Academic Evidence on the Causal Impact of Institutional Landlords on House Prices and Rents

Academic Evidence on the Causal Impact of Institutional Landlords on House Prices and Rents

A central challenge in the housing debate is establishing a rigorous, causal link between institutional single-family rental (SFR) purchases and housing costs. Because institutional investors naturally select into high-growth, desirable markets (selection bias) and their corporate structures are highly fragmented across hundreds of shell LLCs (measurement error), naive ordinary least squares (OLS) regressions fail to isolate their true impact.

Groundbreaking academic research by Caitlin Gorback (UT Austin McCombs), Franklin Qian (UNC Kenan-Flagler), and Zipei Zhu (UNC Kenan-Flagler) in their paper, "The Impact of Institutional Owners on Housing Markets" (June 2024 / updated late 2025), provides the most comprehensive causal identification to date. Their findings demonstrate that institutional single-family rental entry causes statistically significant, positive pressure on both local house prices and rents.¹

A Novel Causal Identification: The Shift-Share Instrument

To solve the endogeneity problem, Gorback, Qian, and Zhu construct a novel shift-share instrumental variable (IV) to predict institutional Long-Term Rental (LTR) market entry across U.S. census tracts from 2010 to 2022:

1. Cross-Sectional "Share" (Suitability Index): The authors exploit the pre-existing 1990 product mix of each census tract. LTR companies exhibit highly specific, revealed preferences for newer, mid-sized, 3-bedroom single-family homes, whereas traditional small landlords (SLLs) prefer smaller, older, multi-family units (2-4 units). By mapping the 1990 product mix and orthogonalizing it to socioeconomic and demographic characteristics, they construct a "Suitability Index" predicting where LTRs would naturally enter.
2. Temporal "Shift" (Property Management Costs): To isolate the timing of LTR expansion, the authors track national venture capital funding flowing into Online Property Management (OPM) software (e.g., AppFolio, RealPage) and national property management establishments (using a leave-one-out county strategy). The rise of OPM platforms dramatically lowered the cost of managing geographically dispersed, decentralized portfolios without on-site superintendents.

A placebo check of pre-trends (2000–2009) confirms no relationship between a tract's Suitability Index and pre-period house price changes, validating the instrument's exclusion restriction.

Causal Impacts on Prices and Rents

Using their shift-share IV in a changes-on-changes specification, the authors estimate the causal impact of LTR market share growth:

• House Prices: A 1-standard-deviation increase in instrumented LTR share growth (corresponding to a 0.26 percentage point annual increase in actual LTR share in the intensive margin sample) causes an additional annual house price growth of 1.64% to 2.11%.
• Rents: Using the Zillow Observed Rent Index (ZORI) from 2015 to 2022, the authors find that a 1-standard-deviation increase in LTR share growth (corresponding to a 0.40 percentage point annual increase in actual LTR share) causes an additional annual rent growth of 1.64% to 2.19%.

The authors note that naive OLS estimates are heavily biased. For prices, OLS showed a tiny positive impact (0.15pp HPI growth), but restricting the sample to LTR-active tracts showed selection bias (LTRs select into high-growth tracts). The 2SLS estimates are significantly larger, indicating that measurement error (the inability to trace all corporate shell LLCs to parent companies) and simultaneity created significant downward bias in OLS.

Reallocation and Professionalization Mechanisms

The authors identify two key structural reallocation mechanisms that drive these price and rent increases:

1. Landlord Professionalization (Small to Large): LTRs actively acquire properties from small landlords (SLLs). In tracts with the highest LTR concentration, LTRs buy 10 times more properties from small landlords than they sell to them. This "professionalization" of the rental stock exposes it to algorithmic pricing and dynamic repricing (via OPMs), putting upward pressure on rents.
2. Owner-to-Investor Reallocation: Owner-occupants sell to LTRs, narrowing the owner-occupied stock and pushing up prices of single-family homes, while expanding rental supply.
3. Locked-In Institutional Portfolios: In high-concentration tracts, once LTRs acquire properties, they tend to trade amongst themselves rather than sell back to owner-occupants or small landlords (83% of LTR sales are to other LTRs), keeping the properties permanently within the professionalized institutional rental stock.

A Balanced Academic Spectrum

While the Gorback, Qian, and Zhu paper establishes a clear causal link between LTR entry and rising housing costs, other recent research suggests a more nuanced national footprint. A November 2025 working paper from the Federal Reserve Bank of Philadelphia (Working Paper 25-37) by Marco Giacoletti, Rawley Heimer, Wenli Li, and Edison Yu, titled "Single-Family REITs and Local Housing Markets", concludes that on a broad national scale, institutional single-family REITs have had a limited impact on overall access to homeownership. This suggests that while localized, high-concentration tracts (such as specific Sun Belt neighborhoods) experience significant upward price and rent pressure, the aggregate national impact on homeownership rates remains constrained by the relatively small overall footprint of institutional players.