Guess who came to dinner

Gallo, Joseph C.; Craycraft, Joseph L.; Bush, Steven C.

doi:10.1007/bf02354216

Cited by 19 publications

(1 citation statement)

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“…All of the existing empirical studies in antitrust enforcement rely on samples of detected (or registered) and convicted cases. For an overview of all types of detected antitrust offenses in the US, see Edwards (1950); Posner (1970); Gallo et al (1985); Salop and White (1986); Gallo et al (1986Gallo et al ( , 1994Gallo et al ( , 2000; Lin et al (2000); Kovacic and Shapiro (2000); Ghosal and Gallo (2001); Posner (2001); Baker (2003), Ghosal and Stennek (2007), and Connor (2014). In analogy, see Carree et al (2010) and Russo et al (2010b) for the European Union.…”

Section: Literature Reviewmentioning

confidence: 99%

Simulating Collusion: Challenging Conventional Estimation Methods

Bellert,

Günster

2024

Preprint

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The empirical literature in industrial economics relies on hazard rate models to estimate the probability of death and survival as well as to explain the duration of collusion. Estimations are based on detected and convicted offenses. Detected cartels are, however, a non-random sample of their population of collusive activity. We question whether hazard rate and linear estimation methods derive consistent unbiased estimators explaining collusion. We simulate collusive behavior of industries with different number of firms based on three classical models of collusion, additionally varying four variables of antitrust enforcement. It is the first easily amenable and amendable simulation tool for collusion. The simulation provides a ground-truth data set of undetected and detected cartels; a population and its sample. Applying hazard rate and linear models on the sample fails to deliver consistent unbiased estimates for the population. Controlling for sample and feature selection on the population of all potential offenders does not improve prediction. The use of average treatment effects and average duration bias shows to quantify the magnitude of any bias well; a solution for future research relying on detected cartel cases. JEL Classification: C13 , C63 , D43 , 43 , L41 , L44

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