Reference-Dependent Residential Location Choice Model within a Relocation Context

This paper presents a reference-dependent model for residential location choice. The key contribution of the model is its incorporation of reference dependence that explicitly recognizes the role of the status quo and captures asymmetric responses toward gains and losses in making location choice decisions. The study uses a retrospective residential search survey and a dwelling supply data set from the Toronto Real Estate Board in Ontario, Canada, to estimate the model at the elemental level of individual dwelling units. The study applies a mixed logit formulation that captures unobserved heterogeneity and avoids imposing independence of irrelevant alternatives restrictions on the choice probabilities. Several types of variables, including dwelling characteristics, land uses and other zonal attributes, accessibility measures, and household socio-demographics, are tested in the model. Although the current dwelling is assumed to be the reference point in framing evaluation of alternative dwellings, all gains and losses are measured by a comparison of current and prospective dwellings in the modeling framework. The results reveal that households prefer gains in the number of bedrooms, but they are more sensitive to the equal amounts of losses. A similar loss aversion attitude is observed for the percentage of open areas and unemployment rate. It is also found that decision makers are sensitive only to the losses for the level of service attributes. The reference-dependent model performs better than a conventional location choice model in terms of model fit and provides important behavioral insights.

[1]  A. Tversky,et al.  Prospect theory: an analysis of decision under risk — Source link , 2007 .

[2]  Steven R. Lerman Random Utility Models of Spatial Choice , 1985 .

[3]  K. Kockelman,et al.  Microsimulation of Residential Land Development and Household Location Choices , 2008 .

[4]  Joachim Scheiner,et al.  Housing mobility and travel behaviour: A process-oriented approach to spatial mobility: Evidence from a new research field in Germany , 2006 .

[5]  Kenneth Train,et al.  Customer-Specific Taste Parameters and Mixed Logit: Households' Choice of Electricity Supplier , 2000 .

[6]  E. Miller,et al.  Microbehavioural Location Choice Process: Estimation of a Random Parameter Model for Residential Mobility , 2007 .

[7]  John M. Quigley,et al.  Consumer choice of dwelling, neighborhood and public services☆ , 1985 .

[8]  Jessica Y. Guo,et al.  Addressing spatial complexities in residential location choice models , 2004 .

[9]  Bruce G. S. Hardie,et al.  Modeling Loss Aversion and Reference Dependence Effects on Brand Choice , 1993 .

[10]  Kay W. Axhausen,et al.  Locations, Commitments and Activity Spaces , 2004 .

[11]  H. Oppewal,et al.  Residential Choice Behaviour of Dual Earner Households: A Decompositional Joint Choice Model , 1992 .

[12]  Frank S. Koppelman,et al.  Representing the differences between female and male commute behavior in residential location choice models , 2001 .

[13]  A. Tversky,et al.  Prospect theory: analysis of decision under risk , 1979 .

[14]  Daniel Klapper,et al.  Another look at loss aversion in brand choice data: Can we characterize the loss averse consumer? , 2005 .

[15]  M. Ben-Akiva,et al.  Tradeoffs in residential location decisions: Transportation versus other factors , 1980 .

[16]  C. Bhat Simulation estimation of mixed discrete choice models using randomized and scrambled Halton sequences , 2003 .

[17]  David E. Bell,et al.  Disappointment in Decision Making Under Uncertainty , 1985, Oper. Res..

[18]  Chandra R. Bhat,et al.  A MIXED SPATIALLY CORRELATED LOGIT MODEL: FORMULATION AND APPLICATION TO RESIDENTIAL CHOICE MODELING , 2004 .

[19]  Daniel McFadden,et al.  Modelling the Choice of Residential Location , 1977 .

[20]  Eric J. Miller,et al.  Microsimulating Residential Mobility and Spatial Search Behavior: Estimation of Continuous-Time Hazard and Discrete-Time Panel Logit Models for Residential Mobility , 2008 .

[21]  S. Mehndiratta TIME-OF-DAY EFFECTS IN INTER-CITY BUSINESS TRAVEL. , 1996 .

[22]  David Genesove,et al.  Loss Aversion and Seller Behaviour: Evidence from the Housing Market , 2001 .

[23]  K. Train A Comparison of Hierarchical Bayes and Maximum Simulated Likelihood for Mixed Logit , 2001 .

[24]  Khandker M. Nurul Habib,et al.  Modeling Choice of Residential Location and Home Type:Recent Movers in Austin, Texas , 2008 .

[25]  Paul A. Ruud,et al.  Handbook of Econometrics: Classical Estimation Methods for LDV Models Using Simulation , 1993 .

[26]  A. Tversky,et al.  Loss Aversion in Riskless Choice: A Reference-Dependent Model , 1991 .

[27]  D.,et al.  Stated Preference Investigation of Influences on Attractiveness of Residential Locations , 2022 .

[28]  S. Rosenthal,et al.  Household Location and Race: Estimates of a Multinomial Logit Model , 1989 .

[29]  Chandra R. Bhat,et al.  A Comprehensive Analysis of Built Environment Characteristics on Household Residential Choice and Auto Ownership Levels , 2007 .

[30]  Terrance Odean,et al.  Are Investors Reluctant to Realize Their Losses? , 1996 .

[31]  Faruk Gul A Theory of Disappointment Aversion , 1991 .

[32]  M William Sermons,et al.  Influence of Race on Household Residential Utility , 2010 .

[33]  A. Young Prospect Theory: An Analysis of Decision Under Risk (Kahneman and Tversky, 1979) , 2011 .

[34]  Moshe Ben-Akiva,et al.  Integration of an Activity-based Model System and a Residential Location Model , 1998 .

[35]  Kenneth E. Train,et al.  Discrete Choice Methods with Simulation , 2016 .

[36]  D. Bell,et al.  Looking for Loss Aversion in Scanner Panel Data: The Confounding Effect of Price Response Heterogeneity , 2000 .

[37]  David A. Hensher,et al.  The Mixed Logit Model: the State of Practice and Warnings for the Unwary , 2001 .

[38]  Erel Avineri,et al.  Sensitivity to Uncertainty: Need for a Paradigm Shift , 2003 .

[39]  F. Porell Models of Intraurban Residential Relocation , 1982 .

[40]  Frans M. Dieleman,et al.  Modelling residential mobility; a review of recent trends in research , 2001 .

[41]  Ryuichi Kitamura,et al.  Reference Points in Commuter Departure Time Choice: A Prospect Theoretic Test of Alternative Decision Frames , 2004, J. Intell. Transp. Syst..

[42]  M.William Sermons,et al.  ASSESSING TRAVELER RESPONSIVENESS TO LAND AND LOCATION BASED ACCESSIBILITY AND MOBILITY SOLUTIONS , 2001 .

[43]  W A Clark,et al.  Comparing Cross-Sectional and Longitudinal Analyses of Residential Mobility and Migration , 1992, Environment & planning A.

[44]  Moshe Ben-Akiva,et al.  ANALYSIS OF A DYNAMIC RESIDENTIAL LOCATION CHOICE MODEL WITH TRANSACTION COSTS , 1986 .

[45]  M. Rabin,et al.  A Model of Reference-Dependent Preferences , 2006 .

[46]  M. Ben-Akiva,et al.  Endogeneity in Residential Location Choice Models , 2006 .

[47]  André de Palma,et al.  Discrete choice models with capacity constraints: an empirical analysis of the housing market of the greater Paris region , 2007 .

[48]  D. McFadden,et al.  MIXED MNL MODELS FOR DISCRETE RESPONSE , 2000 .

[49]  André de Palma,et al.  Equilibria and Information Provision in Risky Networks with Risk-Averse Drivers , 2006, Transp. Sci..

[50]  Yusufcan Masatlioglu,et al.  Rational choice with status quo bias , 2005, J. Econ. Theory.

[51]  Joseph Friedman,et al.  A Conditional Logit Model of the Role of Local Public Services in Residential Choice , 1981 .

[52]  Anna O. Pushkar Modelling household residential search processes, methodology and preliminary results of an original survey , 1998 .

[53]  K. Train,et al.  Mixed Logit with Repeated Choices: Households' Choices of Appliance Efficiency Level , 1998, Review of Economics and Statistics.

[54]  W. Greene,et al.  Interpreting Estimated Parameters and Measuring Individual Heterogeneity in Random Coefficient Models , 2003 .