In: International Journal of Industrial Organization, 2019, vol. 65, p. 277-301
We combine machine learning techniques with statistical screens computed from the distribution of bids in tenders within the Swiss construction sector to predict collusion through bid-rigging cartels. We assess the out of sample performance of this approach and find it to correctly classify more than 84% of the total of bidding processes as collusive or non-collusive. We also discuss...
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In: Computational Statistics, 2014, vol. 29, no. 3-4, p. 407-430
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In: Statistics and Computing, 2012, vol. 22, no. 1, p. 219-235
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