Disentangling the Short and Long-Run Effects of Occupied Stock in the Rental Adjustment Process

  • Zeno Adams
  • Roland Füss


In the current stand of literature on the rental adjustment process starting with Hendershott et al. (Real Estate Economics, 30, 165-183, 2002a, Journal of Real Estate Finance and Economics, 24, 59-87, 2002b) it has become practice to treat the compound variable “occupied stock” as a supply variable. In this study we show that this variable deserves a more critical investigation and that the general view of a supply variable may be misleading. Using panel data covering 30 urban areas for 17 years, we investigate the rental adjustment process in the German office market. The application of recently developed cointegration techniques for non-stationary panel data in conjunction with the corresponding error correction model (ECM) enables us to overcome the data limitations, particularly existent for most European real estate markets. Hence, our primary motivation is (a) to demonstrate how “occupied stock” should be interpreted correctly and (b) to provide useful insights into the long-term relationships and short-run dynamics of real office prime rents. The empirical evidence suggests that a one percent rise in office employment increases real rents on average by 1.64% through higher demand for office space. On the other hand, a one percent increase in the supply of office space decreases real rents in the long run by 2.25%. The results from the error correction model show that deviations from the long-run equilibrium lead to an adjustment process which restores equilibrium within approximately 3 years.


Panel cointegration analysis FMOLS regression Error Correction Model Urban rent models German office market 

JEL Classification

C22 C23 G12 L85 R



The authors are grateful to Thomas Voßkamp from BulwienGesa AG for providing the data and Peter Pedroni for the RATS code for cointegrating vectors in panel data and helpful comments. Furthermore, we thank Heinz Rehkugler, Tobias Rombach, Nico Rottke, Matthieu Stigler, Anthony Strittmatter, Marcel Tyrell, Franziska Wenzel, Joachim Zietz, an anonymous referee, and the participants of the 2009 ARES conference and 2009 IREBS conference on real estate finance and economics for helpful suggestions on various earlier versions. We bear of course responsibility for all remaining errors.


  1. Arellano, M. (1987). Computing robust standard errors for within group estimators. Oxford Bulletin of Economics and Statistics, 49(4), 431–434.CrossRefGoogle Scholar
  2. Bhattacharjee, A., & Jensen-Butler, C. (2005). A model of regional housing markets in England and Wales. Working Paper, University of St. Andrews.Google Scholar
  3. Breitung, J., & Das, S. (2005). Panel unit root tests under cross sectional dependence. Statistica Neerlandica, 59(4), 414–433.CrossRefGoogle Scholar
  4. Blank, D. M., & Winnick, L. (1953). The structure of the housing market. Quarterly Journal of Economics, 67(2), 181–203.CrossRefGoogle Scholar
  5. Case, K. E., & Shiller, R. J. (1989). The efficiency of the market for single-family homes. American Economic Review, 79(1), 125–137.Google Scholar
  6. Case, K. E., & Shiller, R. J. (1990). Forecasting prices and excess returns in the housing market. AREUEA Journal, 18(3), 253–273.Google Scholar
  7. D’Arcy, E., Tsolacos, S., & McGough, T. (1997). An empirical investigation of retail rents in five European cities. Journal of Property Valuation and Investment, 15(4), 308–320.CrossRefGoogle Scholar
  8. Dobson, S. M., & Goddard, J. A. (1992). The determinants of commercial property prices and rents. Bulletin of Economic Research, 44(4), 301–321.CrossRefGoogle Scholar
  9. Engle, R. F., & Granger, C. W. J. (1987). Co-integration and error-correction: representation, estimation and testing. Econometrica, 55(2), 251–276.CrossRefGoogle Scholar
  10. Englund, P., Gunnelin, A., Hendershot, P., & Söderberg, B. (2008). Adjustment in property space markets: taking long-term leases and transaction costs seriously. Real Estate Economics, 36(1), 81–109.CrossRefGoogle Scholar
  11. Gardiner, C., & Henneberry, J. (1988). The development of a simple regional model of office rent prediction. Journal of Property Valuation & Investment, 7(1), 36–52.CrossRefGoogle Scholar
  12. Gardiner, C., & Henneberry, J. (1991). Predicting regional office rents using habit-persistence theories. Journal of Property Valuation & Investment, 9(3), 215–126.CrossRefGoogle Scholar
  13. Giussani, B., & Tsolacos, S. (1993). The office market in the UK: Modeling the determinants of rental values. International Real Estate Research Session of the 1993, ASS/AREUEA Conference. Anaheim. CA, January.Google Scholar
  14. Giussani, B., Hsia, M., & Tsolacos, S. (1993). A comparative analysis of major determinants of office rental values in Europe. Journal of Property Valuation and Investment, 11(2), 157–173.CrossRefGoogle Scholar
  15. Geltner, D. M., & Miller, N. G. (2000). Commercial real estate analysis and investments. Upper Saddle River: Prentice Hall.Google Scholar
  16. Gonzales, J., & Pitarakis, J.-Y. (2006). Threshold effects in cointegrating relationships. Oxford Bulletin of Economics and Statistics, 68(1), 813–833.CrossRefGoogle Scholar
  17. Hanck, C. (2008). An intersection test for panel unit roots. Working Paper, University of Dortmund.Google Scholar
  18. Hekman, J. S. (1985). Rental price adjustment and investment in the office market. Journal of the American Real Estate and Urban Economic Association (AREUEA), 13(1), 32–47.CrossRefGoogle Scholar
  19. Hendershott, P. H. (1997). Uses of equilibrium models in real estate research. Journal of Property Research, 14(1), 1–13.CrossRefGoogle Scholar
  20. Hendershott, P. H., Lizieri, C. M., & Matysiak, G. A. (1999). The workings of the London office market. Real Estate Economics, 27(2), 165–183.CrossRefGoogle Scholar
  21. Hendershott, P. H., MacGregor, B. D., & Tse, R. Y. C. (2002). Estimation of the rental adjustment process. Real Estate Economics, 30(2), 165–183.CrossRefGoogle Scholar
  22. Hendershott, P. H., MacGregor, B. D., & White, M. (2002). Explaining commercial rents using an error correction model with panel data. Journal of Real Estate Finance and Economics, 24(1), 59–87.CrossRefGoogle Scholar
  23. Hort, K. (1998). The determinants of urban house price fluctuations in Sweden 1986–1994. Journal of Housing Economics, 7(2), 93–120.CrossRefGoogle Scholar
  24. Im, K., Pesaran, H. & Shin, Y. (1997). Testing for unit roots in heterogeneous panels, Discussion Paper, University of Cambridge, June.Google Scholar
  25. Ke, Q., & White, M. (2009). An econometric analysis of shanghai office rents. Journal of Property Investment & Finance, 27(2), 120–139.CrossRefGoogle Scholar
  26. Levin, A. & Lin, C.F. (1993). Unit Root Test in Panel Data: Asymptotic and Finite Sample Properties. University of California at San Diego, Discussion Paper No. 92-93.Google Scholar
  27. Matysiak, G., & Tsolacos, S. (2001). Identifying short-term leading indicators for real estate performance. Journal of Property Investment & Finance, 21(3), 212–32.CrossRefGoogle Scholar
  28. McGough, T., & Tsolacos, S. (1994). Forecasting office rental values using vector autoregressive models. The Proceedings of the Cutting Edge Property Research Conference, Royal Institution of Chartered Surveyors, London, September, 303-20.Google Scholar
  29. Moon, H. R., & Perron, B. (2004). Testing for a unit root in panels with dynamic factors. Journal of Econometrics, 122(1), 81–126.CrossRefGoogle Scholar
  30. Mourouzi-Sivitanidou, R. (2002). Office rent processes: the case of U.S. metropolitan markets. Real Estate Economics, 30(2), 317–44.CrossRefGoogle Scholar
  31. Pedroni, P. (1995). Panel cointegration; Asymptotic and finite sample properties of pooled time series tests, with an Application to the PPP Hypothesis. Indiana University Working Papers in Economics, No. 95-013, June.Google Scholar
  32. Pedroni, P. (1996). Fully modified OLS for heterogeneous cointegrated panels and the case of purchasing power parity. Indiana University Working Paper in Economics No. 96-020.Google Scholar
  33. Pedroni, P. (1999). Critical values for cointegration tests in heterogeneous panels with multiple regressors. Oxford Bulletin of Economics and Statistics, 61(s1), 653–670.CrossRefGoogle Scholar
  34. Phillips, P. C. B., & Moon, H. (1999). Linear regression limit theory for nonstationary panel data. Econometrica, 67(5), 1057–1111.CrossRefGoogle Scholar
  35. Phillips, P. C. B., & Sul, D. (2002). Dynamic panel estimation and homogeneity testing under cross section dependence. The Econometrics Journal, 6(1), 217–259.CrossRefGoogle Scholar
  36. Pollakowski, H., Wachter, S., & Lynford, L. (1992). Did office market size matter in the 1980s? A time-series cross-sectional analysis of metropolitan area office market. Journal of the American Real Estate and Urban Economic Association (AREUEA), 20(2), 303–24.Google Scholar
  37. Quah, D. (1994). Exploiting cross-section variation for unit root inference in dynamic data. Economics Letters, 44(1-2), 9–19.CrossRefGoogle Scholar
  38. Rosen, K. (1984). Toward a model of the office building sector. Journal of the American Real Estate and Urban Economic Association (AREUEA), 12(3), 261–69.CrossRefGoogle Scholar
  39. Scott, P., & Judge, G. (2000). Cycles and steps in British commercial property values. Applied Economics, 32(10), 1287–98.CrossRefGoogle Scholar
  40. Simes, R. J. (1986). An improved bonferroni procedure for multiple tests of significance. Biometrika, 73(3), 751–754.CrossRefGoogle Scholar
  41. Smith, L. B. (1974). A note on the price adjustment mechanism for rental housing. American Economic Review, 64(3), 478–481.Google Scholar
  42. Tsolacos, S., Keogh, G., & McGough, T. (1998). Modeling use, investment, and development in the Britain office market. Environment and Planning A, 30, 1409–27.CrossRefGoogle Scholar
  43. Wheaton, W. C. (1987). The cyclic behavior of the national office market. Journal of the American Real Estate and Urban Economic Association (AREUEA), 15(4), 281–99.CrossRefGoogle Scholar
  44. Wheaton, W. C., & Torto, R. G. (1988). Vacancy rates and the futures of office rents. Journal of the American Real Estate and Urban Economic Association (AREUEA), 16(4), 430–36.CrossRefGoogle Scholar
  45. Wilson, P. J., & Okunev, C. (1999a). Spectral analysis of real estate and financial assets markets. Journal of Property Investment and Finance, 17(1), 61–74.CrossRefGoogle Scholar
  46. Wilson, P. J., & Okunev, C. (1999b). Long-term dependencies and long-run non-periodic co-cycles: real estate and stock markets. Journal of Real Estate Research, 18(2), 257–78.Google Scholar
  47. Wilson, P. J., & Zurbruegg, R. (2003). Common trends and spectral response: a case study on the US. Journal of Property Research, 20(1), 1–22.CrossRefGoogle Scholar
  48. Wilson, P. J., Ellis, C., & Higgins, D. M. (2000). Comparing univariate forecasting techniques in property markets. Journal of Real Estate Portfolio Management, 6(3), 283–306.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.European Business SchoolOestrich-WinkelGermany

Personalised recommendations