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After the Global Financial Crisis in 2008, the impact of expanded liquidity in the financial market has drawn attention. The purpose of this paper is to examine the relationship between liquidity in financial markets and office markets across Asian countries. In particular, the research not only examines the effect of normal liquidity on real estate markets, but also the effects of excess liquidity are specifically highlighted.

This paper uses panel estimation utilizing quarterly data from the first quarter of 2007 to the fourth quarter of 2015. Taking both time and location dimensions into account allows for a more precise estimate of the relationship between liquidity and office market’s yields.

Per the empirical outcome, an increasing excess liquidity tends to decelerate the value of office yields in six major Asian office market centers due to the positive effect on commercial real estate value. This effect is also identified by comparing the difference between the level of fitted yields and actual yields.

The results enhance the understanding of commercial real estate yield determinants. Furthermore, the results can be used to assess the impacts of liquidity on major office markets in Asia.

This paper attempts to uncover the impact of liquidity in financial markets on the office market yields. To better understand the relationship, the concept of excess liquidity is adopted and further exploration of each office market is conducted by comparing the fitted yields, which is computed considering the effects of excess liquidity on yield levels and actual yields.

This study aims to examine the impact of “space-as-a-service” (SAAS) provision on office rents in the UK and quantify premia to office rents.

Using hedonic modelling techniques the authors are able to quantify the impact of a number of SAAS features on office rents in the City of London using CoStar data. The authors control for the quality of the buildings by focussing on five-star buildings, rated by CoStar, as these buildings are more likely to incorporate SAAS features.

Using data on 317 transactions in 37 City of London Office buildings over the period 1 November 2004–15 July 2020, the authors find that tenant exclusive mobile applications (MAPPS) and a public terrace or rooftop command a rent premium of around £13 and £6.5 per sq. ft per annum, respectively. However, other SAAS features such as conferencing facilities, on-site fitness centre and touch down space have no significant impact on office rents. The impact of exclusive MAPPS varies with size of net lettable area.

The SAAS real estate model is an emerging trend in the office market. As it grows in importance more research questions will have to be investigated. The present study raises awareness of the need to specify SAAS features and form a rating system that will facilitate future research on the subject.

The conclusion from the present investigation is that only two SAAS features have a positive impact on office (tenant exclusive mobile apps and a public terrace or rooftop), which suggest that these two features may form the basis of any future SAAS rating system. These two SAAS components should carry more weight in valuations and pricing.

To the best of the authors’ knowledge, this is the first study that attempts to quantify the impact of SAAS features on office rents.

This paper offers empirical evidence on factors influencing credit spreads on commercial mortgage loans. It extends existing work on the pricing of commercial mortgage loans. The authors examine the relative significance of a range of factors on loan pricing that are lender, asset and loan specific. The research explores and quantifies the sources of spread differentials among commercial mortgage loans. The paper contributes to a limited literature on the subject and serves the purpose of price discovery in commercial property lending. It offers a framework to compare actual pricing with fundamental-based estimates of loan spreads.

Panel analysis is deployed to examine the cross-section and time-series determinants of commercial mortgage loan margins and credit spreads. Using an exclusive database of loan portfolios in the United Kingdom (UK), the panel analysis enables the authors to analyse and quantify the impact of a number of theory-consistent and plausible factors determining the cost of lending to commercial real estate (CRE), including type and origin of lender, loan size, loan to value (LTV) and characteristics of asset financed – type, location and grade.

Spreads on commercial mortgages and, therefore, loan pricing differ by the type of lender – bank, insurance company and debt fund. The property sector is another significant risk factor lenders price in. The LTV ratio has increased in importance since 2012. Prior to global financial crisis (GFC), lenders made little distinction in pricing different LTVs. Loans secured in secondary assets command a higher premium of 50–60bps. The analysis establishes an average premium of 35bps for loans advanced in regions compared to London. London is particularly seen a less risky region for loan advancements in the post-GFC era.

The study considers the role of lender characteristics and the changing regulation in the pricing of commercial mortgage loans and provides a framework to study spreads or pricing in this market that can include additional fundamental influences, such as terms of individual loans. The ultimate aim of such research is to assess whether mortgage loans are correctly priced and spotting risks emanating from actual loan spreads being lower than fundamental-based spreads pointing to tight pricing and over-lending.

The analysis provides evidence on lender criteria that determine the cost of loans. The study confirms that differences in regulation affect loan pricing. The regulatory impact is most visible in the increased significance of LTV. In that sense, regulation has been effective in restricting lending at high LTV levels.

The paper exploits a database of a commercial mortgage loan portfolio to make loan pricing more transparent to the different types of lender and borrowers. Lenders can use the estimates to assess whether commercial loans are fairly priced. Borrowers better understand the relative significance of risk factors affecting margins and the price they are charged. The results of this paper are of value to regulators as they can assist to understand the determinants of loan margins and gauge conditions in the lending market.

Presents an empirical investigation of office rental trends for some of the largest cities in Europe. Uses annual data for the period 1983‐91 to test the changes in rental values and fluctuations in economic activity. Includes a review of previous office market studies and an assessment of the research direction and information requirements of current European property research. Suggests that European rental values are determined by similar demand‐side variables and, in particular, real gross domestic product (GDP).

The paper seeks to evaluate accuracy and efficiency of consensus forecasts for all property rents and total returns in the UK. The aim of the paper is to investigate whether consensus forecasts, containing a high degree of judgement, are better than forecasts produced by uncomplicated time‐series and econometric models that practitioners can easily estimate and use for forecasting.

This study estimates simple models of all property rents and returns and generates forecasts for one‐ and two‐year horizons on a rolling basis over the period 1999 to 2004. These forecasts are real time forecasts. That is they are made using information available to the analyst at the time of the forecast each year and no future knowledge is assumed. The forecasts made by these models are compared with the corresponding consensus forecasts. The comparative assessment is based on conventional tests for bias, variability and efficiency of forecasts.

If attention is focused on rents, the consensus forecast is ranked best for the one‐year horizon but it is outperformed by the regression model and a combination of the statistical models for the two‐year horizon. For the one‐year and two‐year forecasts of total returns a simple regression model with interest rates clearly improves upon the consensus forecasts. There is clear evidence that the consensus forecasts fail to incorporate the information contained in recent interest rate movements. Therefore subject to the sample period for this analysis the survey forecasts of total returns cannot be considered impartial. Analysts should include base rate information into their predictions.

This is one of the few attempts to formally evaluate consensus forecasts in the real estate field and perform a direct comparison with quantitative forecasts. It produces initial evidence suggesting that highly judgemental consensus forecasts do not necessarily outperform quantitative forecasts based on fundamentals. It prompts property forecasters and investors to engage in forecast evaluation and include missing information and past errors in their forecasts.

This paper looks at the application of economic and financial series in forecasting IPD monthly rental series. The approach follows that employed in classical business cycle work that seeks to decompose series into trend, cyclical and noise components and is the first time that it has been applied to IPD monthly data. Trend extraction is obtained by means of the Hodrick‐Prescott filter. Several potential indicator series are investigated together with their lead characteristics. The short‐term forecasts of these series are compared with naïve methods and a composite indicator. The results show the naïve methods, especially the Holt‐Winters method, and certain leading indicator series produce satisfactory short‐term forecasts, but the success is both sector and time‐dependent. This suggests that it is a worthwhile endeavour in identifying potential leading indicator series. The methodology presented in this paper should be seen as complementing existing approaches that employ standard econometric procedures in modelling rental growth.

The aim of the present study is to assess the significance of cash flow and profitability survey data in the modelling and forecasting of industrial rents. These data, taken from the British Chambers of Commerce regional surveys of the manufacturing sector, are used as a partial proxy for the affordability of industrial space occupiers. In the absence of direct profitability measures existing studies approximate this information indirectly through output and to some extent employment variables.

A cross‐section time‐series framework is deployed to model regional industrial rents using a set of output and employment variables. The empirical model is subsequently augmented with the inclusion of the cash flow and profitability measures.

Consistent with the findings of existing studies, changes in output are a significant influence on the variation of real industrial rents. Supportive evidence for turnover and profitability is found in four regions. In these regions cash flow variables contain additional information and improve the forecast performance of the base model. The empirical findings also extend to obtaining estimates after the BCC survey data are normalised with respect to the overall growth and the input costs manufacturers face in each of the regions.

The present study extends existing work on industrial rents by introducing more direct turnover and profitability series. Greater use of such series in property performance forecasting over short‐term horizons has the potential of resulting in smaller errors.

The aim of this paper is to forecast the office property returns in Helsinki CBD using both short‐run and long‐run econometric specifications. Real economy, monetary and financial market indicators are included in these specifications to explain the variation in office property returns and forecast them. The paper illustrates the steps that analysts can follow to select models based on common diagnostics criteria and ex post forecasting evaluation tests. The findings of this research are in accordance with the results of previous comparative research in Europe and suggest that the growth of the gross domestic product in Finland is a key variable for modelling and forecasting office property returns in Helsinki. Moreover, the analysis indicated that information from a long‐run relationship of the gross domestic product and the real office return index should be monitored in the future as a way of improving the forecasts through an error correction model. It is predicted that Helsinki office returns will show a growth of about 7.1 per cent on average in the period 1999‐2001.

Presents the findings of the first comparative econometric investigation into the influence of demand side forces on retail rent determination in European cities. Examines five major retail centres ‐ Amsterdam, Brussels, Hamburg, London and Paris ‐ over the period 1980 to 1994. Estimates for each city a theory consistent model which tests influences of GDP, retail sales and consumer expenditure on changes in retail rents. Univariate and multivariate regressions show that the relative explanatory capabilities of these influences exhibit a notable degree of variation between the cities. A time series cross‐sectional analysis demonstrates that contemporaneous changes in GDP are the most important common determinant of retail rents across the cities and that the process of rent determination in Paris is influenced by different structural factors from the other cities examined.