Coordinated vs Efficient Prices : The Impact of Algorithmic Pricing on Multifamily Rental Markets

Algorithmic pricing can improve efficiency by helping firms set prices more responsive to changing market conditions. However, widespread adoption of the same algorithm could also lead to price coordination, resulting in elevated prices. In this paper, we examine the impact of algorithmic pricing on the U.S. multifamily rental housing market using hand-collected adoption decisions of property management companies merged with the data of market-rate multifamily apartments from 2005 to 2019. First, our findings suggest that algorithm adoption indeed helps building managers set more responsive prices: buildings with the software increase prices during booms and lower prices during busts, compared to non-adopters in the same market. Second, when compared across markets, we find markets with greater algorithm penetration also experienced higher rents and lower occupancy in the post-crisis period. Such empirical patterns are consistent with either price coordination through the algorithm or widespread pricing error among non-adopters. Lastly, we estimate a structural model of housing demand and perform a test of conduct to evaluate the "algorithmic coordination" hypothesis