Robust Screens for Noncompetitive Bidding in Procurement Auctions

Chassang, Sylvain; Kawai, Kei; Nakabayashi, Jun; Ortner, Juan

doi:10.3982/ecta17155

Cited by 29 publications

(22 citation statements)

References 40 publications

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“…Differences are scaled by the winner's bid in each case. Chassang et al (2022) demonstrate that, under some assumptions on the auction environment, these differences should display discontinuities in the histogram near zero if there is collusion.…”

Section: D3 Implementation Of Local Labor Market Estimatorsmentioning

confidence: 83%

“…18 One potential concern is that, because firms face one another multiple times, they may collude to achieve bid revenues greater than those predicted by our first-price sealed-bid auction model. In Online Appendix Figure A.1, we apply the collusion test of Chassang et al (2022) to each of the 28 states in our data separately, finding no evidence of collusion in any state.…”

Section: Data Sources and Sample Selectionmentioning

confidence: 92%

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Imperfect Competition and Rents in Labor and Product Markets: The Case of the Construction Industry

et al. 2020

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The primary goal of our paper is to quantify the importance of imperfect competition in the U.S. construction industry by estimating the size of rents earned by American firms and workers.To obtain a comprehensive measure of the total rents and to understand its sources, we take into account that rents may arise both due to markdown of wages and markup of prices. Our analyses combine the universe of U.S. business and worker tax records with newly collected records from U.S. procurement auctions. We first examine how firms respond to a plausibly exogenous shift in product demand through a difference-in-differences design that compares first-time procurement auction winners to the firms that lose, both before and after the auction.Motivated and guided by these estimates, we next develop, identify, and estimate a model where construction firms compete with one another for projects in the product market and for workers in the labor market. The firms may participate both in the private market and in government projects, the latter of which are procured through first-price sealed-bid auctions. We find that American construction firms have significant wage-and price-setting power. This imperfect competition generates a considerable amount of rents, two-thirds of which is captured by the firms. Lastly, we use the estimated model to perform counterfactual analyses which reveal how increases in the market power of firms, in the product market or the labor market, would affect the outcomes and behavior of workers and firms in the construction industry.

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Section: D3 Implementation Of Local Labor Market Estimatorsmentioning

confidence: 83%

Section: Data Sources and Sample Selectionmentioning

confidence: 92%

Imperfect Competition and Rents in Labor and Product Markets: The Case of the Construction Industry

et al. 2020

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“…Relying on firm-specific covariates could impede a broad screening activity if firm-specific data are unavailable or if the time needed to collect them without raising the attention of potential cartel participants is lacking. Chassang et al (2022) show that winning bids tend to be isolated in terms of value when bidders collude. For analyzing the missing density of bids between the first and the secondlowest bids, they calculate the normalized margin.…”

Section: Introductionmentioning

confidence: 96%

“…Calculating screens for subgroups as in our approach is also considered in Conley and Decarolis (2016) and Chassang et al (2022). First, Conley and Decarolis (2016) investigate subgroups to detect cartels in collusive auctions in Italy, but in contrast to our method (which considers all possible subgroups in a tender), they exploit firmspecific covariates (such as, e.g., common owner, municipality, or country) to form subgroups.…”

Section: Introductionmentioning

confidence: 99%

A Machine Learning Approach for Flagging Incomplete Bid-Rigging Cartels

2022

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We propose a detection method for flagging bid-rigging cartels, particularly useful when cartels are incomplete. Our approach combines screens, i.e., statistics derived from the distribution of bids in a tender, with machine learning to predict the probability of collusion. As a methodological innovation, we calculate such screens for all possible subgroups of three or four bids within a tender and use summary statistics like the mean, median, maximum, and minimum of each screen as predictors in the machine learning algorithm. This approach tackles the issue that competitive bids in incomplete cartels distort the statistical signals produced by bid rigging and it outperforms previously suggested methods in applications to incomplete cartels based on empirical data from Switzerland.

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“…4 4 There is also a significant applied and empirical literature on the economics of detecting and understanding mechanics of collusion, especially in auctions. See Asker [2010] and Chassang, Kawai, Nakabayashi, and Ortner [2022] for some recent work, and Marshall and Marx [2012] for a textbook treatment. Collusion due to the While the model is stylized, it captures some essence of why automated price settings can lead to sustained markups that regulators can no longer ignore.…”

Section: Introductionmentioning

confidence: 99%

Pricing with algorithms

Lamba¹,

Zhuk²

2022

Preprint

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This paper studies Markov perfect equilibria in a repeated duopoly model where sellers choose algorithms. An algorithm is a mapping from the competitor's price to own price.Once set, algorithms respond quickly. Customers arrive randomly and so do opportunities to revise the algorithm. In the simple game with two possible prices, monopoly outcome is the unique equilibrium for standard functional forms of the profit function. More generally, with multiple prices, exercise of market power is the rule-in all equilibria, the expected payoff of both sellers is above the competitive outcome, and that of at least one seller is close to or above the monopoly outcome. Sustenance of such collusion seems outside the scope of standard antitrust laws for it does not involve any direct communication.

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Robust Screens for Noncompetitive Bidding in Procurement Auctions

Cited by 29 publications

References 40 publications

Imperfect Competition and Rents in Labor and Product Markets: The Case of the Construction Industry

Imperfect Competition and Rents in Labor and Product Markets: The Case of the Construction Industry

A Machine Learning Approach for Flagging Incomplete Bid-Rigging Cartels

Pricing with algorithms

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