Dissertations, Theses, and Capstone Projects

Date of Degree

6-2024

Document Type

Dissertation

Degree Name

Ph.D.

Program

Economics

Advisor

Paul Krugman

Committee Members

Miles Corak

Wim Vijverbeg

Ellora Derenoncourt

Subject Categories

Economics

Keywords

Monopoly, Housing Rental Market, NYC

Abstract

This dissertation consists of three chapters on market power in housing rental markets. It introduces the concept of dynamic monopoly power in housing rental markets, develops methods to estimate that form of market power, and uses its analytical lense over the New York City (NYC) housing rental market.

In the first chapter, I formulate a search model in which market frictions give landlords rent-setting (dynamic monopoly) power. This model incorporates search frictions in the spirit of Manning’s (2003) monopsonistic labor market framework. In this setting, the demand faced by individual landlords (i.e., residual demand) results from an equilibrium between tenants’ inflow and outflow to a landlord’s housing units. Frictions determine how sensitive these flows are to rent variation: it is more challenging for tenants to relocate when frictions are high. Consequently, frictions result in a downward-sloping residual demand, implying landlords hold dynamic monopoly power and face a trade-off between rent and turnover. This dynamic monopoly framework yields two measures of landlord’s market power: the residual demand elasticity and the markup share. I show that the residual demand elasticity, reflecting how turnover varies with rent, can be derived from the rent elasticities of both move-in and move-out. Secondly, I show that the markup share, quantifying the markups landlords can charge over marginal costs, is the Lerner’s index when landlords do not discount the future and is, thus, a function of the residual demand elasticity. Finally, I discuss how rent controls and constrained supply affect the market equilibrium.

In the second chapter, I use newly scraped data from New York City Craigslist’s postings to analyse move-ins. I exploit rent variation at the unit level based on whether the unit is advertised as rent-stabilized or classified as an apartment versus a condo. These institutional settings introduce unit-specific rent variation: Rent-stabilized units have administratively set rents, while condo owners are subject to building-specific condo association’s bylaws, leading to idiosyncratic rent variations. Using several survival analysis models, I find that a 1% increase in rent results in a 0.9% decrease in the move-in rate, which aligns with this dissertation’s theoretical prediction that landlords with higher rents face more challenges recruiting new tenants. Furthermore, according to the dynamic monopoly model introduced, this finding implies a residual demand elasticity of -1.9 and a markup share of 55%. For robustness, I compare these findings with results from an alternative empirical strategy. In this alternative approach, I employ a double-machine learning (DML) method outlined in Chernozhukov et al. (2018) and used in a labor market power context in Dube et al. (2020). To ascertain causality, I use natural language processing (NLP) tools to cull a vast array of covariates from the textual content of each posting. The core assumption is that leveraging a large set of covariates can minimize the omitted variable bias when estimating the move-in elasticity. The results, obtained using random forests, suggest that a 1% rent hike curtails the move-in rate by 0.8%, leading to a residual demand elasticity of -1.5. Both methods converge on a consistent estimate for the residual demand elasticity, approximately -2, which underscores the robustness of the results.

In the third chapter, I turn to move-outs data. I apply the methods developed in Chapter 1 to estimate the move-out elasticity and the residual demand elasticity using data from the American Housing Survey (AHS) for two distinct periods in New York City, Jersey City, and Newark: 2001-2013 and 2015-2021. I exploit unit-level exogenous rent variation resulting from whether the unit is rent-stabilized and whether it is publicly owned. Like rent-stabilized units, publicly owned units have rents set administratively, pegged to the lesser of 30% of household income or the ”fair market rent” as determined by the U.S. Department of Housing and Urban Development. As in the previous setting, the identifying assumption is that, conditional on the controls, unobserved factors influencing the move-out rate are presumed uncorrelated with these instruments. I apply falsification tests to address potential validity concerns, as in the approach with the Craigslist data. This analysis reveals that a 1% rent hike increases the move-out rate by 1.1% for 2001-2013 and 2.3% for 2015-2021. These results align with this paper’s theoretical prediction that landlords with higher rents face more challenges retaining tenants. Based on the dynamic monopoly model introduced, these results suggest residual demand elasticities of -2.2 for 2001-2013 and -4.5 for 2015-2021 and markup shares of 45% and 22%, respectively.

Economics students worldwide have traditionally been taught that housing rental markets epitomize perfect competition, where rent levels fundamentally result from the supply and demand interaction, leading to a perfectly horizontal demand curve faced by individual landlords. This perspective suggests no room for Pareto-improving market interventions, with rent controls inevitably resulting in shortages (Krugman and Wells (2021), Mankiw (2016)). Contrary to this conventional model, the empirical evidence presented in Chapters 2 and 3 of this dissertation reveals that individual landlords in NYC face a downward-sloping demand curve. Chapter 1 introduces an alternative framework that aligns with these findings, proposing that market power, alongside supply and demand, plays a fundamental role in defining rent prices. Consequently, housing policy debates around the world should focus not only on supply and demand factors but also on the reduction of market frictions, the distribution of market power and surplus, and on non-market alternatives to the allocation of rental housing.

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