Evaluation of urban scenarios using bid-rents of spatial interaction models as hedonic price estimators: an application to the Terceira Island, Azores

Abstract

This paper aims to present and test a methodology capable of determining the impact of urban scenarios and policies through the use of calibrated bid-rents of a spatial interaction model (SIM) as hedonic price estimators of the real estate houses. This approach responds to the increasing requirement of decision support systems to assess complex effects of urban policies because through linking the bid-rents with hedonic prices, it is possible to connect the quantity estimates of the spatial interaction models with the value estimates of the hedonic price approach. The combined methodology is applied to Terceira Island to assess the spatial and economic impact of the decrease in activity of Lajes Military Airfield on employment and on the real estate value of the island. The SIM distributes employment and population by the 31 zones of Terceira Island in the Azores given the distances between zones, the basic employment per zone, the average distances for commuting and shopping and the space available for urban activities. The model’s friction parameters are iteratively calibrated to secure that estimated average commuting and shopping distances are equal to those observed in reality; bid-rents are also calibrated to guarantee that the demand for space in each zone does not overcomes the available sspace for urban activities per zone. The SIM is coded and integrated in MATLAB 2013a. Afterward, a hedonic price regression is estimated to explain house prices in relation to the calibrated bid-rents and house typologies. The effect of the Lajes Military Airfield drawdown is estimated by the SIM, which evaluates the impacts on employment and population, and a hedonic price regression is subsequently performed with the new SIM bid-rents,to appraise the new real estate value. Results show that the Lajes Military Airfield reduction of 750 basic employment will result not only in a decrease of 1552 total employments and 3502 of the 56,437 residents of the island but also in a loss of 55 million € in real estate value. The method has proved its usefulness and effectiveness for predicting the impacts of exogenous shocks in complex urban systems.