Exploring House Price Dynamics: An Agent-Based Simulation with Behavioral Heterogeneity

  • Tolga A. OzbakanEmail author
  • Serdar Kale
  • Irem Dikmen


The objective of this study is to contribute to the understanding of price formations in housing markets through an agent-based simulation that conceptualizes insights from behavioral economics. For this purpose, the study uses a prominent real estate market model as a benchmark and extends it to account for (1) behavioral heterogeneity and (2) dynamic agent interaction. The validation of the model is carried out by using real data from the Turkish housing market. The results show that the introduction of a fitness-based behavior-switching regime with myopic agents improves the extent to which the observed market behavior can be replicated, in comparison to the benchmark model.


Agent-based modeling House prices Behavioral economics Evolutionary finance 



This paper was based mainly upon the unpublished doctoral dissertation of the first author (Ozbakan 2016). We graciously appreciate the constructive and meticulous feedback received during the review process.


  1. Allen, H., & Taylor, M. P. (1990). Charts, noise and fundamentals in the London foreign exchange market. The Economic Journal, 100(400), 49–59.CrossRefGoogle Scholar
  2. Barberis, N., & Thaler, R. (2003). A survey of behavioral finance. In G. M. Constantinides, M. Harris & R. M. Stulz (Eds.), Handbook of the economics of finance (Vol. s.l, pp. 1053–1128). Amsterdam: Elsevier.Google Scholar
  3. Bijman, I. T. (2012). Expectations in a nonlinear real estate model. Unpublished master’s thesis. University of Amsterdam, Amsterdam.Google Scholar
  4. Bolt, W. et al., (2013). Identifying booms and busts in house prices under heterogeneous expectations. Tinbergen Institute Discussion Papers, pp. 1–24.Google Scholar
  5. Brock, W. A., & Hommes, C. H. (1997). A rational route to randomness. Econometrica, 65(5), 1059–1095.CrossRefGoogle Scholar
  6. Brock, W. A., & Hommes, C. H. (1998). Heterogeneous beliefs and routes to chaos in a simple asset pricing. Journal of Economic Dynamics and Control, 22(8–9), 1235–1274.CrossRefGoogle Scholar
  7. Burnside, C., Eichenbaum, M., & Rebelo, S., (2011). Understanding booms and busts in housing markets. NBER Working Papers, Issue 16734, pp. 1–56.Google Scholar
  8. Campisi, G., Naimzada, A. K., & Tramontana, F. (2018). Local and global analysis of a speculative housing market with production lag. Chaos, 28(5), 055901.CrossRefGoogle Scholar
  9. Dieci, R., & Westerhoff, F. (2012). A simple model of a speculative housing market. Journal of Evolutionary Economics, 22, 303–329.CrossRefGoogle Scholar
  10. DiPasquale, D., & Wheaton, W. C. (1992). The markets for real estate assets and space: A conceptual framework. Journal of the American Real Estate and Urban Economics Association, 20(1), 181–197.CrossRefGoogle Scholar
  11. Eichholtz, P., Huisman, R., & Zwinkels, R. C. J. (2015). Fundamentals or trends? A long-term perspective on house prices. Applied Economics, 47(10), 1050–1059.CrossRefGoogle Scholar
  12. Frankel, J. A., & Froot, K. A. (1987). Expectations, using survey data to test standard propositions regarding exchange rate. The American Economic Review, 77(1), 133–153.Google Scholar
  13. Frankel, J. A., & Froot, K. A. (1990). Chartists, Fundamentalists and the Demand for Dollars. National Bureau of Economic Research, 1655, 73–126.Google Scholar
  14. Harrison, J. M., & Kreps, D. M. (1978). Speculative investor behavior in a stock market with heterogeneous expectations. The Quarterly Journal of Economics, 92(2), 323–336.CrossRefGoogle Scholar
  15. Himmelberg, C., Mayer, C., & Sinai, T., (2005). Assessing high house prices: Bubbles, fundamentals and misperceptions. NBER Working Paper Series, Issue 11643, pp. 1–42.Google Scholar
  16. Hommes, C. H. (2006). Heterogeneous agent models in economics and finance. In: L. Tesfatsion & K. L. Judd (Eds.), Handbook of Computational Economics (Vol. s.l., pp. 1110–1146) Elsevier.Google Scholar
  17. Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263–291.CrossRefGoogle Scholar
  18. Kahneman, D., & Tversky, A. (1984). Choices, values, and frames. American Psychologist, 39(4), 341–350.CrossRefGoogle Scholar
  19. Kirman, A. (1993). Ants, rationality, and recruitment. The Quarterly Journal of Economics, 108(1), 137–156.CrossRefGoogle Scholar
  20. LeBaron, B. (2001). A builder’s guide to agent-based financial markets. Quantitative Finance, 1(2), 254–261.CrossRefGoogle Scholar
  21. Ozbakan, A. T. (2016). Exploring house price dynamics: An agent-based simulation with behavioral heterogeneity. Unpublished doctoral dissertation. Izmir: Izmir Institute of Technology.Google Scholar
  22. Poterba, J. M. (1984). Tax subsidies to owner-occupied housing: An asset-market approach. The Quarterly Journal of Economics, 99(4), 729–752.CrossRefGoogle Scholar
  23. Poterba, J. M. (1991). House price dynamics: The role of tax policy and demography. Brookings Papers on Economic Activity, 2, 143–203.CrossRefGoogle Scholar
  24. Simon, H. A. (1955). A behavioral model of rational choice. The Quarterly Journal of Economics, 69(1), 99–118.CrossRefGoogle Scholar
  25. Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4157), 1124–1131.CrossRefGoogle Scholar
  26. Wheaton, W. C. (1999). Real estate “cycles”: Some fundamentals. Real Estate Economics, 27(2), 209–230.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Technopark, Izmir Institute of TechnologyIzmirTurkey
  2. 2.Department of ArchitectureIzmir Institute of TechnologyIzmirTurkey
  3. 3.Department of Civil EngineeringMiddle East Technical UniversityAnkaraTurkey

Personalised recommendations