Beauty in the Eye of the HomeOwner : Aesthetic Zoning and Residential Property Values

This paper provides empirical evidence for one of the core justifications for architectural zoning: Shape homogeneity influences the value of a residential building. Drawing on large-scale shape and transaction data, this study first develops a data-driven measure of architectural similarity, condensing threedimensional shapes to univariate shape distributions. The algorithm-based similarity estimates are good predictors of human perceptions of shape similarity and are linked to property attributes and transaction prices. For the city of Rotterdam, a price premium of approximately 4 percent for row houses in very homogeneous ensembles is estimated. One of the eminent objectives of urban planning is the protection of present and future property values, which motivates the close regulation of not only the location and scope of new development, but also controlling the external appearance of new buildings. Exemplary for many other municipalities, the zoning ordinance for Eastchester, NY, aims to prevent “monotonous and unsightly uniformity of building development or unsightly structures of incongruous or inappropriate form that might tend to depress surrounding property values” (Town of Eastchester NY, 2000). Very explicitly, lawmakers and courts have been curtailing the owner's property rights, justifying this stark intervention with assumed welfare gains at the neighborhood and city level (Anderson, 1960; Regan, 1990; Rubin, 1975). The far reaching power granted to planning authorities warrants the question: Does the enforcement of architectural standards positively influence property values? A wealth of studies established solid evidence for tight land use regulations being associated with rising in property values and, simultaneously, declining levels of new construction (Glaeser and Ward, 2009; Ihlanfeldt, 2007; Koster et al., 2012; Mayer and Somerville, 2000; Quigley and Raphael, 2005). However, the extent to which the increase in prices is caused by land use regulation imposing supply constraints or by the planning process creating value directly is less understood. Empirical research on the price effect of land use policies is plagued by regulation being “astonishingly vague” (Glaeser and Ward, 2009). Architectural control is no exception to this and, in addition, the enforcement of vague rules is commonly delegated to architecture review boards making case by case decisions. For instance, the Dutch city of Rotterdam requires new 1 Similar regulations can be found throughout the US and also in the UK or continental Europe. Japan's zoning, in contrast, allows large variations in architectural design at lot level. construction to adhere to “high design standards”, to use “high quality materials” and to follow the “shape and appearance of surrounding buildings” (City of Rotterdam, 2016). This ambiguity leaves substantial leeway for interpretations by the review panels. As geographic and temporal variation in architectural regulations and the stringency of their application is challenging to quantify, the identification of economic effects of policies regarding architectural designs and levels of homogeneity between neighboring building remains difficult at the policy level. At the building-level, however, the frequently assumed effects of architectural design on the value of surrounding properties have been explored to some extent: Historic landmark buildings have been found to create positive externalities (Ahlfeldt and Maennig, 2010; Leichenko et al., 2001; Listokin et al., 1998). Similarly, dwellings designed by famous architects leads to other buildings in the vicinity being more highly-valued. For instance, homes within 50 m of a residential building by Frank Lloyd Wright in Oak Park, Illinois, enjoy a price premium of 8.5 percent (Ahlfeldt and Mastro, 2012). Inversely, buildings can also impair the value of surrounding buildings very directly, for instance by protecting or blocking a sought-after view. For commercial properties, buildings by star architects command higher rents and values (Fuerst et al., 2011; Vandell and Lane, 1989). At the neighborhood level, perceived beauty of the built environment is one of the main determinants of the resident's satisfaction, alongside economic factors, school quality, and the perceived opportunity of social interactions (Florida et al., 2009). This body of literature suggests that a building's architectural quality indeed creates value beyond its own boundaries. Less evidence emerged on the influence of architectural similarities within ensembles of buildings on sales values: For 19 century Boston, Moorhouse and Smith (1994) find that properties which look a little different from their neighbors sell for more. In a sample of rowhouses from Boston's South End, properties with facade styles different from other fronts close by carry a price premium. The observed premia for “sticking out” become smaller with each additional building in the proximity sharing the same architectural style. This study relies on relatively few observations from one neighborhood only (and from more than 150 years ago) rendering the representativeness of the findings not self-evident. So far, all studies on the economic value of architecture relied on on-site inspections by experts and the classifications of styles and shapes into a limited number of categories (as for instance in Asabere et al., 1989, or Moorhouse and Smith, 1994). Less palpable dimensions like the silhouette, massing, roof forms, proportions and angles or similarities to surrounding properties remain unrecorded and ignored. Within the constraints imposed by topography, climate, construction costs, urban planning, lot sizes and lot shapes, these form-related building attributes vary extensively. Individualistic developer preferences, architectural creativity and amendments during the life-time of a building are a source of constant diversity. 2 An unobstructed sea view will increase property prices by 15% in Singapore (Yu et al., 2007) while positive values for viewsheds on nature and historical buildings have also been documented for Kyoto (Yasumoto et al., 2011). At the same time, economies of scale during construction, architectural preferences for harmony, overall fashion trends and zoning induce similarities between buildings. This study is the first to estimate the effect of architectural homogeneity on observed sales prices using a large, city-wide dataset on the three-dimensional shapes. Using an automatic, algorithm-driven evaluation of similarity between buildings, it unlocks property-level data for all buildings in a city and also on the degree of architectural homogeneity between them. The full-city approach drastically increases the number of observations available for analysis compared to subsamples based on sales, mortgage originations or valuations for tax purposes. Furthermore, the direct context of neighboring buildings can be analyzed which is not always possible when relying on samples instead of the universe of structures. The remainder of the paper first refines a method to convert three-dimensional building shape data into a numerical representation that can be fed into empirical pricing equations. Then it verifies whether these quantitative representations of shape can help to explain recent transaction prices using property data from the Dutch city of Rotterdam. Lastly, the price effect of architectural similarity is identified and estimated, providing empirical evidence for the main justification of architectural control. Methodology The shape and the hedonic configuration of a building are inextricably tangled as “form follows function” (Sullivan, 1896). The function or use of a building determines its shape and, simultaneously, its value. The outer shell of a structure reveals a wealth of information about the place (as in Jensen and Cowen, 1999). A three-dimensional model not only captures the type and spaciousness of a dwelling, but also its location within the city and neighborhood. Trained observers might be able to estimate the year of construction from the architecture, the height of rooms from the location of windows and other element in the facade. Additional amenities like green spaces, garages or balconies are directly observable. Also, certain shapes might be perceived as more aesthetically pleasing than others and therefore carry a direct architectural premium. Shape data availability is not a limiting factor anymore. Advances in the interpretation of remotely sensed data has lead to a surge of large and spatially consistent data sets with detailed three-dimensional information at building level. New York, Paris, Singapore, Tokyo and many other cities can be explored digitally, while the municipalities of Berlin or Rotterdam openly share semantic city models. So far, these models have been put to use in a wide range of research areas, including urban planning (Ranzinger and Gleixner, 1997; Wu et al., 2010), disaster management (Kwan and Lee, 2005), law enforcement (Wolff and Asche, 2009), navigation (Rakkolainen and Vainio, 2001), facility management and building information models (Nagel et al., 2009), or emission and other environmental modeling (Nichol and Wong, 2005). The heterogeneity and multi-dimensionality of building shapes renders their classification a 3 3D city data for Berlin is available for download at http://www.businesslocationcenter. de/en/downloadportal and for Rotterdam at http://www.rotterdam. nl/rotterdam_3d. non-trivial challenge. Broad categories can describe roof forms, the 2D shape of the ground plates or overall dimensions. Still, classifications relying on a manageable number of categories cannot provide a finely grained view and the variation in shape within each of the classes remains high. In addition, even objective shape measures and large sample sizes do not fully differentiate the aesthetic side of architecture from its functional aspects. However,