in the following NEP Reports:- NEP-BIG-2020-04-20 (Big Data)
- NEP-CMP-2020-04-20 (Computational Economics)
- NEP-IND-2020-04-20 (Industrial Organization)
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