Machine Learning, Architectural Styles and Property Values

Thies Lindenthal,Erik B. Johnson

doi:10.1007/s11146-021-09845-1

Thies Lindenthal, Erik B. Johnson

Open Access

https://doi.org/10.1007/s11146-021-09845-1

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Abstract

AbstractThis paper couples a traditional hedonic model with architectural style classifications from human experts and machine learning (ML) enabled classifiers to estimate sales price premia over architectural styles, both at the building and the neighborhood-level. We find statistically and economically significant price differences for houses from distinct architectural styles across an array of specifications and modeling assumptions. Comparisons between classifications from ML models and human experts illustrate the conditions under which ML classifiers may perform at least as reliable as human experts in mass appraisal models. Hedonic estimates illustrate that the impact of architectural style on price is attenuated by properties with less well-defined styles and we find no evidence for differential price effects ofRevivalorContemporaryarchitecture for new construction.

Highlights

In this paper, we introduce a new data collection technique that allows us to rigorously test the notion that households have strong preferences over architectural styles
Our results indicate that 1) there is evidence for sales price premia associated with houses from a variety of architectural styles, 2) hedonic estimates from high confidence machine learning (ML) enabled architectural image classifications are similar
Proximate neighbor styles have an impact on sales price, with Contemporary neighborhoods clearly preferred to Georgian, Early Victorian, and Postwar

Summary

Introduction

We introduce a new data collection technique that allows us to rigorously test the notion that households have strong preferences over architectural styles. The policy perspective is best illustrated by Britain’s Building Better, Building Beautiful Commission, which advises the government on design choices for homes and neighborhoods. It lists as one of its primary aims as “To make the planning system work in support of better design and style, not against it.” (The Economist, 2018) and boldly claims that matching the style of new housing to aggregate neighborhood preferences should overcome otherwise prevailing objections of incumbent households to new construction (ibid.)

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