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Real Estate Rental Growth Rates at Different Points in the Physical Market Cycle

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Abstract

Real estate markets go through both physical cycles (demand and supply) that affect rental growth rates and financial cycles (capital flows to real estate) that affect property Prices (Mueller, 1995). This study develops a rental growth rate hypothesis based on a market’s position in the physical (demand-supply) market cycle. Using data from fifty-four office and industrial markets in the United States over a thirty-year period, an aggregated national average rental growth rate was calculated for each point in the cycle. An ANOVA test for differences of means found that the national average rental growth rates at each point in the cycle were statistically different. The results show local demand and supply, which interact to affect occupancy, are major determinants in rental growth rates. This research should help investors move from using a single rental growth rate for multiple year forecasts, to using yearly cycle driven rental growth rate estimates in their discounted cash flow projections.

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  • Glenn R. Mueller, 1999. "Real Estate Rental Growth Rates at Different Points in the Physical Market Cycle," Journal of Real Estate Research, American Real Estate Society, vol. 18(1), pages 131-150.
    • Handle: RePEc:jre:issued:v:18:n:1:1999:p:131-150
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    1. William C. Wheaton, 1987. "The Cyclic Behavior of the National Office Market," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 15(4), pages 281-299, December.
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    Cited by:

    1. Changha Jin & Terry V. Grissom, 2008. "Forecasting Dynamic Investment Timing under the Cyclic Behavior in Real Estate," International Real Estate Review, Global Social Science Institute, vol. 11(2), pages 105-125.
    2. Krzysztof Olszewski, 2012. "The impact of commercial real estate on the financial sector, its tracking by central banks and some recommendations for the macro-financial stability policy of central banks," NBP Working Papers 132, Narodowy Bank Polski.
    3. Laurin Frederic, 2011. "The Real Estate Conundrum in the CEE Office Markets: Thinking Too Big?," EERC Working Paper Series 11/07e, EERC Research Network, Russia and CIS.
    4. Fuerst, Franz, 2007. "Office Rent Determinants: A Hedonic Panel Analysis," MPRA Paper 11445, University Library of Munich, Germany.
    5. Yun-Ling Wu & Cheng-Huang Tung & Chun-Chang Lee, 2017. "The Power of a Leading Indicators Fluctuation Trend for Forecasting Taiwans Real Estate Business Cycle: An Application of a Hidden Markov Model," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 7(1), pages 81-98, January.
    6. 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.
    7. Barrett, Alan & Kearney, Ide & Goggin, Jean, 2008. "Quarterly Economic Commentary, Winter 2008," Forecasting Report, Economic and Social Research Institute (ESRI), number QEC20084.
    8. Daniel Lo & Yung Yau & Michael McCord & Martin Haran, 2022. "Dynamics between Direct Industrial Real Estate and the Macroeconomy: An Empirical Study of Hong Kong," Land, MDPI, vol. 11(10), pages 1-23, September.
    9. Rose Lai & Ko Wang & Jing Yang, 2007. "Stickiness of Rental Rates and Developers’ Option Exercise Strategies," The Journal of Real Estate Finance and Economics, Springer, vol. 34(1), pages 159-188, January.
    10. Lisha He & Mia M Bennett & Ronghao Jiang, 2022. "The uneven geography of real estate investment by Mainland Chinese state-owned and private enterprises in the U.S.: Local market conditions, migration, and ethnic networks," Environment and Planning A, , vol. 54(4), pages 653-675, June.
    11. Richard D. Evans & Glenn R. Mueller, 2016. "Five Property Types' Real Estate Cycles as Markov Chains," International Real Estate Review, Global Social Science Institute, vol. 19(3), pages 265-296.
    12. Krzysztof Olszewski, 2013. "The Commercial Real Estate Market, Central Bank Monitoring and Macroprudential Policy," Review of Economic Analysis, Digital Initiatives at the University of Waterloo Library, vol. 5(2), pages 213-250, December.
    13. 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).
    14. Frederic Laurin & John-John D'Argensio & Thea Goginashvili, 2010. "The Real Estate Conundrum in the CEE Office Markets: Thinking Too Big?," Working Papers 10-001, International School of Economics at TSU, Tbilisi, Republic of Georgia.

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    JEL classification:

    • L85 - Industrial Organization - - Industry Studies: Services - - - Real Estate Services

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