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The purpose of this study is to estimate an empirical model for new office space development starts, based on the theoretical treatment of urban growth. The study introduces a new parameter, namely, office space-usage pattern, to the office space development equation and tests whether developers respond to non-price measures in deciding to commence new developments.

The study first introduces a co-integration approach based on an error correction model to test for long-run relations and short-run dynamics of new office space development. A multivariate regression model is then introduced to identify significant determinants that influence office development starts. The study uses annual data over a time span of 30 years.

Estimated results provide strong evidence that the newly introduced parameter exerts a positive impact on new office space development. It suggests that if the average floor space per employee changes by one percentage point, new office development starts would change by 1.5 percentage point, indicating even a marginal change in floor-space usage per employee (SPE) would have a significant impact on new office space development. Empirical estimates also suggest a strong response of office development starts to the lagged land supply and office space stock.

The paper raises the concern about the importance of non-price measures of the supply-side of the office market. There is scope to address the research questions using better data sets. It is also possible to model the supply adjustment process more dynamically in an error correction framework.

The findings would suggest that non-price measures, such as space-usage pattern, need to be taken into account when planning and estimating future office space needs. This finding provides valuable insight for our current knowledge on factors affecting new office supply.

This is the first study to introduce office floor space usage as a determinant of office development starts in an urban growth conceptual framework for the Hong Kong office market.

The purpose of this paper is to examine the structure and dynamics of Singapore's Central Area office market. A long-run equilibrium relationship is tested and a short-run adjustment error correction model are estimated, incorporating appropriate serial error correction. The long-run equation is estimated for office rent, with office employment and available stock.

With the vector error correction model (VECM), the lagged rent, available stock, office employment, vacancy and occupied stock (OS) can impact the rental adjustment process. Equilibrium rent on the whole reacts positively to lagged rents, available stock, office employment, OS and negatively to vacancy rates (VC). Past levels of positive change in VC and rental growth can have negative effects on current OS.

While good economic conditions signaled by increases in rents increase the supply of new stock (available space), higher rents and VC dampen the long-term occupied space (space absorption) in accordance with economic theory. Available stock can be forecasted by past rent and absorption levels owing to the developer's profit-driven nature.

An understanding of the interaction between the macroeconomic variables and the Central Area office market is useful to domestic and foreign investors and developers, who then can better evaluate their decision making in commercial real estate investment and development projects.

It is implicit that the Singapore Central Area office market requires at least a year before any rental increase can potentially dampen the space demanded. Firms are attracted to locate there owing to agglomeration economies and they are willing to pay premium office rents in conjunction with office space intensification in the Central Area. Newly built space is positively affected by past rents. Urban Redevelopment Authority and private real estate developers should be wary of excess office sector vacancies by avoiding over supply, even though an increase in the supply of office space in the Central Area can have a positive impact on office rent in the longer term. Most of the office space development would tend to meet the demand in the long run. Rental stickiness is exemplified as rental changes are affected by lagged rent.

Policy makers are better enabled to stabilize the office sectors of the real estate market if so required.

The paper adopts the VECM and validated by empirical evidence, to investigate the long-run equilibrium relationship and short-term corrections underlying the dynamics of the Singapore Central office market. Delay in the restoration of equilibrium in real estate markets is attributed to factors like lease terms and supply lags.

Office markets and particularly international financial centres over the past decade have experienced rapid financialisation, developments and indeed changes in the post-global financial crisis (GFC) landscape. Importantly, the volume and types of international capital flows have witnessed more foreign actors and vehicles entering into the investment landscape with the concentration of investment intensifying within key financial centres. This paper examines the interaction of international real estate capital flows in the London, New York and Tokyo office markets between 2007 and 2017.

Using Real Capital Analytics (RCA) data comprising over 5,700 office property transactions equating to $563bn between 2007 and 2017, the direct global capital flows into the London, New York and Tokyo office markets are assessed using an autoregressive distributed lag (ARDL) approach. Further, Granger causality tests are examined to analyse the short-run interaction of international real estate capital flows into these three major office markets.

By assessing the relativity of internal to external investments in these three central business district (CBD) office markets, differences in market dynamics are highlighted. The London office market is shown to be highly dependent on international flows and the USA, the foremost source of cross-border investment on the global stage. The cointegration and causality analysis indicate that cross-border real estate investment flows in these markets (and financial centres) show both long- and short-run relationships and suggest that the London office market remains more distinct and the most reliant on international capital flows with a wider geographical spread of investment activities and investor types. In the case of New York and Tokyo, these markets appear to be driven by more domestic investment activity and capital seemingly due to subtle factors pertaining to investor home bias, risk aversion and diversification strategies between the markets in the aftermath of the GFC.

Given the importance of the CBD offices in London, New York and Tokyo as an asset class for institutional investors, this paper provides some insights as to their level of connection and the interaction of the international capital flows into these three major cities.

Using a data set comprising 16 European office markets provided by the DTZ Research Institute from Q1 2003 to Q4 2013, the purpose of this paper is to measure the strength of the unconditional transmission of volatility in the returns to direct property between 16 European office markets with the objective of determining the degree of unconditional spillover between markets.

To examine volatility spillovers across the 16 office markets, the authors adopted the generalized VAR methodology, variance decomposition and the generalized spillover index of Diebold and Yilmaz (2012) by measuring cross-office market volatility transmission in asset pricing through estimates of several “volatility spillover indices.”

Volatility spillovers are important and time-varying across the leading office markets, with cross-market volatility interaction being bi-directional and of relative endogenous nature for many markets. The London office market is the “volatility leader” and has exerted significant net volatility influence on the other markets. Additionally, the volatility spillovers between business cycle fluctuations and asset market cycle volatilities are linked across some European economies.

Evidence of co-integration among the domestic volatility spillover cycles implies the presence of unobserved common shocks and might not be good news for international investors who pursue diversification strategies in European office real estate markets.

No previous study has addressed formally the measurement and assessment of the nature and intensity of volatility spillovers across direct office markets on such a broad range of European office markets. The relevance of the topic has been even increasing over the previous years as more and more investors seek for flexibility and participation in the investment process and asset management.

According to normative‐rational investment decision models, investors who seek office buildings should select markets which show high employment numbers in office related sectors such as Finance, Insurance, Real Estate (FIRE) and Knowledge Intensive Business Services (KIBS). This view is challenged by behavioural studies, which find that the investors' willingness for analysis and the structure of their decision‐making processes in practice notably limit such an influence. Looking at German office markets, the purpose of this paper is to explore to what extent the aforementioned connection between employment structure and market selection holds.

Qualitative interviews with German investment experts are analysed in a manner that differentiates between investor types. Behavioural economics form a theoretical basis to identify investor type specific attitudes towards investment markets and the resulting market selection processes. The findings are tested by logistic regressions which connect the spatial structure of office investments with employment data.

A sector‐specific employment structure does not have a direct but an indirect influence on the market selection. The existing theoretical contradiction is resolved by this indirect influence. Investor type specific risk profiles and business models determine varying spatial patterns of market selection.

The study shows that attitudes towards markets, business logics and decision processes differ between insurance companies and open‐ended funds. Researchers should be aware that empirical results may not always be valid for all institutional investors. In some cases a differentiating research design according to investor type may be necessary.

The study identifies a set of minimum requirements with regard to building and market characteristics open‐ended funds use for filtering in German secondary/regional markets. Market selection by these funds and insurance companies correlates with relative employment in FIRE‐ and KIBS‐branches.

This paper overcomes decision‐theoretical contradictions and gives empirical evidence for the importance of the employment structure on market selection.

Automated valuation models (AVMs) are statistical asset pricing models omnipresent in residential real estate markets, where they inform property tax assessment, mortgage underwriting and marketing. Use of these asset pricing models outside of residential real estate is rare. The purpose of the paper is to explore key characteristics of commercial office lease contracts and test an application in estimating office market rental prices using an AVM.

The authors apply a semi-log ordinary least squares hedonic regression approach to estimate either contract rent or the total costs of occupancy (TOC) (“grossed up” rent). Furthermore, the authors adopt a training/test split in the observed leasing data to evaluate the accuracy of using these pricing models for prediction. In the study, 80% of the samples are randomly selected to train the AVM and 20% was held back to test accuracy out of sample. A naive prediction model is used to establish accuracy prediction benchmarks for the AVM using the out-of-sample test data. To evaluate the performance of the AVM, the authors use a Monte Carlo simulation to run the selection process 100 times and calculate the test dataset's mean error (ME), mean absolute error (MAE), mean absolute percentage error (MAPE), median absolute percentage error (MdAPE), coefficient of dispersion (COD) and the training model's r-squared statistic (R²) for each run.

Using a sample of office lease transactions in Sydney CBD (Central Business District), Australia, the authors demonstrate accuracy statistics that are comparable to those used in residential valuation and outperform a naive model.

AVMs in an office leasing context have significant implications for practice. First, an AVM can act as an impartial arbiter in market rent review disputes. Second, the technology may enable frequent market rent reviews as a lease negotiation strategy that allows tenants and property owners to share market risk by limiting concerns over high costs and adversarial litigation that can emerge in a market rent review dispute.

Given that planned marketing strategies and observable behaviors often are contingent on buyer and third‐party (e.g. competitor) responses, deep understanding and descriptions of the thoughts and actions of marketers need to reflect the dynamic interplay of such contingencies. The same view applies to planned organizational buying strategies and observable behaviors: buying behavior adapts through time based on information learned and marketers’ responses to requests made by the customer organization. Consequently, a two‐way, or multiple‐party, approach to theory construction is useful in particular for mapping the “if‐then” responses of the marketer’s thoughts/actions linked with the if‐then responses of buyers’ thoughts/actions through several time periods. Using in‐depth interviews and case histories of one marketing organization and 28 buying organizations related to the office furniture industry, the article illustrates descriptive modeling of the contingency dynamics in the thoughts and actions across the multiple parties involved in marketing‐buying interactions.

In this paper, it is argued that neo‐classical location theory is of limited value in conceptualising the structure of urban office markets. Rather there are sound theoretical and technical arguments for segmenting office markets into distinct submarkets. It is further argued that submarkets, rather than being based on prior knowledge of agents or researchers, should be derived empirically. As an illustration the authors use principal components analysis and cluster analysis to construct office submarkets. The results reported are based on the analysis of a unique dataset of asking rents, physical and locational characteristics of properties on the market in the cities of Glasgow and Edinburgh in the 1990s. From the empirical evidence, it is clear that different factors are important in influencing the structure of the office market in Scotland’s major urban centres.

With the marked increase in the awareness of earthquake risks following the Canterbury earthquakes, the purpose of this paper is to assess if the reassessment of risk has influenced rents for office accommodation in commercial buildings. Two contrasting office markets are examined: New Zealand’s largest market within a high-risk earthquake zone – Wellington, and the country’s largest market within a low-risk zone – Auckland.

A sample of 252 leasing transactions were collected from a proprietary database of Colliers International, one of the largest commercial brokerage firms in New Zealand. Hedonic pricing models were developed to isolate the effects of building seismic strength on office rents.

Wellington office market rents tend to increase with higher earthquake strength (New Building Standard) ratings, all other factors held equal. In contrast, rents in Auckland, a low-risk earthquake area, do not exhibit such price effects.

The study provides estimates of the economic value associated with seismic retrofits which are vital for building owners’ decision making who must weigh retrofit costs against the economic benefits of doing so.

This study provides the first empirical analysis of office rents in New Zealand and the first quantitative analysis, internationally, of the impact of earthquake risk on commercial rents.

The purpose of this paper is to investigate the role of spatial dependency in the construction of a price index for the transactions of whole office buildings. It examines transactions of office buildings over a 15-year period and addresses an under-researched area in investment property analysis.

The study examines data relating to transactions of all office buildings in the Melbourne (Australia) central business district between 2000 and 2015. The methodology uses a spatial weights matrix to construct a hedonic model, spatial error model, spatial lagged model and an office building transactional price index.

The findings confirm the existence of spatial dependency for the transactions of office buildings. In addition, incorporating the effect of spatial dependency by constructing spatial error and spatial lagged model improved the accuracy of the estimated transactional price index for office buildings.

These findings make an important contribution to the literature by highlighting the importance of the issue of spatial autocorrelation in the estimation of valuation models and price indexes for office buildings. Until now the focus has predominantly been on individual office units rather than whole office buildings, where the barrier has traditionally been access to comprehensive data. The analysis did not consider leasing details as this information is not accessible in the Australian market.

The research will assist stakeholders including valuers, investors and market regulators to improve their understanding of movements in the office property transactional market. The findings provide an insight into trends associated with the transfer of office buildings. It will assist future decisions about the location of a new office building developments in order to optimise their proximity to transport and other buildings.

The study will assist planners to ensure the location of office buildings are optimised from a social sustainability perspective. This equates to buildings located in close proximity to transport facilities and also supporting the development of office buildings in locations, which are associated with lower future risk.

The construction of an accurate and reliable property index is critically important for practitioners to understand the movement in both the property market and also in the broader economy. A substantial increase in whole office building acquisitions has been observed in recent years, especially after the 2007 Global Financial Crisis (Lizieri and Pain, 2014) although there has remained limited research undertaken in this area.