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Effects of Neighborhood Choice on Housing Markets: a model based on the interaction between microsimulations and revealed/stated preference modeling

English title Effects of Neighborhood Choice on Housing Markets: a model based on the interaction between microsimulations and revealed/stated preference modeling
Applicant Maggi Rico
Number 116523
Funding scheme Interdisciplinary projects
Research institution Istituto Ricerche Economiche Università della Svizzera Italiana
Institution of higher education Università della Svizzera italiana - USI
Main discipline Economics
Start/End 01.05.2007 - 31.10.2010
Approved amount 297'750.00
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All Disciplines (2)

Discipline
Economics
Mathematics

Keywords (6)

Microsimulations; stated preference; housing markets; neighborhood; validation; calibration

Lay Summary (English)

Lead
Lay summary
The main goal of the overall project is to develop a new method to measure and forecast the effects on urbandevelopment, housing markets and quality of life combining a new microsimulation tool (Interaction Spaces, a newtype of mathematical model for complex systems developed by the Modeling and Applications of Complex SystemsLaboratory (Macs-Lab), University of Lugano) and integrating it with an RP-SP based residential choice model in arecursive way. The secondary objective consists in modeling neighborhood segregation processes and studyingsense of community in small urban areas.In order to develop the new model, an interdisciplinary approach between mathematics and economics andpsychology seems appropriate, because simulation models risk to be too idealized in terms of validation on existingreality, and economic stated choice models, even if embedded in a psychological frame, might remain too far fromrealistic calibration and are not able to produce future forecasts. The combination of both approaches in a new andrecursive model should attribute more relevance to both, introducing revealed as well as hypothetical behavioralparameters into simulations on the one hand, and enhancing stated preference designs integrating variable valuesextracted from simulations on the other.Concerning the secondary objective, it has to be noted that neighborhood does not refer only, as usual inEuropean applications to environmental quality, to infrastructure and public services, but to the psychological senseof community in the neighborhood and characteristics of the neighbors in a literal sense. This focus, more popular inUS applications, permits to study the impacts of immigration, increasingly relevant also in the reality of relativelysmall Swiss urban conglomerations, on the dynamics of spatial segregation processes. Though the scope is not toexplain the complexities of social segregation as such, but its spatial and economical impacts, it is essential tocomplement the study with a psychological module. This will permit to evaluate and enhance the relevance of theeconomic rationale behind the choice experiment.The first step will be the development of a model for housing market in the framework of IS, a new type ofmathematical model for complex systems developed by the Macs-Lab at the University of Lugano. This type ofmodel would enable to join the approach of microsimulations with more classical analytical approach typical ofEconophysics, obtaining a very detailed model for housing markets with the possibility to study its dynamics thanksto its sound mathematical properties. Using fuzzy modeling methods it is possible, in the framework of IS, torealistically describe agents’ decision processes of a multi-agents like system (MAS), including memory effects,long range spatial interactions, neighborhood effects on prices, etc. Moreover extensive state variables, typicallyused in IS, always verify suitable differential equations for the time dynamics, realizing in this way the abovementioned connection between MAS and analytical methods, and enabling to study a MA like system as acontinuous dynamical system. In this research project, we propose a stepwise approach to calibration and validationof our microsimulation model via RP and SP surveys. First we use the reliable hedonic prices and multinomialchoice models constructed from the RP survey in order to obtain an input “learning set” for the calibration andvalidation of the prices sector of the dynamical model. In this way the output prices of the microsimulation modelcan reach a level of validity comparable to the one of the hedonic method, which are well-known strongly reliable atthe time of data collection. Other validation methods (comparison between simulated and empirical frequencies ofevents and validation by means of experts’ opinion, see the enclosed Vancheri et al. 2006 II) will be used tocalibrate and validate all the parameters which are not included in the “prices sector” of the dynamical model. Atthis stage, future scenarios can be produced using the microsimulation model. A meaningful set of local and globalfuture urban configurations can be selected from these scenarios and used in the subsequent SP survey. It isimportant to point out that, unlike usual design of SP survey, we do not use here hypothetical and simple variationsof given situations. Indeed, fuzzy logic indicators used in the model can be employed to produce stronglycontextualized and meaningful descriptions of local and global urban configurations using natural language (virtualreality tools are also planned as a support to visualize spatial and land use related aspects). For example it is possibleto propose a situation which is not just the present one plus an added feature (e.g. a new shopping centre), but alsoall the probable consequences of this added feature. Moreover, these scenarios belong to a probable future of thesystem and hence extend in a relevant way the validity of the SP survey beyond the current time. It is possible tofocus on critical configurations far away from the present one, e.g. near to bifurcation points (in our approach it ispossible to investigate these aspects using random and ordinary differential equations, see the enclosed Vancheri etal. 2006, I). In the last stage, the results of the SP will be used to calibrate and validate the dynamical model at ahigher level of reliability. More precisely the SP extends the initial learning set to future critical situations and henceincreases the validity of the dynamical model. This use of the SP results is made possible by the use of fuzzy logicbased methods which model agents’ decisional behavior in terms of goals and constraints, and this makes possiblethe translation of SP results into the dynamical model.
Direct link to Lay Summary Last update: 21.02.2013

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