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Predictable or Not? Forecasting Office Markets with a Simultaneous Equation Approach

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  • Fuerst, Franz

Abstract

The main objective of this paper is to elucidate the capability of time-series regression models to capture and forecast movements in occupancy patterns, rental rates and construction activity. The model presented is a three-stage simultaneous equation model. The first stage incorporates the office space market in terms of occupied space and absorption of new space. The second stage captures the adjustment of office rents to changing market conditions and the third stage specifies the supply response to market signals in terms of construction of new office space. The standard simultaneous model is subsequently modified to account for the specific characteristics using the New York market as a case study. The results demonstrate that the market reacts efficiently and predictably to changes in market conditions. The significance of the estimated parameters underscores the general validity and robustness of the simultaneous equation approach in modeling real estate markets. The modifications of the standard model, notably the inclusion of sublet space in the rent equation, contributed considerably to improving the explanatory power of the model. Finally, we test whether a non-linear function performs better than the original linear approach and find mixed evidence based on the limited empirical dataset of this study.

Suggested Citation

  • Fuerst, Franz, 2006. "Predictable or Not? Forecasting Office Markets with a Simultaneous Equation Approach," MPRA Paper 5262, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:5262
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    File URL: https://mpra.ub.uni-muenchen.de/5262/1/MPRA_paper_5262.pdf
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    References listed on IDEAS

    as
    1. Franz Fuerst, 2004. "Forecasting the Manhattan office market with a simultaneous equation model," Urban/Regional 0410006, EconWPA.
    2. Timothy W. Viezer, 1999. "Econometric Integration of Real Estate's Space and Capital Markets," Journal of Real Estate Research, American Real Estate Society, vol. 18(3), pages 503-519.
    3. John S. Hekman, 1985. "Rental Price Adjustment and Investment in the Office Market," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 13(1), pages 32-47.
    4. Chen, Nai-fu, 1983. " Some Empirical Tests of the Theory of Arbitrage Pricing," Journal of Finance, American Finance Association, vol. 38(5), pages 1393-1414, December.
    5. Wheaton, William C & Torto, Raymond G & Evans, Peter, 1997. "The Cyclic Behavior of the Greater London Office Market," The Journal of Real Estate Finance and Economics, Springer, vol. 15(1), pages 77-92, July.
    6. Patric H. Hendershott & Colin M. Lizieri & George A. Matysiak, 1999. "The Workings of the London Office Market," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 27(2), pages 365-387.
    7. Shilling, James D. & Sirmans, C. F. & Corgel, John B., 1987. "Price adjustment process for rental office space," Journal of Urban Economics, Elsevier, vol. 22(1), pages 90-100, July.
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    Cited by:

    1. Barrett, Alan & Kearney, Ide & Goggin, Jean, 2008. "Quarterly Economic Commentary, Winter 2008," Forecasting Report, Economic and Social Research Institute (ESRI), number QEC20084.
    2. McCartney, John, 2008. "An Empirical Analysis of Development Cycles in the Dublin Office Market 1976-2007," Quarterly Economic Commentary: Special Articles, Economic and Social Research Institute (ESRI), vol. 2008(4-Winter), pages 68-92.

    More about this item

    Keywords

    forecasting; real estate; office markets; dynamic models; simultaneous equation approach; multivariate regression models;

    JEL classification:

    • R33 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Nonagricultural and Nonresidential Real Estate Markets
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables

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