An Instrumental Variables Approach to Testing Firm Conduct under a Bertrand-Nash Framework

TL;DR

This paper introduces a new testing method for firm conduct under Bertrand competition that compares two price regressions, performing well in detecting collusion and robust to model issues, aiding regulators and researchers.

Contribution

It develops a novel testing procedure based on non-nested model selection that simplifies detecting firm collusion without estimating the full demand-supply system.

Findings

The test performs comparably or better than existing methods in simulations.

The approach is robust to model misspecification and data limitations.

It provides practical guidelines for strengthening demand instruments in collusion detection.

Abstract

Understanding firm conduct is crucial for industrial organization and antitrust policy. In this article, we develop a testing procedure based on the Rivers and Vuong non-nested model selection framework. Unlike existing methods that require estimating the demand and supply system, our approach compares the model fit of two first-stage price regressions. Through an extensive Monte Carlo study, we demonstrate that our test performs comparably to, or outperforms, existing methods in detecting collusion across various collusive scenarios. The results are robust to model misspecification, alternative functional forms for instruments, and data limitations. By simplifying the diagnosis of firm behavior, our method offers researchers and regulators an efficient tool for assessing industry conduct under a Bertrand oligopoly framework. Additionally, our approach offers a practical guideline for enhancing the strength of BLP-style instruments in demand estimation: once collusion is detected, researchers are advised to incorporate the product characteristics of colluding partners into own-firm instruments while excluding them from other-firm instruments.