Real Estate

Motivated by the recent National Association of Realtors (NAR) settlement, this note examines the effects of reduced real estate agent commissions on home prices, housing turnover, and consumer welfare. Using a calibrated dynamic structural search model of the housing market, we explore how lowering agent commissions might influence market equilibrium. Our analysis highlights the importance of accounting for the dynamic nature of the housing market, consumer heterogeneity, and general equilibrium effects when assessing these outcomes.

Non-informational cues, such as facial expressions, can significantly influence judgments and interpersonal impressions. While past research has explored how smiling affects business outcomes in offline or in-store contexts, relatively less is known about how smiling influences consumer choice in e-commerce settings even when there is no face-to-face interaction.

A rent guarantee insurance (RGI) policy makes a limited number of rent payments to the landlord on behalf of an insured tenant unable to pay rent due to a negative income or health expenditure shock. We introduce RGI in a rich quantitative equilibrium model of housing insecurity and show it increases welfare by improving risk sharing across idiosyncratic and aggregate states of the world, reducing the need for a large security deposits, and reducing homelessness which imposes large costs on society.

I propose a dynamic equilibrium model of the rental markets that endogenously gives rise to defaults on rents and evictions. In the model, eviction protections make it harder to evict delinquent renters, but higher default costs to landlords increase equilibrium rents. I quantify the model using micro data on evictions, rents, and homelessness. I find that stronger eviction protections exacerbate housing insecurity and lower welfare. The key empirical driver of this result is the persistent nature of risk underlying rent delinquencies.

Professional house price forecast data are consistent with a rational model where agents must learn about the parameters of the house price growth process and the underlying state of the housing market. Slow learning about the long-run mean generates overreaction to forecast revisions and a modest response of forecasts to lagged realizations. Heterogeneity in signals and priors about the long-run mean helps the model account for cross-sectional dispersion in forecasts. Introducing behavioral biases helps improve the model's predictions for short-horizon overreaction and dispersion.

ASC 842, which requires balance sheet recognition of right-of-use (ROU) lease assets, resulted in a large increase in reported assets since 2019, thus impairing the time-series consistency of metrics that use assets (e.g., asset turnover). This paper shows that ROU assets can be estimated quite precisely using lease disclosure. Adding the estimated ROU asset for pre-ASC 842 observations substantially improves the ability of operating assets to explain sales. It also increases the ability of growth in operating assets to predict sales growth and explain analysts’ revenue growth forecasts.

Rules are being drafted to guide compliance with a 2019 New York City law that requires most of about 50,000 buildings, many over 25,000 square feet, to cut their greenhouse gas emissions by 40 percent by the end of this decade and to achieve net-zero emissions by 2050.

Working from home resulted in a sharp contraction in office demand. We built a valuation model to find that the office stock lost about 45% in value. More for low-quality buildings and in cities with a larger IT sector and less for trophy buildings. We discuss the implications for mortgage lenders and the vitality of cities.