The New Age of Collusion? An Empirical Study into Airbnb's Pricing Dynamics and Market Behavior

TL;DR

This paper empirically examines how Airbnb's new algorithmic pricing tool affects host pricing strategies and market behavior, highlighting potential risks of tacit collusion in digital marketplaces.

Contribution

It introduces a causal analysis of the impact of Airbnb's pricing tool on host behavior using RDD and PSM methods, providing insights into digital market regulation.

Findings

Pricing strategies are significantly influenced by the algorithmic tool.

Potential signs of market dynamics approaching collusion.

Insights into balancing market efficiency and anti-competitive risks.

Abstract

This study investigates the implications of algorithmic pricing in digital marketplaces, focusing on Airbnb's pricing dynamics. With the advent of Airbnb's new pricing tool, this research explores how digital tools influence hosts' pricing strategies, potentially leading to market dynamics that straddle the line between efficiency and collusion. Utilizing a Regression Discontinuity Design (RDD) and Propensity Score Matching (PSM), the study examines the causal effects of the pricing tool on pricing behavior among hosts with different operational strategies. The findings aim to provide insights into the evolving landscape of digital economies, examining the balance between competitive market practices and the risk of tacit collusion facilitated by algorithmic pricing. This study contributes to the discourse on digital market regulation, offering a nuanced understanding of the implications of AI-driven tools in market dynamics and antitrust analysis.