Emergent Phenomena in Housing Markets

Emergent Phenomena in Housing Markets

Emergent Phenomena in Housing Markets . Lidia Diappi Editor Emergent Phenomena in Housing Markets Gentrification, Housing Search, Polarization Editor Prof. Lidia Diappi Politecnico di Milano Department of Architecture and Planning Milano Italy ISBN 978-3-7908-2863-4 ISBN 978-3-7908-2864-1 (eBook) DOI 10.1007/978-3-7908-2864-1 Springer Heidelberg New York Dordrecht London Library of Congress Control Number: 2012943937 # Springer-Verlag Berlin Heidelberg 2013 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. Exempted from this legal reservation are brief excerpts in connection with reviews or scholarly analysis or material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work. Duplication of this publication or parts thereof is permitted only under the provisions of the Copyright Law of the Publisher’s location, in its current version, and permission for use must always be obtained from Springer. Permissions for use may be obtained through RightsLink at the Copyright Clearance Center. Violations are liable to prosecution under the respective Copyright Law. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. While the advice and information in this book are believed to be true and accurate at the date of publication, neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or omissions that may be made. The publisher makes no warranty, express or implied, with respect to the material contained herein. Printed on acid-free paper Physica-Verlag is a brand of Springer Springer is part of Springer ScienceþBusiness Media (www.springer.com) Contents 1 Introduction ......................................... 1 Lidia Diappi Part 1 Modeling the Spatial Behavior of Agents 2 Employing Agents to Develop Integrated Urban Models: Numerical Results from Residential Mobility Experiments .............. 19 Oswald Devisch, Theo Arentze, Aloys Borgers, and Harry Timmermans 3 Modeling Housing Market Dynamics Using a Multi-agent Simulation of Participants’ Cognitive Behavior .............. 43 Maryam Esmaeili, Alberto Vancheri, and Paolo Giordano 4 Redevelopments and Gentrification: A MAS Model of the Urban Housing Market in Milan ............................... 85 Lidia Diappi and Paola Bolchi Part 2 Empirical Investigations 5 Between Friends and Strangers: Schelling-Like Residential Dynamics in a Haredi Neighborhood in Jerusalem ............ 103 Shlomit Flint, Itzhak Benenson, Nurit Alfasi, and Yefim Bakman 6 Gentrification Without Exclusion? A SOM Neural Network Investigation on the Isola District in Milan .................. 127 Lidia Diappi, Paola Bolchi, and Luca Gaeta 7 Urban Policy and Gentrification. A Critical Analysis Using the Case of Paris ...................................... 151 Anne Clerval and Antoine Fleury 8 Conclusions .......................................... 171 Lidia Diappi v . List of Figures Fig. 2.1 General structure of a decision table (Figure from Verhelst (1980))...................................................... 27 Fig. 2.2 Example of an activity diagram (Figure from Gooch (2000)) . 28 Fig. 2.3 Example of a decision tree; the square node represents a decision node and the circular node represents a nature node; U represents utility ................................................... 29 Fig. 2.4 Decision table of a student with preference-profile 2 ............. 31 Fig. 2.5 Activity diagram of unboundedly rational students in a stationary housing-market ........................................... 31 Fig. 2.6 Decision tree of an unboundedly rational student in a stationary housing-market; o represents a residence; U(v, c), U 0 (o0) and U represent the utilities the student expects to derive from living in, respectively, a residence belonging to a residence-class v and price-category c; the parental home o0; and the current residence ............................................ 32 Fig. 2.7 Activity diagram of unboundedly rational students in a non- stationary housing-market ........................................... 35 Fig. 2.8 Activity diagram of boundedly rational students in a non- stationary housing-market ........................................... 36 Fig. 2.9 Decision table of a student with preference-profile 2 ............. 37 Fig. 2.10 Decision tree of boundedly rational students in a non- stationary housing-market ........................................... 38 Fig. 2.11 Results on the level of single students; the life-course is indicated as a full line, the move-course as a dotted line. The life-course of an eventual partner is indicated in grey.The o-signs indicate moves within the same profile ................... 39 Fig. 3.1 stress-resistance hypothesis. The figure depicts the time- related behavioral decision-making process consisting of householder stress, resistance, and choice-decisions .............. 50 Fig. 3.2 Typical structure of a fuzzy logic system .......................... 54 Fig. 3.3 The fundamental steps of the market model proposed . 59 Fig. 3.4 Conceptual model of the stress-resistance model ................. 60 Fig. 3.5 The conceptual model of the proposed product selection mechanism ................................................. 63 vii viii List of Figures Fig. 3.6 Conceptual model of supply maker behavior .................... 64 Fig. 3.7 Negotiation protocol between two agents ............................ 66 Fig. 3.8 Comparison of Swiss populations in 2008 in different districts of Lugano produced by IRE and simulation ......................... 66 Fig. 3.9 Comparison of Italian population in 2008 in different districts of Lugano produced by IRE and simulation ......................... 76 Fig. 3.10 Comparison of Portuguese population in 2008 in different districts of Lugano produced by IRE and simulation ............... 77 Fig. 3.11 Comparison of Turkish population in 2008 in different districts of Lugano produced by IRE and simulation ............... 78 Fig. 4.1 The rent gap theory. Rent variation in an urban area (Reworking of Smith (1979), p. 544) ................................. 79 Fig. 4.2 The real estate market cycle (Muller€ 1995) .......................... 87 Fig. 4.3 Regression line between estimated data (cycle 120) and real data (2003, OSMI) ..................................................... 89 Fig. 4.4 (a, b) Comparison between real estate rents structure observed and estimated by the model (cycle 121) ............................. 93 Fig. 4.5 A projection of the real estate rents in year 2013, cycle 241 . 94 Fig. 4.6 The cyclicality of average rent ........................................ 94 Fig. 4.7 The urban mean rent trend with and without the effect of redeveloped .......................................................... 96 Fig. 4.8 The master plan and the eight urban renewal projects: (1)Quarto Oggiaro, (2) Rubattino 1 e 2, (3) Santa Giulia, (4) Bisceglie Lorenteggio, (5) Portello, (6)PompeoLeoni,(7)PiazzaleLodi, (8) Bicocca................................................................. 96 Fig. 4.9 (a) Simulation results after 100 cycles without interventions. (b) Simulation results after 100 cycles including redevelopment projects ................................................ 97 Fig. 4.10 Distribution of housing units in rent classes with and without the effect of the planned developments after100 cycles ............ 97 Fig. 5.1 Jerusalem, the expansion of the city’s borders; (a) population groups (b) Sanhedria and old city .................................... 108 Fig. 5.2 Sanhedria buildings and the coverage of Voronoi polygons constructed based of buildings’ centroids. Voronoi-neighbors of the selected building (Black) are shown in Gray ................. 109 Fig. 5.3 Population dynamics in Sanhedria in absolute numbers ............ 112 Fig. 5.4 Spatial distribution of Lithuanians, Hassidim, Sephardim, Foreign-Lithuanians, National-Religious and Secular in apartment buildings, Sanhedria 1983–2008 .......................... 114 Fig. 5.5 The dynamics of Haredim residential segregation in Sanhedria, according to Moran I index, during the period of 1982–2008 .............................................................. 115 Fig. 5.6 The probabilities to leave the apartment on the fractions of sects in the building ................................................. 116 List of Figures ix Fig. 5.7 The probabilities to replace friend on the fractions of sects in the building .......................................................... 118 Fig. 5.8 The probabilities to leave the apartment as dependent on the fractions of other sects in the building’s neighborhood ........ 118 Fig. 5.9 Significant dependencies of the probabilities to replace the family of the same sect on the fractions of each of the other sects in the building’s neighborhood ................................. 119 Fig. 5.10 Significant dependencies of

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