Université de Fribourg

Machine learning with screens for detecting bid-rigging cartels

Huber, Martin ; Imhof, David

(Working Papers SES ; 494)

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 80% of the total of bidding processes as collusive or non-collusive. As the correct...

Université de Fribourg

Simple Statistical Screens to Detect Bid Rigging

Imhof, David

(Working Papers SES ; 484)

The paper applies simple statistical screens to a bid-rigging cartel in Switzerland, and shows how well the screens detect it by capturing the impact of collusion on the discrete distribution of the bids. In case of bid rigging, the support for the distribution of the bids decreases involving a lower variance, illustrated by the coefficient of variance and the kurtosis statistic. Furthermore,...

Université de Fribourg

Econometric tests to detect bid-rigging cartels: does it work?

Imhof, David

(Working Papers SES ; 483)

This paper tests how well the method proposed by Bajari and Ye (2003) performs to detect bidrigging cartels. In the case investigated in this paper, the bid-rigging cartel rigged all contracts during the collusive period, and all firms participated to the bid-rigging cartel. The two econometric tests constructed by Bajari and Ye (2003) produce a high number of false negative results: the tests do...

Université de Fribourg

Screening for bid-rigging - does it work?

Imhof, David ; Karagök, Yavuz ; Rutz, Samuel

(Working Papers SES ; 468)

This paper proposes a method to detect bid-rigging by applying mutually reinforcing screens to a road construction procurement data set from Switzerland in which no prior information about collusion was available. The screening method is particularly suited to deal with the problem of partial collusion, i.e. collusion which does not involve all firms and/or all contracts in a specific data set,...