IDEAS home Printed from https://ideas.repec.org/r/eee/intfor/v30y2014i3p415-425.html

Forecasting the US housing market

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Martin, Carolin & Schmitt, Noemi & Westerhoff, Frank, 2021. "Heterogeneous expectations, housing bubbles and tax policy," Journal of Economic Behavior & Organization, Elsevier, vol. 183(C), pages 555-573.
  2. Frijns, Bart & Zwinkels, Remco C.J., 2020. "Absence of speculation in the European sovereign debt markets," Journal of Economic Behavior & Organization, Elsevier, vol. 169(C), pages 245-265.
  3. Ling Zhang & Wenlong Bian & Hao Zhang, 2019. "Dissecting the myth of the house price in Chinese metropolises: allowing for behavioral heterogeneity among investors," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(4), pages 721-740, December.
  4. Martin, Carolin & Schmitt, Noemi & Westerhoff, Frank, 2022. "Housing Markets, Expectation Formation And Interest Rates," Macroeconomic Dynamics, Cambridge University Press, vol. 26(2), pages 491-532, March.
  5. Basse, Tobias & Desmyter, Steven & Saft, Danilo & Wegener, Christoph, 2023. "Leading indicators for the US housing market: New empirical evidence and thoughts about implications for risk managers and ESG investors," International Review of Financial Analysis, Elsevier, vol. 89(C).
  6. Bingzi Jin & Xiaojie Xu, 2025. "Predictions of residential property price indices for China via machine learning models," Quality & Quantity: International Journal of Methodology, Springer, vol. 59(2), pages 1481-1513, April.
  7. McGurk, Zachary, 2020. "US real estate inflation prediction: Exchange rates and net foreign assets," The Quarterly Review of Economics and Finance, Elsevier, vol. 75(C), pages 53-66.
  8. Oguzhan Cepni & Rangan Gupta & Yigit Onay, 2022. "The role of investor sentiment in forecasting housing returns in China: A machine learning approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(8), pages 1725-1740, December.
  9. Chen, Zhenxi, 2016. "Regimes dependent speculative trading: Evidence from the United States housing market," FinMaP-Working Papers 66, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
  10. David Coble & Pablo Pincheira, 2021. "Forecasting building permits with Google Trends," Empirical Economics, Springer, vol. 61(6), pages 3315-3345, December.
  11. Bolt, Wilko & Demertzis, Maria & Diks, Cees & Hommes, Cars & Leij, Marco van der, 2019. "Identifying booms and busts in house prices under heterogeneous expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 103(C), pages 234-259.
  12. Dieci, Roberto & Schmitt, Noemi & Westerhoff, Frank, 2018. "Interactions between stock, bond and housing markets," Journal of Economic Dynamics and Control, Elsevier, vol. 91(C), pages 43-70.
  13. Benjamin Patrick Evans & Kirill Glavatskiy & Michael S. Harré & Mikhail Prokopenko, 2023. "The impact of social influence in Australian real estate: market forecasting with a spatial agent-based model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 18(1), pages 5-57, January.
  14. P. S. Morawakage & G. Earl & B. Liu & E. Roca & A. Omura, 2023. "Housing Risk and Returns in Submarkets with Spatial Dependence and Heterogeneity," The Journal of Real Estate Finance and Economics, Springer, vol. 67(4), pages 695-734, November.
  15. Laurynas Narusevicius & Tomas Ramanauskas & Laura Gudauskaitė & Tomas Reichenbachas, 2019. "Lithuanian house price index: modelling and forecasting," Bank of Lithuania Occasional Paper Series 28, Bank of Lithuania.
  16. Schmitt, Noemi & Westerhoff, Frank, 2015. "Managing rational routes to randomness," Journal of Economic Behavior & Organization, Elsevier, vol. 116(C), pages 157-173.
  17. Frijns, Bart & Zwinkels, Remco C.J., 2018. "Time-varying arbitrage and dynamic price discovery," Journal of Economic Dynamics and Control, Elsevier, vol. 91(C), pages 485-502.
  18. Alqaralleh, Huthaifa & Canepa, Alessandra, 2020. "Housing market cycles in large urban areas," Economic Modelling, Elsevier, vol. 92(C), pages 257-267.
  19. ter Ellen, Saskia & Hommes, Cars H. & Zwinkels, Remco C.J., 2021. "Comparing behavioural heterogeneity across asset classes," Journal of Economic Behavior & Organization, Elsevier, vol. 185(C), pages 747-769.
  20. Tanashkin, Alexey S. & Tanashkina, Irina G. & Maksimchuik, Alexander S., 2026. "Modern approaches to building interpretable models of the property market using machine learning on the base of mass cadastral valuation," Land Use Policy, Elsevier, vol. 165(C).
  21. Martin Carolin & Westerhoff Frank, 2019. "Regulating Speculative Housing Markets via Public Housing Construction Programs: Insights from a Heterogeneous Agent Model," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 239(4), pages 627-660, August.
  22. Wai-Mun Chia & Mengling Li & Huanhuan Zheng, 2017. "Behavioral heterogeneity in the Australian housing market," Applied Economics, Taylor & Francis Journals, vol. 49(9), pages 872-885, February.
  23. Bart Frijns & Ivan Indriawan, 2018. "Behavioural heterogeneity in the New Zealand stock market," New Zealand Economic Papers, Taylor & Francis Journals, vol. 52(1), pages 53-71, January.
  24. Blake LeBaron, 2021. "Microconsistency in Simple Empirical Agent-Based Financial Models," Computational Economics, Springer;Society for Computational Economics, vol. 58(1), pages 83-101, June.
  25. Bolt, Wilko & Demertzis, Maria & Diks, Cees & Hommes, Cars & Leij, Marco van der, 2019. "Identifying booms and busts in house prices under heterogeneous expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 103(C), pages 234-259.
  26. Hany Guirguis & Glenn Mueller & Vaneesha Dutra & Robert Jafek, 2025. "Advances in Forecasting Home Prices," Computational Economics, Springer;Society for Computational Economics, vol. 65(6), pages 3633-3650, June.
  27. Kuang-Liang Chang & Nan-Kuang Chen & Charles Ka Yui Leung, 2016. "Losing Track of the Asset Markets: the Case of Housing and Stock," International Real Estate Review, Global Social Science Institute, vol. 19(4), pages 435-492.
  28. Roy Kouwenberg & Remco C J Zwinkels, 2015. "Endogenous Price Bubbles in a Multi-Agent System of the Housing Market," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-10, June.
  29. Dieci, Roberto & Westerhoff, Frank, 2016. "Heterogeneous expectations, boom-bust housing cycles, and supply conditions: A nonlinear economic dynamics approach," Journal of Economic Dynamics and Control, Elsevier, vol. 71(C), pages 21-44.
  30. Zhenxi Chen & Cuntong Wang, 2020. "Speculative trading in Chinese housing market: a panel regression method," Applied Economics, Taylor & Francis Journals, vol. 52(38), pages 4186-4195, July.
  31. Kukacka, Jiri & Barunik, Jozef, 2017. "Estimation of financial agent-based models with simulated maximum likelihood," Journal of Economic Dynamics and Control, Elsevier, vol. 85(C), pages 21-45.
  32. Saskia ter Ellen & Willem F. C. Verschoor, 2018. "Heterogeneous Beliefs and Asset Price Dynamics: A Survey of Recent Evidence," Dynamic Modeling and Econometrics in Economics and Finance, in: Fredj Jawadi (ed.), Uncertainty, Expectations and Asset Price Dynamics, pages 53-79, Springer.
  33. Piet Eichholtz & Ronald Huisman & Remco C. J. Zwinkels, 2015. "Fundamentals or trends? A long-term perspective on house prices," Applied Economics, Taylor & Francis Journals, vol. 47(10), pages 1050-1059, February.
  34. Dieci, Roberto & Westerhoff, Frank, 2015. "Heterogeneous expectations, boom-bust housing cycles, and supply conditions: A nonlinear dynamics approach," BERG Working Paper Series 99, Bamberg University, Bamberg Economic Research Group.
  35. Noemi Schmitt & Frank Westerhoff, 2022. "Speculative housing markets and rent control: insights from nonlinear economic dynamics," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 17(1), pages 141-163, January.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.