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Real Estate Modelling and Forecasting

Author

Listed:
  • Brooks,Chris
  • Tsolacos,Sotiris

Abstract

As real estate forms a significant part of the asset portfolios of most investors and lenders, it is crucial that analysts and institutions employ sound techniques for modelling and forecasting the performance of real estate assets. Assuming no prior knowledge of econometrics, this book introduces and explains a broad range of quantitative techniques that are relevant for the analysis of real estate data. It includes numerous detailed examples, giving readers the confidence they need to estimate and interpret their own models. Throughout, the book emphasises how various statistical techniques may be used for forecasting and shows how forecasts can be evaluated. Written by a highly experienced teacher of econometrics and a senior real estate professional, both of whom are widely known for their research, Real Estate Modelling and Forecasting is the first book to provide a practical introduction to the econometric analysis of real estate for students and practitioners.

Suggested Citation

  • Brooks,Chris & Tsolacos,Sotiris, 2010. "Real Estate Modelling and Forecasting," Cambridge Books, Cambridge University Press, number 9780521873390.
    • Handle: RePEc:cup:cbooks:9780521873390
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    Citations

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    Cited by:

    1. Joseph DeSalvo, 2017. "Teaching the DiPasquale-Wheaton Model," Working Papers 0117, University of South Florida, Department of Economics.
    2. Inna S. Lola & Anton Manukov & Murat Bakeev, 2020. "Stress Testing As A Tool For Monitoring And Modelling The Dynamics Of Business Activity Of Manufacturing Enterprises In Russia In The Face Of Market Shocks: Short-Term Scenarios Of Industry Tendencies," HSE Working papers WP BRP 108/STI/2020, National Research University Higher School of Economics.
    3. Joseph Obaje Ataguba & Celestine Udoka Ugonabo, 2023. "Framework for measuring the efficiency and efficacy of sale of distressed mortgaged properties using imports of statistical tests deployed in clinical studies," SN Business & Economics, Springer, vol. 3(8), pages 1-32, August.
    4. Troug, Haytem & Murray, Matt, 2015. "The Effects of Asymmetric Shocks in Oil Prices on the Performance of the Libyan Economy," MPRA Paper 68705, University Library of Munich, Germany.
    5. Arvydas Jadevicius & Brian Sloan & Andrew Brown, 2013. "Property Market Modelling and Forecasting: A Case for Simplicity," ERES eres2013_10, European Real Estate Society (ERES).
    6. Fragoso Januário, João & Costa, Álvaro & Oliveira Cruz, Carlos & Miranda Sarmento, Joaquim & Faria e Sousa, Vítor, 2021. "Transport infrastructure, accessibility, and spillover effects: An empirical analysis of the Portuguese real estate market from 2000 to 2018," Research in Transportation Economics, Elsevier, vol. 90(C).
    7. Ramiro J. Rodriguez & Simon Sosvilla-Rivero, 2017. "Office Market Dynamics in Madrid: Modelling with a Single-Equation Error Correction Mechanism," International Real Estate Review, Global Social Science Institute, vol. 20(4), pages 451-491.
    8. Philipp Bejol & Nicola Livingstone, 2018. "Revisiting currency swaps: hedging real estate investments in global city markets," Journal of Property Investment & Finance, Emerald Group Publishing Limited, vol. 36(2), pages 191-209, March.
    9. Gary Owen Garner, 2012. "The significance of financial barriers caused by holding costs in greenfield residential development," ERES eres2012_003, European Real Estate Society (ERES).
    10. Erik Louw, 2011. "Surveys and forecasting industrial property demand," ERES eres2011_217, European Real Estate Society (ERES).
    11. Coskun Yener & Jadevicius Arvydas, 2017. "Is there a Housing Bubble in Turkey?," Real Estate Management and Valuation, Sciendo, vol. 25(1), pages 48-73, March.
    12. Arvydas Jadevicius & Brian Sloan & Andrew Brown, 2012. "Examination of property forecasting models - accuracy and its improvement through combination forecasting," ERES eres2012_082, European Real Estate Society (ERES).
    13. Farzanegan, Mohammad Reza, 2011. "Oil revenue shocks and government spending behavior in Iran," Energy Economics, Elsevier, vol. 33(6), pages 1055-1069.
    14. Maral Taşcılar & Kerem Yavuz Arslanlı, 2022. "Forecasting commercial real estate indicators under COVID-19 by adopting human activity using social big data," Asia-Pacific Journal of Regional Science, Springer, vol. 6(3), pages 1111-1132, October.

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