Breaking Down the Monolith: Using Network Methods to Identify and Analyze Chicago’s Largest Landlords

<p dir="ltr">More than a third of households in the US and more than half in Chicago, IL are renter-occupied. In recent decades, ownership of residential rental properties has become increasingly concentrated in the hands of large, sophisticated landlords. Large landlords are obscure in two senses. First, it is difficult to determine which actors own which properties. Second, the causes of landlord behavior (e.g., investment decisions and property management practices) are often complex and difficult to ascertain. </p><p dir="ltr">In this thesis, I address both types of large landlord obscurity in Chicago, IL. First, I comprehensively identify the largest landlords and the scopes of their portfolios by linking large, administrative datasets in a network model. I identify 48 landlords who each own 1,000 or more units in MFR buildings (as of 2024). These 48 landlords collectively own 17.3% of MFR units in Chicago. </p><p dir="ltr">After identifying these actors, I describe them, especially in terms of their business strategies and histories. Quantitatively, I analyze readily observable characteristics of parcels in their portfolios. Qualitatively, I draw from a variety of non-academic sources to conduct case studies on three landlords. To analyze business strategies, I draw from various academic sources, and I apply the popular real estate industry framework of “core,” “value-add,” and “opportunistic” investing. I demonstrate that Chicago’s large landlords are highly diverse, varying greatly in terms of firm age; the spatial distributions of their holdings; the racial and class characteristics of renters in neighborhoods where they invest; and sizes and values of owned buildings. With my case studies, I offer evidence of all three investment strategies. </p><p dir="ltr">With this thesis, I contribute to a young but growing body of work that uses computational methods and administrative data to identify which landlords own which properties. Further, I demonstrate that Chicago’s large landlords are not monolithic. I argue that understanding landlord behaviors requires a nuanced and multi-factorial framework. By addressing both types of obscurity, this thesis bridges two largely separate bodies of literature. Such an approach allows for a strong understanding of a city’s residential rental market dynamics. </p><p dir="ltr">Supplementary Materials for this thesis can be found at https://doi.org/10.25417/uic.29169677.v1.</p>