Geographically Weighted Regression Models in Estimating Median Home Prices in Towns of Massachusetts Based on an Urban Sustainability Framework

Yaxiong Ma,Sucharita Gopal

doi:10.3390/su10041026

Abstract

Housing is a key component of urban sustainability. The objective of this study was to assess the significance of key spatial determinants of median home price in towns in Massachusetts that impact sustainable growth. Our analysis investigates the presence or absence of spatial non-stationarity in the relationship between sustainable growth, measured in terms of the relationship between home values and various parameters including the amount of unprotected forest land, residential land, unemployment, education, vehicle ownership, accessibility to commuter rail stations, school district performance, and senior population. We use the standard geographically weighted regression (GWR) and Mixed GWR models to analyze the effects of spatial non-stationarity. Mixed GWR performed better than GWR in terms of Akaike Information Criterion (AIC) values. Our findings highlight the nature and spatial extent of the non-stationary vs. stationary qualities of key environmental and social determinants of median home price. Understanding the key determinants of housing values, such as valuation of green spaces, public school performance metrics, and proximity to public transport, enable towns to use different strategies of sustainable urban planning, while understanding urban housing determinants—such as unemployment and senior population—can help modify urban sustainable housing policies.

Highlights

We first examine the spatio-temporal patterns of median home prices derived by comparing and validating the results of the ordinary least squares (OLS) and geographically weighted regression (GWR) models
Our second set of results show the application of MGWR to highlight the differences in the degree of spatial non-stationarity in the determinants of the median home price in towns of Massachusetts, while the third set of results describes the urban sustainability from the perspective of economic, social and ecological determinants
We proposed an urban sustainability framework centered on housing that could address issues involving economic, social and ecological dimensions

Summary

Introduction

More than 83 percent of the US population lives in cities, up thirty percent from 50 years ago. By 2050, the US urban population is projected to increase to more than 90 percent (of 423 million in 2050). Urbanization is transforming farmland, wetlands, forests, and other natural ecosystems into urban landscapes at an unprecedented rate resulting in urban sprawl. Urban landscape patterns and dynamics are the physical manifestation of complex interactions between environment, society, and economy [1,2,3,4]. Urban areas are highly relevant, if not central, to any discussion on sustainable development

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