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Green Design and the Market for Commercial Office Space

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Abstract

This paper considers the relationship between energy-efficient design and the leasing/sales markets for commercial real estate. An economic model is provided that considers lease rates and occupancy in simultaneous equilibrium. The behavior of both is predicted to be influenced by efficient design attributes. Selling price is determined by both rents and occupancy; therefore the impact of efficient design on commercial sales activity should be distributed through the leasing market. The model is tested empirically using a national sample of sales and leasing data for class A office buildings. The evidence indicates that “green” buildings achieve superior rents and sustain significantly higher occupancy. The improved performance in the rental market is reflected in a significant premium for the selling price of Energy Star-labeled and LEED-certified properties.

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Notes

  1. EPA press release, Feb. 12, 2008 “Green Choices Grow with Energy Star Qualified Buildings.”

  2. In two reports prepared as guidelines for appraisers considering the contribution of energy costs, Chao et al. (1999) and Chao and Parker (2000) use data from Building Owners and Managers Association 1998 Experience Exchange Report to illustrate that median energy costs contribute between 23 to 30% of total operating costs in four major downtown California office markets and between 31 to 37% in four major downtown New York office markets.

  3. EPA press release, Feb. 12, 2008 “Green Choices Grow with Energy Star Qualified Buildings.”

  4. See, for instance, Evolution Partners press release, Dec. 6, 2005 “Meeting Notes: LEEDÒ and Energy StarÒ Building Finance Summit.”

  5. Leasing markets include Atlanta, Austin, Boise City/Nampa, Boston, Charlotte, Chicago, Cincinnati/Dayton, Cleveland, Colorado Springs, Columbus, Dallas/Ft Worth, Denver, Detroit, East Bay/Oakland, Hampton Roads, Hartford, Hawaii, Houston, Indianapolis, Inland Empire (CA), Jacksonville (FL), Kansas City, Los Angeles, Louisville, Milwaukee/Madison, Minneapolis/St Paul, Nashville, New York City, Northern New Jersey, Orange (CA), Orlando, Philadelphia, Phoenix, Portland, Raleigh/Durham, Sacramento, Salt Lake City, San Diego, San Francisco, Seattle/Puget Sound, South Bay/San Jose, South Florida, St Louis, Tampa/St Petersburg, Toledo, Washington DC.

  6. Lease types include Full Service Gross, Modified Gross, Negotiable, Net, Plus All Utilities, Plus Cleaning, Plus Electric, Tenant Electric, Triple Net, Utilities and Char.

  7. Sales markets include Atlanta, Boston, Charlotte, Chicago, Columbus, Dallas/Ft Worth, Denver, East Bay/Oakland, Houston, Jacksonville (FL), Los Angeles, Milwaukee/Madison, Minneapolis/St Paul, Northern New Jersey, Orange (CA), Philadelphia, Phoenix, Portland, Sacramento, San Diego, San Francisco, Seattle/Puget Sound, South Florida, St Louis, Washington DC.

  8. Model 2 uses the 45 market indicators along with the 11 lease type indicators as instrumental variables in the first-stage estimation to collect predicted values for Occupancy. In the second stage, the market indicator for “Los Angeles” along with the lease type indicator for “Double Net” are omitted so that the model is full rank resulting in second-stage parameter estimates that are unique, consistent and unbiased. Model 4 uses the 45 market indicators as instrumental variables in the first-stage estimation to collect predicted values for ln(Avg_rent). The market indicator for “Kansas City” is omitted in the second stage.

References

  • Bollinger, C. R., Ihlanfeldt, K. R., & Bowes, D. R. (1998). Spatial variation in office rents within the Atlanta region. Urban Studies, 35, 1097–1118. doi:10.1080/0042098984501.

    Article  Google Scholar 

  • Brennan, T. P., Cannaday, R. E., & Colwell, P. F. (1984). Office rent in the Chicago CBD. Real Estate Economics, 12, 243–260. doi:10.1111/1540-6229.00321.

    Article  Google Scholar 

  • Benjamin, J. D., Jud, G. D., & Winkler, D. T. (1998). A simultaneous model and empirical test of the demand and supply of retail space. Journal of Real Estate Research, 16, 1–13.

    Google Scholar 

  • Cassidy, R. (2003). White paper on sustainability: A report on the Green Building Movement. Supplement to Building Design and Construction.

  • Chao, M., & Parker, G. (2000). Recognition of energy costs and energy performance in commercial property valuation. New York, NY: New York State Energy Research and Development Authority.

    Google Scholar 

  • Chao, M., Parker, G., Mahone, D., & Kammerud, R. (1999). Recognition of energy costs and energy performance in commercial property valuation. San Francisco, CA: Pacific Gas and Electric Company.

    Google Scholar 

  • Clapp, J. M. (1980). The intrametropolitan location of office activities. Journal of Regional Science, 20, 387–399. doi:10.1111/j.1467-9787.1980.tb00655.x.

    Article  Google Scholar 

  • Frew, J., & Jud, G. D. (1988). The vacancy rate and rent levels in the commercial office market. Journal of Real Estate Research, 3, 1–8.

    Google Scholar 

  • Glascock, J. L., Jahanian, S., & Sirmans, C. F. (1990). An analysis of office market rents: Some empirical evidence. Real Estate Economics, 18, 105–119. doi:10.1111/1540-6229.00512.

    Article  Google Scholar 

  • Hekman, J. S. (1985). Rental price adjustment and investment in the office market. Real Estate Economics, 13, 32–47. doi:10.1111/1540-6229.00339.

    Article  Google Scholar 

  • Hendershott, P. H. (1996). Rental adjustment and valuation in overbuilt markets: Evidence from the Sydney office market. Journal of Urban Economics, 39, 51–67. doi:10.1006/juec.1996.0003.

    Article  Google Scholar 

  • Hendershott, P. H., MacGregor, B. D., & Tse, R. Y. C. (2002). Estimation of the rental adjustment process. Real Estate Economics, 30, 165–183. doi:10.1111/1540-6229.00036.

    Article  Google Scholar 

  • Kats, G. (2003). The costs and financial benefits of green buildings. A Report to California’s Sustainable Building Task Force.

  • McHugh, J., Heschong, L., Stone, N., Vogen, A., Mills, D., & Panetti, C. (2002). Non-energy benefits as a market transformation driver. In Proceedings of the ACEEE 2002 Summer Study on Energy Efficiency in Buildings. Washington, DC: American Council for an Energy Efficient Economy.

  • Pollakowski, H. O., Wachter, S. M., & Lynford, L. (1992). Did office market size matter in the 1980s? A time-series cross-sectional analysis of metropolitan area office markets. Real Estate Economics, 20, 302–324. doi:10.1111/1540-6229.00586.

    Article  Google Scholar 

  • Rosen, K. T. (1984). Toward a model of the office building sector. Real Estate Economics, 12, 261–269. doi:10.1111/1540-6229.00322.

    Article  Google Scholar 

  • Shilling, J. D., Sirmans, C. F., & Corgel, J. B. (1987). Price adjustment process for rental office space. Journal of Urban Economics, 22, 90–100. doi:10.1016/0094-1190(87)90051-9.

    Article  Google Scholar 

  • Slade, B. A. (2000). Office rent determinants during market decline and recovery. Journal of Real Estate Research, 20, 357–380.

    Google Scholar 

  • Watchman, L. H. (2007). LEED certification: Overview and trends for the future. Real Estate Review, 36, 19–29.

    Google Scholar 

  • Wheaton, W. C. (1990). Vacancy, search, and prices in a housing market matching model. Journal of Political Economy, 98, 1270–1292. doi:10.1086/261734.

    Article  Google Scholar 

  • Wheaton, W. C. (1999). Real estate “cycles”: Some fundamentals. Real Estate Economics, 27, 209–230. doi:10.1111/1540-6229.00772.

    Article  Google Scholar 

  • Wheaton, W. C., & Torto, R. G. (1994). Office rent indices and their behavior over time. Journal of Urban Economics, 35, 121–139. doi:10.1006/juec.1994.1008.

    Article  Google Scholar 

  • Williams, J. T. (1995). Pricing real assets with costly search. Review of Financial Studies, 8, 55–90. doi:10.1093/rfs/8.1.55.

    Article  Google Scholar 

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Authors and Affiliations

  1. College of Charleston, 5 Liberty Street, 4th Floor, Charleston, SC, 29401, USA

    Jonathan A. Wiley & Justin D. Benefield

  2. Florida International University, 11200 SW 8th Street, University Park MARC 230, Miami, FL, 33199, USA

    Ken H. Johnson

Authors
  1. Jonathan A. Wiley
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  2. Justin D. Benefield
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  3. Ken H. Johnson
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Correspondence to Jonathan A. Wiley.

Appendices

Appendix 1

Table 5 Description of markets
Full size table

Appendix 2

Table 6 Description of lease types
Full size table

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Wiley, J.A., Benefield, J.D. & Johnson, K.H. Green Design and the Market for Commercial Office Space. J Real Estate Finan Econ 41, 228–243 (2010). https://doi.org/10.1007/s11146-008-9142-2

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