Abstract

This paper examines the effects of property age, neighborhood commercial density, and lot size on residential real estate sale prices per square foot in New York City. An extensive dataset of thousands of property transactions from 2022-2023 is analyzed using OLS regressions. Building age shows a counterintuitively positive relationship with price per square foot, suggesting buyers value older, likely historic, construction. In line with expectations, commercial density demonstrates a significantly positive impact on residential property values, evidencing amenity benefits of mixed-use development. However, larger buildings relative to land area are associated with lower prices per square foot, indicating preferences for less dense housing with more surrounding open space. These findings have implications for urban policymakers, planners, developers, and researchers. The complex drivers of housing prices in New York revealed by this study highlight the need for evidence-based decision-making to balance consumer preferences, housing affordability, and sustainable urban growth. Further avenues for research include geographic and temporal analysis to assess changing dynamics in this massive metropolitan real estate market. This paper makes an empirical contribution towards deeper understanding of the nuanced factors influencing property values and promoting informed policies for equitable and vibrant cities.

Data

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