MR POTATOHEAD: Real Estate Market Edition — Development of a common description template for agent-based residential real estate market models
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Keywords

agent-based modeling
real-estate markets
design pattern
model replication
reuseable building blocks

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Parker, D. C., Ida, C., Detotto, C. ., Filatova, T., Ge, J., Huang, Y., Innocenti, E., Magliocca, N., Polhill, J. G., Prunetti, D., & Valaei Sharif, S. (2026). MR POTATOHEAD: Real Estate Market Edition — Development of a common description template for agent-based residential real estate market models. Socio-Environmental Systems Modelling, 8, 18913. https://doi.org/10.18174/sesmo.18913

Abstract

In recent years, a wide range of agent-based real-estate market models (ABM-REMMs) have been developed to incorporate actor and environmental heterogeneity and feedbacks between scales, features not possible in traditional real-estate market models. Despite close communication and collaboration between scholars, independent research groups have developed customized model codes, often in different programming languages. To synthesize this knowledge, we present a new meta-model template “MR POTATOHEAD: Real Estate Market Edition” (MP-REME), developed collaboratively by the authors, to describe and compare six independently developed ABM-REMMs. We demonstrate that the six models are special cases of a generalized meta-model, which is suitable for a wide range of agent-based exploration of real-estate market dynamics. The MP-REME templates can serve as a design pattern to catalyze development of a community ABM-REMM code base, facilitating faster model development, model transparency and replicability, and model comparison. Residential real estate (land and housing) markets impact a wide variety of critical socio-ecological outcomes at local, national, and international scales, and scientifically robust and transparent real-estate market models are needed to explore the impacts of these markets on socio-ecological outcomes. Given the range of differences between models, development of such a standard model is critical to increase confidence in the application of ABM-REMMs to policy analysis of issues such as urban flooding, carbon sequestration, heat island mitigation, and biodiversity preservation.

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References

Aalbers, M. (2017). The financialization of housing: A political economy approach (First issued in paperback). Routledge.

Almagor, J., Benenson, I., & Alfasi, N. (2018). Assessing innovation: Dynamics of high-rise development in an Israeli city. Environment and Planning B: Urban Analytics and City Science, 45(2), 253–274. https://doi.org/10.1177/0265813516671311

Almagor, J., Benenson, I., & Czamanski, D. (2018). The evolution of the land development industry: An agent-based simulation model. In Trends in Spatial Analysis and Modelling (pp. 93–120). Springer.

Anas, A., Arnott, R., & Small, K. A. (1998). Urban Spatial Structure. Journal of Economic Literature, 36(3), 1426–1464.

August, M. (2022). The financialization of housing in Canada: A summary report for the Office of the Federal Housing Advocate. Canadian Human Rights Commission = Commission canadienne des droits de la personne.

August, M., & St-Hilaire, C. (2025). Financialization, housing rents and affordability in Toronto. Environment and Planning A: Economy and Space, 57(5), 517–535. https://doi.org/10.1177/0308518X251328129

Axtell, R. L., & Farmer, J. D. (2025). Agent-based modeling in economics and finance: Past, present, and future. Journal of Economic Literature, 63(1), 197–287.

Baptista, R., Hinterschweiger, M., Low, K., & Uluc, A. (2016). Macroprudential Policy in an Agent-Based Model of the UK Housing Market. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.2850414

Barton, C. M., Ames, D., Chen, M., Frank, K., Jagers, H. R. A., Lee, A., Reis, S., & Swantek, L. (2022). Making modeling and software FAIR. Environmental Modelling & Software, 156, 105496. https://doi.org/10.1016/j.envsoft.2022.105496

Barton, C. M., Lee, A., Janssen, M. A., Van Der Leeuw, S., Tucker, G. E., Porter, C., Greenberg, J., Swantek, L., Frank, K., Chen, M., & Jagers, H. R. A. (2022). How to make models more useful. Proceedings of the National Academy of Sciences, 119(35), e2202112119. https://doi.org/10.1073/pnas.2202112119

Berger, U., Bell, A., Barton, C. M., Chappin, E., Dreßler, G., Filatova, T., Fronville, T., Lee, A., Loon, E. van, Lorscheid, I., Meyer, M., Müller, B., Piou, C., Radchuk, V., Roxburgh, N., Schüler, L., Troost, C., Wijermans, N., Williams, T. G., … Grimm, V. (2024). Towards reusable building blocks for agent-based modelling and theory development. Environmental Modelling & Software, 175, 106003. https://doi.org/10.1016/j.envsoft.2024.106003

Borsos, A., Carro, A., Glielmo, A., Hinterschweiger, M., Kaszowska-Mojsa, J., & Uluc, A. (2025). Agent-based modeling at central banks: Recent developments and new challenges (Documentos Ocasionales No. 2503; Documentos Ocasionales, p. 2503). Banco de España. https://doi.org/10.53479/39238

Caprioli, C., Bottero, M., & De Angelis, E. (2023). Combining an Agent-Based Model, Hedonic Pricing and Multicriteria Analysis to Model Green Gentrification Dynamics. Computers, Environment and Urban Systems, 102, 101955. https://doi.org/10.1016/j.compenvurbsys.2023.101955

Carro, A. (2023). Taming the housing roller coaster: The impact of macroprudential policy on the house price cycle. Journal of Economic Dynamics and Control, 156, 104753. https://doi.org/10.1016/j.jedc.2023.104753

Carro, A., Hinterschweiger, M., Uluc, A., & Farmer, J. D. (2023). Heterogeneous effects and spillovers of macroprudential policy in an agent-based model of the UK housing market. Industrial and Corporate Change, 32(2), 386–432. https://doi.org/10.1093/icc/dtac030

Cortellino, F., & Jasmin-Tucci, L. (2023). Housing Market Insight Canadian Metropolitan Areas (Housing Market Insight). Canada Mortgage and Housing Corporation (CMHC). https://www.cmhc-schl.gc.ca/professionals/housing-markets-data-and-research/market-reports/housing-market/housing-market-insight

Crooks, A., Heppenstall, A., Malleson, N., & Manley, E. (2021). Agent-Based Modeling and the City: A Gallery of Applications. In W. Shi, M. F. Goodchild, M. Batty, M.-P. Kwan, & A. Zhang (Eds.), Urban Informatics (pp. 885–910). Springer. https://doi.org/10.1007/978-981-15-8983-6_46

Dai, E., Ma, L., Yang, W., Wang, Y., Yin, L., & Tong, M. (2020). Agent-Based Model of Land System: Theory, Application and Modelling Framework. Journal of Geographical Sciences, 30(10), 1555–1570. https://doi.org/10.1007/s11442-020-1799-3

de Koning, K., & Filatova, T. (2020). Repetitive floods intensify outmigration and climate gentrification in coastal cities. Environmental Research Letters, 15(3), 034008. https://doi.org/10.1088/1748-9326/ab6668

de Koning, K., Filatova, T., Need, A., & Bin, O. (2019). Avoiding or mitigating flooding: Bottom-up drivers of urban resilience to climate change in the USA. Global Environmental Change, 59, 101981. https://doi.org/10.1016/j.gloenvcha.2019.101981

Diappi, L., & Bolchi, P. (2008). Smith’s rent gap theory and local real estate dynamics: A multi-agent model. Computers, Environment and Urban Systems, 32(1), 6–18. https://doi.org/10.1016/j.compenvurbsys.2006.11.003

Doucet, B. (2021). The ‘hidden’ sides of transit-induced gentrification and displacement along Waterloo Region’s LRT corridor. Geoforum, 125, 37–46. https://doi.org/10.1016/j.geoforum.2021.06.013

Dragićević, S., & Hatch, K. (2018). Urban geosimulations with the Logic Scoring of Preference method for agent-based decision-making. Habitat International, 72, 3–17.

Egerer, M., Haase, D., McPhearson, T., Frantzeskaki, N., Andersson, E., Nagendra, H., & Ossola, A. (2021). Urban Change as an Untapped Opportunity for Climate Adaptation. Npj Urban Sustainability, 1(1). https://doi.org/10.1038/s42949-021-00024-y

Erlingsson, E. J., Teglio, A., Cincotti, S., Stefansson, H., Sturluson, J. T., & Raberto, M. (2014). Housing Market Bubbles and Business Cycles in an Agent-Based Credit Economy. Economics, 8(1). https://doi.org/10.5018/economics-ejournal.ja.2014-8

Farha, L., & Schwan, K. (2021). The human right to housing in the age of financialization. In M. F. Davis, M. Kjaerum, & A. Lyons (Eds.), Research Handbook on Human Rights and Poverty (pp. 385–400). Edward Elgar Publishing. https://doi.org/10.4337/9781788977517.00038

Farmer, J. D., & Foley, D. (2009). The economy needs agent-based modelling. Nature, 460(7256), 685–686. https://doi.org/10.1038/460685a

Filatova, T. (2015). Empirical agent-based land market: Integrating adaptive economic behavior in urban land-use models. Computers, Environment and Urban Systems, 54, 397–413. https://doi.org/10.1016/j.compenvurbsys.2014.06.007

Filatova, T., Parker, D., & Veen, A. van der. (2009). Agent-based urban land markets: Agent’s pricing behaviour, land prices and urban land use change. Journal of artificial societies and social simulation, 12(1,3), 1–30.

Filatova, T., Verbeek, L., Warnier, M., Ghorbani, A., Nikolic, I., Grimm, V., Berger, U., Barton, M., Bell, A., Lee, A., Wagenblast, T., & Magliocca, N. R. (2025). AGENTBLOCKS: A community platform for sharing, comparing, and improving reusable building blocks for (agent-based) models (SSRN Scholarly Paper No. 5219387). https://doi.org/10.2139/ssrn.5219387

Filatova, T., Verburg, P. H., Parker, D. C., & Stannard, C. A. (2013). Spatial agent-based models for socio-ecological systems: Challenges and prospects. Environmental Modelling and Software, 45, 1–7. https://doi.org/10.1016/j.envsoft.2013.03.017

Gamal, Y., Elsenbroich, C., Gilbert, N., Heppenstall, A., & Zia, K. (2024). A Behavioural Agent-Based Model for Housing Markets: Impact of Financial Shocks in the UK. Journal of Artificial Societies and Social Simulation, 27(4), 5. https://doi.org/10.18564/jasss.5518

Gatti, D. D., Gaffeo, E., & Gallegati, M. (2010). Complex agent-based macroeconomics: A manifesto for a new paradigm. Journal of Economic Interaction and Coordination, 5(2), 111–135. https://doi.org/10.1007/s11403-010-0064-8

Ge, J. (2017). Endogenous rise and collapse of housing price. Computers, Environment and Urban Systems, 62, 182–198. https://doi.org/10.1016/j.compenvurbsys.2016.11.005

Ge, J., Polhill, J. G., Craig, T., & Liu, N. (2018). From oil wealth to green growth-An empirical agent-based model of recession, migration and sustainable urban transition. Environmental Modelling & Software, 107, 119–140.

Geanakoplos, J., Axtell, R., Farmer, D. J., Howitt, P., Conlee, B., Goldstein, J., Hendrey, M., Palmer, N. M., & Yang, C.-Y. (2012). Getting at Systemic Risk via an Agent-Based Model of the Housing Market. American Economic Review, 102(3), 53–58. https://doi.org/10.1257/aer.102.3.53

Glavatskiy, K. S., Prokopenko, M., Carro, A., Ormerod, P., & Harre, M. (2021). Explaining herding and volatility in the cyclical price dynamics of urban housing markets using a large-scale agent-based model. SN Business & Economics, 1(6), 76.

Grimm, V., Berger, U., Bastiansen, F., Eliassen, S., Ginot, V., Giske, J., Goss-Custard, J., Grand, T., Heinz, S. K., Huse, G., Huth, A., Jepsen, J. U., Jørgensen, C., Mooij, W. M., Müller, B., Pe’er, G., Piou, C., Railsback, S. F., Robbins, A. M., … DeAngelis, D. L. (2006). A standard protocol for describing individual-based and agent-based models. Ecological Modelling, 198(1–2), 115–126. https://doi.org/10.1016/j.ecolmodel.2006.04.023

Grimm, V., Railsback, S. F., Vincenot, C. E., Berger, U., Gallagher, C., DeAngelis, D. L., Edmonds, B., Ge, J., Giske, J., Groeneveld, J., Johnston, A. S. A., Milles, A., Nabe-Nielsen, J., Polhill, J. G., Radchuk, V., Rohwäder, M.-S., Stillman, R. A., Thiele, J. C., & Ayllón, D. (2020). The ODD Protocol for Describing Agent-Based and Other Simulation Models: A Second Update to Improve Clarity, Replication, and Structural Realism. Journal of Artificial Societies and Social Simulation, 23(2), 7. https://doi.org/10.18564/jasss.4259

Gunderson, M., & Cukier, W. (2024). Immigrants and house prices: Myths and realities. Equality, Diversity and Inclusion: An International Journal. https://doi.org/10.1108/EDI-05-2024-0196

Huang, Q., Parker, D. C., Filatova, T., & Sun, S. (2014). A review of urban residential choice models using agent-based modeling. Environment and Planning B: Planning and Design, 41(4), 661–689.

Huang, Q., Parker, D. C., Sun, S., & Filatova, T. (2013). Effects of agent heterogeneity in the presence of a land-market: A systematic test in an agent-based laboratory. Computers, Environment and Urban Systems, 41, 188–203.

Innocenti, E., Detotto, C., Idda, C., Parker, D. C., & Prunetti, D. (2020). An iterative process to construct an interdisciplinary ABM using MR POTATOHEAD: An application to Housing Market Models in touristic areas. Ecological Complexity, 44, 100882.

Innocenti, E., Detotto, C., Idda, C., Parker, D. C., & Prunetti, D. (2023). Spécification conceptuelle MR POTATOHEAD – Property Market Edition du système complexe d’un territoire touristique à deux marchés: Application au territoire corse. In D. Prunetti & J. Jouve (Eds.), ESTATE – Etude de la SouTenAbilité des recompositions TErritoriales de la Corse (pp. 17–44). Università di Corsica Pasquale Paoli, CNRS, Laboratoire “Lieux, Identités, eSpaces, Activités” (UMR 6240 LISA). https://doi.org/10.58110/ESTATE-BG32

Innocenti, E., Prunetti, D., Delhom, M., & Idda, C. (2024). Reusable Building Blocks for Agent‐Based Simulations: Towards a Method for Composing and Building ABM/LUCC. The 16th International Conference on Advances in System Modeling and Simulation (SIMUL 2024), 28–33.

Innocenti, E., Prunetti, D., Delhom, M., & Idda, C. (2025). A Modular Approach for ABM/LMM Models: Specification of Reusable Building Blocks Centred on the Economic Concepts of WTA and WTP. International Journal On Advances in Software, 18(1 & 2), 11–24.

IPCC. (2025). Special Report on Climate Change and Cities—IPCC. The Intergovernmental Panel on Climate Change (IPCC). https://www.ipcc.ch/report/special-report-on-climate-change-and-cities/

Jackson, J., Forest, B., & Sengupta, R. (2008). Agent‐Based Simulation of Urban Residential Dynamics and Land Rent Change in a Gentrifying Area of Boston. Transactions in GIS, 12(4), 475–491. https://doi.org/10.1111/j.1467-9671.2008.01109.x

Kundu, D., & Pandey, A. K. (2020). World Urbanisation: Trends and Patterns. In D. Kundu, R. Sietchiping, & M. Kinyanjui (Eds.), Developing National Urban Policies: Ways Forward to Green and Smart Cities (pp. 13–49). Springer Nature. https://doi.org/10.1007/978-981-15-3738-7_2

Liu, J., Dietz, T., Carpenter, S. R., Alberti, M., Folke, C., Moran, E., Pell, A. N., Deadman, P., Kratz, T., Lubchenco, J., Ostrom, E., Ouyang, Z., Provencher, W., Redman, C. L., Schneider, S. H., & Taylor, W. W. (2007). Complexity of Coupled Human and Natural Systems. Science, 317(5844), 1513–1516. https://doi.org/10.1126/science.1144004

Liu, Y., Miller, E. J., & Habib, K. N. (2023). A Review of the Housing Market-Clearing Process in Integrated Land-Use and Transport Models. Journal of Transport and Land Use, 16(1), 335–360.

Magliocca, N., McConnell, V., & Walls, M. (2015). Exploring sprawl: Results from an economic agent-based model of land and housing markets. Ecological Economics, 113, 114–125.

Magliocca, N., McConnell, V., Walls, M., & Safirova, E. (2012). Zoning on the urban fringe: Results from a new approach to modeling land and housing markets. Regional Science and Urban Economics, 42(1–2), 198–210. https://doi.org/10.1016/j.regsciurbeco.2011.08.012

Magliocca, N. R., Brown, D. G., McConnell, V. D., Nassauer, J. I., & Westbrook, S. E. (2014). Effects of Alternative Developer Decision-Making Models on the Production of Ecological Subdivision Designs: Experimental Results from an Agent-Based Model. Environment and Planning B: Planning and Design, 41(5), 907–927. https://doi.org/10.1068/b130118p

Magliocca, N. R., & Walls, M. (2018). The role of subjective risk perceptions in shaping coastal development dynamics. Computers, Environment and Urban Systems, 71, 1–13. https://doi.org/10.1016/j.compenvurbsys.2018.03.009

Magliocca, N., Safirova, E., McConnell, V., & Walls, M. (2011). An economic agent-based model of coupled housing and land markets (CHALMS). Computers, Environment and Urban Systems, 35(3), 183–191. https://doi.org/10.1016/j.compenvurbsys.2011.01.002

Miller, E. (2018). The case for microsimulation frameworks for integrated urban models. Journal of Transport and Land Use, 11(1), 1025–1037.

Ministry of Attorney General. (2026). Local government housing initiatives—Province of British Columbia. Province of British Columbia. Retrieved March 19, 2026, from https://www2.gov.bc.ca/gov/content/housing-tenancy/local-governments-and-housing/housing-initiatives

Monkkonen, P., Guerra, E., Escamilla, J. M., Cos, C. C., & Tapia-McClung, R. (2024). A global analysis of land use regulation, urban form, and greenhouse gas emissions. Cities, 147, 104801. https://doi.org/10.1016/j.cities.2024.104801

Müller, B., Balbi, S., Buchmann, C. M., de Sousa, L., Dressler, G., Groeneveld, J., Klassert, C. J., Le, Q. B., Millington, J. D. A., Nolzen, H., Parker, D. C., Polhill, J. G., Schlüter, M., Schulze, J., Schwarz, N., Sun, Z., Taillandier, P., & Weise, H. (2014). Standardised and transparent model descriptions for agent-based models: Current status and prospects. Environmental Modelling and Software, 55, 156–163. Scopus. https://doi.org/10.1016/j.envsoft.2014.01.029

Müller, B., Bohn, F., Dreßler, G., Groeneveld, J., Klassert, C., Martin, R., Schlüter, M., Schulze, J., Weise, H., & Schwarz, N. (2013). Describing human decisions in agent-based models – ODD + D, an extension of the ODD protocol. Environmental Modelling & Software, 48, 37–48. https://doi.org/10.1016/j.envsoft.2013.06.003

Mutlu, A., & Filatova, T. (2026). Urban housing markets under flood risk: Modeling demand pressure, risk perception bias, and public interventions. Computers, Environment and Urban Systems, 128, 102440. https://doi.org/10.1016/j.compenvurbsys.2026.102440

Obsidian. (2026). Obsidian: Sharpen Your Thinking. https://obsidian.md/

Overwater, A., & Yorke-Smith, N. (2022). Agent-Based Simulation of Short-Term Peer-to-Peer Rentals: Evidence from the Amsterdam Housing Market. Environment and Planning B: Urban Analytics and City Science, 49(1), 223–240. https://doi.org/10.1177/23998083211000747

Ozel, B., Nathanael, R. C., Raberto, M., Teglio, A., & Cincotti, S. (2019). Macroeconomic Implications of Mortgage Loan Requirements: An Agent-Based Approach. Journal of Economic Interaction and Coordination, 14(1), 7–46. https://doi.org/10.1007/s11403-019-00238-5

Parker, D., Berger, T., & Manson, S. (2002). Agent-Based Models of Land-Use/Land-Cover Change: Report and Review of an International Workshop. Bloomington, IN: LUCC Focus 1 Publication 6. LUCC Focus 1.

Parker, D. C., Brown, D. G., Polhill, J. G., Deadman, P. J., & Manson, S. M. (2008). Illustrating a new conceptual design pattern for agent-based models of land use via five case studies—The MR POTATOHEAD framework. In Agent-based modelling in natural resource management (pp. 23–51). Universidad de Valladolid.

Parker, D. C., Carro, A., Detotto, C., Filatova, T., Ge, J., Huang, Y., Idda, C., Magliocca, N., Polhill, J. G., & Prunetti, D. (2019). MR POTATOHEAD: Property Market Edition| Development of a Common Description Template and Code Base for Agent-Based Land Market Models. Social Simulation Conference 2019, 15th Annual Social Simulation Conference.

Parker, D. C., & Filatova, T. (2008). A conceptual design for a bilateral agent-based land market with heterogeneous economic agents. Computers, Environment and Urban Systems, 32(6), 454–463. Scopus. https://doi.org/10.1016/j.compenvurbsys.2008.09.012

Parker, D. C., Jin, X., Yeung, K., Babin, R., Casello, J., Huang, Y., Pi, X., & Fard, P. (2016). The WARM Prototype: An Agent-Based Integrated Residential Land Market and Transportation Model to Simulate Impacts of Light-Rail Transit on a Medium-Sized North American Urban Area. International Congress on Agent Computing, Fairfax, VA, 29-30 Nov. 2016.

Parker, D. C., Manson, S. M., Janssen, M. A., Hoffmann, M. J., & Deadman, P. (2003). Multi-agent systems for the simulation of land-use and land-cover change: A review. Annals of the Association of American Geographers, 93(2), 314–337. Scopus. https://doi.org/10.1111/1467-8306.9302004

Parker, D. C., & Meretsky, V. (2004). Measuring pattern outcomes in an agent-based model of edge-effect externalities using spatial metrics. Agriculture, Ecosystems & Environment, From Pattern to Process: Landscape Fragmentation and the Analysis of Land Use/Land Cover Change, 101(2), 233–250. https://doi.org/10.1016/j.agee.2003.09.007

Polhill, J. G., Parker, D., Brown, D., & Grimm, V. (2008). Using the ODD protocol for describing three agent-based social simulation models of land-use change. JASSS, 11(2). https://www.jasss.org/11/2/3.html

Prunetti, D., Innocenti, E., Maraninchi, G., Idda, C., Detotto, C., Ling, Y., & Parker, D. C. (2025). Evaluation of Development Policies of a Tourist Territory Confronted with Intensive Urban Development using a Multi-Agent Modeling (Working Paper No. 26; Working Paper TerRA). UMR CNRS 6240 LISA. https://doi.org/10.58110/WP-8D85

Prunetti, D., Muzy, A., Innocenti, E., & Pieri, X. (2014). Utility-based multi-agent system with spatial interactions: The case of virtual estate development. Computational Economics, 43(3), 271–299. https://doi.org/DOI:%252010.1007/s10614-013-9372-0

Railsback, S. F., & Grimm, V. (2019). Agent-based and individual-based modeling: A practical introduction. Princeton university press.

Robinson, D. T., Brown ,Daniel G., Parker ,Dawn C., Schreinemachers ,Pepijn, Janssen ,Marco A., Huigen ,Marco, Wittmer ,Heidi, Gotts ,Nick, Promburom ,Panomsak, Irwin ,Elena, Berger ,Thomas, Gatzweiler ,Franz, & and Barnaud, C. (2007). Comparison of empirical methods for building agent-based models in land use science. Journal of Land Use Science, 2(1), 31–55. https://doi.org/10.1080/17474230701201349

Rød, J. K., & van der Meer, D. (2009). Visibility and Dominance Analysis: Assessing a High-Rise Building Project in Trondheim. Environment and Planning B: Planning and Design, 36(4), 698–710. https://doi.org/10.1068/b34118

Rosenfield, A., Chingcuanco, F., & Miller, E. J. (2013). Agent-based Housing Market Microsimulation for Integrated Land Use, Transportation, Environment Model System. Procedia Computer Science, The 4th International Conference on Ambient Systems, Networks and Technologies (ANT 2013), the 3rd International Conference on Sustainable Energy Information Technology (SEIT-2013), 19, 841–846. https://doi.org/10.1016/j.procs.2013.06.112

Rosenzweig, C., Solecki, W., Romero-Lankao, P., Mehrotra, S., Dhakal, S., Bowman, T., & Ibrahim, S. A. (2018). Climate Change and Cities: Second Assessment Report of the Urban Climate Change Research Network: Summary for City Leaders. In C. Rosenzweig, W. D. Solecki, P. Romero-Lankao, S. Mehrotra, S. Dhakal, & S. Ali Ibrahim (Eds.), Climate Change and Cities (1st ed., pp. xvii–xlii). Cambridge University Press. https://doi.org/10.1017/9781316563878.007

Seto, K. C., Sánchez-Rodríguez, R., & Fragkias, M. (2010). The New Geography of Contemporary Urbanization and the Environment. Annual Review of Environment and Resources, 35(1), 167–194. https://doi.org/10.1146/annurev-environ-100809-125336

Sun, S., Parker, D. C., Huang, Q., Filatova, T., Robinson, D. T., Riolo, R. L., Hutchins, M., & Brown, D. G. (2014). Market Impacts on Land-Use Change: An Agent-Based Experiment. Annals of the Association of American Geographers, 104(3), 460–484. https://doi.org/10.1080/00045608.2014.892338

Szangolies, L., Rohwäder, M.-S., Ahmed, H., Jahanmiri, F., Wagner, A., Souto-Veiga, R., Grimm, V., & Gallagher, C. (2024). Visual ODD: A Standardised Visualisation Illustrating the Narrative of Agent-Based Models. Journal of Artificial Societies and Social Simulation, 27(4), 1. https://doi.org/10.18564/jasss.5450

Thompson, J. J., Wilby ,Robert L., Hillier ,John K., Connell ,Richenda, & and Saville, G. R. (2023). Climate Gentrification: Valuing Perceived Climate Risks in Property Prices. Annals of the American Association of Geographers, 113(5), 1092–1111. https://doi.org/10.1080/24694452.2022.2156318

Valaei Sharif, S., Costa, R., & Parker, D. C. (2025, August 27). Incorporating demand heterogeneity into an agent-based housing market model using a two-stage hedonic model. Proceesings of the 2025 Social Simulation Conference. Social Simulation 2025, Delft, The Netherlands.

Valaei Sharif, S., Parker, D. C., Waddell, P., & Tsiakopoulos, T. (2023). Understanding the Effects of Market Volatility on Profitability Perceptions of Housing Market Developers. Journal of Risk and Financial Management, 16(10), Article 10. https://doi.org/10.3390/jrfm16100446

Verburg, P. H., & Overmars, K. P. (2009). Combining Top-down and Bottom-up Dynamics in Land Use Modeling: Exploring the Future of Abandoned Farmlands in Europe with the Dyna-CLUE Model. Landscape Ecology, 24(9), 1167–1181. https://doi.org/10.1007/S10980-009-9355-7

Waddell, P. (2007). UrbanSim: Modeling Urban Development for Land Use, Transportation, and Environmental Planning. Journal of the American Planning Association, 68(3), 297–314. https://doi.org/10.1080/01944360208976274

Walls, M., Magliocca, N., & McConnell, V. (2018). Modeling coastal land and housing markets: Understanding the competing influences of amenities and storm risks. Ocean & Coastal Management, 157, 95–110. https://doi.org/10.1016/j.ocecoaman.2018.01.021

Wilensky, U., & Rand, W. (2015). An introduction to agent-based modeling: Modeling natural, social, and engineered complex systems with NetLogo. Mit Press.

Wyman, D., Worzala, E., & Seldin, M. (2013). Hidden Complexity in Housing Markets: A Case for Alternative Models and Techniques. International Journal of Housing Markets and Analysis, 6(4), 383–404. https://doi.org/10.1108/IJHMA-05-2012-0021

Ying, X., Ding, G., Hu, X., & Zhang, Y. (2016). Developing planning indicators for outdoor wind environments of high-rise residential buildings. Journal of Zhejiang University-SCIENCE A, 17(5), 378–388. https://doi.org/10.1631/jzus.A1600026

Zhong, M., Hunt, J. D., Abraham, J. E., Wang, W., Zhang, Y., & Wang, R. (2022). Chapter Nine—Advances in Integrated Land Use Transport Modeling. In X. J. Cao, C. Ding, & J. Yang (Eds.), Advances in Transport Policy and Planning (Vol. 9, pp. 201–230). Academic Press. https://doi.org/10.1016/bs.atpp.2021.10.002

Zhu, Y., Diao, M., Ferreira, J., & Zegras, relax PC. (2018). An Integrated Microsimulation Approach to Land-Use and Mobility Modeling. Journal of Transport and Land Use, 11(1), 633–659. http://dx.doi.org/10.5198/jtlu.2018.1186

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