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DOCUMENT DE TRAVAIL 1999-011 GIS- A E - fsaulavalca

Publié par :

Published by :

Publicación de la :Faculté des sciences de l"administration

Université Laval

Québec (Québec) Canada G1K 7P4

Tél. Ph. Tel. : (418) 656-3644

Fax : (418) 656-2624

Édition électronique :

Electronic publishing :

Edición electrónica :Céline Frenette

Vice-décanat à la recherche et au développement

Faculté des sciences de l"administration

Disponible sur Internet :

Available on Internet

Disponible por Internet :http ://www.fsa.ulaval.ca/rd rd@fsa.ulaval.ca

DOCUMENT DE TRAVAIL 1999-011

GIS-

BASED SIMULATION OF ACCESSIBILITY TO ENHANCE

HEDONIC MODELING AND PROPERTY VALUE APPRAISAL :

A

N APPLICATION TO THE QUEBEC CITY METROPOLITAN

AREA

Marius Thériault, François Des Rosiers,

Marie-Hélène Vandersmissen

Version originale :

Original manuscript :

Version original :ISBN - 2-89524-081-7

ISBN -

ISBN -

Série électronique mise à jour :

One-line publication updated :

Seria electrónica, puesta al dia 04-1999

GIS-based Simulation of Accessibility to Enhance Hedonic Modeling and Property Value Appraisal: An Application to the Quebec City Metropolitan Area

Marius Thériault

1 , François Des Rosiers 2 and Marie-Hélène Vandersmissen 3

1. Department of Geography, Planning and Research Center, Laval University, Québec, Canada, G1K 7P4

Phone: 418-656-2131 ext. 5899, Fax: 418-524-6701 e-mail: Marius.Theriault@ggr.ulaval.ca

2. Faculty of Business Administration, Planning and Research Center, Laval University, Québec, Canada, G1K 7P4

Phone: 418-656-2131 ext. 5012, e-mail: Francois.DesRosiers@fsa.ulaval.ca

3. Department of Planning, Planning and Research Center, Laval University, Québec, Canada, G1K 7P4

Phone: 418-656-2131 ext. 4251, e-mail: Marie-Helene.Vandersmissen@crad.ulaval.ca

Summary

This paper presents a simulation procedure that uses GIS technology for integrating accessibility to services and working places

in order to improve modeling of houses values. Most real estate models use simple functions of distance to CBD in order to

evaluate access to services and centrality. However, cities are complex systems. Secondary business centers appear. Shopping

malls are disseminated. And, daily services are often located in the neighborhoods. Therefore, measuring accessibility is far

more complex than evaluating a mere Euclidean distance to CBD. Using topological streets and roads network and origin-

destination surveys, TransCAD (transportation GIS software) simulates trips from each home to selected activity places. Using

streets and realistic speed values, it computes accessibility based on the shortest route length, the minimum traveling time or

some global cost index. The main purpose of this paper is to compare the effectiveness of these various accessibility

measurements to improve hedonic modeling of house values and urban dynamics understanding. Previous work indicates strong

effects of proximity to shopping centers, to schools, to highway exits and to working places on the surrounding houses values.

This paper improves hedonic modeling procedure with distance measurements that are compatible with human perception of

accessibility and are more sensitive to the local urban context. Distance to the nearest business and working places is measured

on the road network. This clearly enhances understanding of externalities and allows for a comprehensive evaluation of

neighborhood attractiveness. Application to housing market of the Quebec City Metropolitan Area (more than 2,400 cottages

sold from 1993 to 1997) illustrates the potential of this method to improve CAMA and urban studies.

Key Words GIS, Hedonic modeling, Accessibility, Traveling time, CAMA, Housing markets, Spatial analysis

1. Introduction : Context and Objective

This paper deals with the integration of proximity and accessibility measurements to hedonic modeling, in order to assess their effects on the value of residential properties. The hedonic approach aims at explaining property prices on the basis of their physical and neighborhood-related characteristics. The purpose is to evaluate the respective contribution of each attribute of the residential bundle in the market value (Can 1990 & 1993, Dubin 1998). The analytical procedure is essentially an application of the multiple regression analysis. Although hedonic models prove quite successful in highlighting market trends as well as providing indications about change in household preferences over time and space, previous research has shown that substantial portion of price variability remains unexplained (Anselin and Can 1986, Dubin and Sung 1987, Can 1993, Dubin

1998). Data gathering costs can be substantial, thereby-impeding

development of computer-assisted mass appraisal (CAMA) systems. Moreover, the appropriate neighborhood factors needed to improve hedonic models may change among places and market segments, making it difficult to integrate all significant factors. Finally, multicollinearity of model attributes, as well as structural heteroskedasticity and spatial autocorrelation among residuals is detrimental to the stability of regression coefficients (Dubin

1988, Anselin and Rey 1991, Can and Megbolugbe 1997, Basu

and Thibodeau 1998, Pace et al. 1998, Des Rosiers and Thériault

1999). These are issues that need substantial research efforts inorder to improve hedonic modeling procedures and CAMA

systems reliability. Geographic Information Systems (GIS) provide resources to enhance real estate analysis. This paper shows how GIS can improve location and accessibility variables, in comparison to the traditional Euclidean distance assumption. Previous applications had shown evidence of statistically significant relationships between residential sale prices and the geo- relational information provided by the GIS (Can 1992, Des Rosiers and Thériault 1992, Thrall 1993, Thrall and Marks

1993, Rodriguez et al. 1995). Moreover, integrating housing

market analysis in GIS means additional tools to analyze spatial dependence and model urban dynamics. Such a tool can relate properties to their immediate neighborhood depicted using topographical maps, aerial photographs, remote sensed imagery, transportation surveys, geo-marketing systems, etc.. GIS is developing rapidly and some extensions integrate spatial statistics methods (Anselin and Getis 1992, Griffith 1993, Zhang and Griffith 1993, Thériault and Des Rosiers 1995, Levine 1996). This provides an efficient framework to enhance market understanding by analyzing the spatial structure behind the model residuals. This aims at detecting additional neighborhood factors that must be considered to explain market variability. Therefore, GIS provides the market analyst with geo-statistical resources, like centrographic analysis, trend surface analysis, spatial pattern analysis and autocorrelation analysis (Odland 1988, Cressie 1993, Ord and Getis 1995, Tiefelsdorf and Boots 1997). Using them, one can interpolate GIS-based Simulation of Accessibility to Enhance Hedonic Modeling and Property Value Appraisal GIS & CAMA 1999 - URISA-IAAO, New Orleans, April 11-14, 1999

Thériault, Des Rosiers and Vandersmissen2

data or model residuals, using variography and Kriging techniques (Dubin 1992, Panatier 1996). All these methods greatly improve analysis and modeling of the geographical structure of housing markets. The next sections deal with the following topics. Section 2 presents operational definitions of accessibility and mobility. It explains how their measurement can improve the hedonic modeling strategy. Section 3 describes a procedure that estimates road distances, travel times and most important activity locations. It is using geo-relational GIS technology to combine a road network, service locations tables and origin-destination surveys. Section 4 shows an application to a specific housing market. This hedonic model uses data describing more than 2,400 transactionsquotesdbs_dbs2.pdfusesText_3