Presentation on theme: "Modelling the Impact of Accessibility to Services on House Prices: A Comparative Analysis of Two Methodological Approaches François Des Rosiers, Marius."— Presentation transcript:
Modelling the Impact of Accessibility to Services on House Prices: A Comparative Analysis of Two Methodological Approaches François Des Rosiers, Marius Thériault & Yan Kestens European Real Estate Society 10 th Annual Meeting, June 11-13, 2003 Research funded by
This paper is an attempt to bridge the gap between, on the one hand, the mobility behaviour of households and their perception of accessibility to urban amenities and, on the other hand, house price dynamics as captured through hedonic modelling It consists of an empirical test of the impact of accessibility on house prices, whereby hedonic modelling is applied to some 952 single-family houses sold in Quebec City between 1993 and 1996 Two accessibility measures are compared: the former measure is based on simulated travel times to nearest amenities aggregated through factor analysis (PCA) The latter rests on perceived accessibility indices obtained via a fuzzy logic approach applied to observed trips patterns derived from the 2001 QMA O-D survey Introduction
Our hypothesis is that different people having a heterogeneous perception of space, they will adjust their willingness to pay for additional centrality/accessibility when choosing their home location depending on their needs and preferences The main objective of this paper is to test whether perceptual indices of accessibility are actually internalized in housing prices Secondary objectives are: Testing for the marginal contribution to value of access to various amenities: work places, schools, shops, groceries, health care centres, restaurants, leisure places Testing for the differential impact of accessibility among types of individuals and households Testing for the way life cycle and income impact upon the perception of accessibility and is translated into house prices Hypothesis and objectives
Traditional urban models are currently based on the centrality concept (distance decay function) and on accessibility to the CBD (monocentric model) McMillen’s (2003 – Chicago): decades of urban sprawl in North American cities did not weaken the prominence of the centrality concept Impact of proximity and accessibility to services on property values: Guntermann and Colwell 1983, Colwell, Gujral and Coley 1985, Colwell 1990, Grieson and White 1989, Sirpal 1994, So et al. 1997, Smersh and Smith 2000, Des Rosiers et al. (1996, 2001 & 2003 – Quebec City) Not all authors though agree on the actual influence of accessibility upon house prices and residential mobility (McGreal et al – Belfast & Bordeaux) Accessibility and House Values (1)
Polycentric cities: mere Euclidean distances to the CBD falls short of integrating all relevant aspects of accessibility (Jackson 1979, Dubin and Sung 1987, Niedercorn and Ammari 1987, Hoch and Waddell 1993) Despite use of minimum travel time and walking distance (Bateman et al. 2001), the faulty specification of accessibility descriptors may explain rather poor performances Travel surveys, commuting patterns and accessibility to jobs and houses: Levinson (1996 – Washington, DC): suburbanization of jobs maintains stability in commuting durations despite rising congestion and increasing work and non-work trip making and length Helling ( Atlanta): Effect of residential car accessibility to jobs on the quantity and nature of travel by men and women - Accessibility do not affect everyone while gravity indices only provide partial information Srour et al. ( Dallas-Fort Worth): Apply both general and specific accessibility indices to the modelling of residential and commercial markets - While common accessibility measures do not perform that well, job accessibility indices impact positively on residential land values Accessibility and House Values (2)
Database: hedonic modelling applied to 952 single-family houses sold in Quebec City between 1993 and sale prices range from $ to $ (Can.$) High variance on prices: use of a multiplicative functional form (ln of sale price – ln SP) Three steps: SIT Model 1: Ln SP = f [Property Specifics, Inflation, Taxation] SITPCA Model 2: Ln SP = f [S, I, T, PCA of travel times to nearest amenities] SITPAI Model 3: Ln SP = f [S, I, T, PAI : Perceived Accessibility Indices] Phone survey among buyers revealed that accessibility to services, jobs, schools, highways and transit networks was an important criteria for choosing new neighbourhoods: SITPAIAge Model 3a : Ln SP = f [S, I, T, PAI * Buyer’s Age] SITPAI*Income Model 3b : Ln SP = f [S, I, T, PAI * Buyer’s Income] Database & Modelling Approach
Step 1: compute 15 travel times (car and walking) to the nearest local & regional amenities : primary & high schools, colleges, universities; regional, neighbourhood & local shopping centres; CBD Step 2: PCA - extract 2 principal components using Varimax rotation Factor 1 : access to nearest regional-level services (42% of variance) Factor 2 : access to nearest local-level services (34% of variance) Already used by Des Rosiers et al., 2000 – Quebec City Mutually independent factors help control multicollinearity Step 3: Model 2 - Factor scores are substituted for access attributes Factor Analysis - PCA ( Nearest Amenities )
where : A i : Raw suitability of residential location i (sum of suitable opportunities) S ij : Suitability index of travelling from residential location i to activity location j : Total number of potential activities at location j where : A i * : Accessibility index of residential location i relative to the most suitable place Modelling Perceptual Accessibility Model 3 : Accessibility indices were computed for significantly different types of persons and activities using
Perceived Accessibility to Restaurants C 50 : 5,3 min. C 90 : 12,6 min.
Analysis of Results (1) All models do perform well in spite of remaining spatial autocorrelation among residuals Model 2 performs better in all respects
Analysis of Results (2) … Size and Age coefficients are strengthened. Tax rate effect declines. This suggests structural spatial links among these variables and urban form. Model 1 : All coefficients highly significant and consistent with expectations. Prominence of age, size and taxation Model 2 : Factors 1 and 2 substantially improve performances. Most other coefficients unchanged, but… Model 3 : Journey-to-Work coefficients highly significant even when controlling for urban centrality. Perceptual accessibility indices provide a more comprehensive picture of accessibility – more related to people and less related to closest amenities.
Analysis of Results (3) Models 4, 9 and 10 : Accessibility to schools and health care facilities for families as well as to restaurants exerts strong influence on prices. Perceived accessibility indices overcome centrality.
Analysis of Results (4) Model 3a : People aged are willing to pay a substantial market premium to locate at a reasonable travel time from their work place. Model 3b : The higher the household income, the stronger the propensity to lessen work-trip duration: under an income constraint, households trade-off longer commuting trips for cheaper land.
The two sub-hypothesis of this research were:  Various types of persons experience different constraints and are not equally willing to travel in order to reach various kinds of activities, meaning that they have an heterogeneous perception of space  Households will adjust their willingness to pay for additional centrality/accessibility when choosing their home location depending on their needs and preferences less straightforward Both sub-hypotheses are supported by empirical results, suggesting the accessibility concept might be less straightforward than is usually considered in the literature behavioural approaches The physical, absolute concept of accessibility ought to be complemented by behavioural approaches integrating people wills and needs in their valuation of urban space novel tools Considering they are a paramount determinant of location choices and property values, accessibility/centrality issues deserve being further investigated using novel tools, including travel and activity surveys and modelling Conclusion & Research Agenda