Modelling sustainable rents for estimation of long-term or fundamental values of commercial real estate. Issue 1 (2nd January 2022)

• Record Type: Journal Article
• Authors: Crosby, Neil; Devaney, Steven; Lizieri, Colin; Mansley, Nick
• Is Part Of: Journal of property research. Volume 39:Issue 1(2022)
• Page Start: 30
• Page End: 55
• Publication Date: 2022-01-02
• Subjects: Sustainable rents -- long-term value -- financial stability -- equilibrium models -- commercial real estate; Real estate business -- Great Britain -- Periodicals; Land use -- Great Britain -- Periodicals; 333.3
• DOI: 10.1080/09599916.2021.1913441
• Languages: English
• ISSNs: 0959-9916

Abstract

ABSTRACT: Commercial real estate occupier markets are analysed in the context of the debate over the role of real estate lending in financial stability and the search for long-term valuation methods to complement market value estimations. Models of sustainable rent, including a long-term trend model and an econometric equilibrium rent model, are tested to examine whether they provide early warning of upcoming corrections in real rental values. Models were estimated using rental value data for the UK and predictions of corrections from the mid-1980s through to 2018/9 and were then compared against actual real rental growth. The models were successful in identifying the occupier market crash of the 1990s and the more muted downturn of the early 2000s, but were less successful at predicting the falls in real rental value that followed the GFC in 2008/9. There is a late reaction to this downturn in estimates from the econometric model, while other approaches struggled to identify it at all. Econometric modelling of sustainable rental values is the recommended approach and could be used in conjunction with a model of sustainable cap rates to develop long-term valuations. This would aid lending decisions and provide evidence for regulators of cyclical movements in CRE markets. For the UK, there are data issues related to this recommendation, especially concerning stock data.