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This paper aims to propose a new valuation method for income producing properties. The model originally called cyclical dividend discount models (d’Amato, 2003) has been recently proposed as a family of income approach methodologies called cyclical capitalization (d’Amato, 2013; d’Amato, 2015; d’Amato, 2017).

The proposed methodology tries to integrate real estate market cycle analysis and forecast inside the valuation process allowing the appraiser to deal with real estate market phases analysis and their consequence in the local real estate market.

The findings consist in the creation of a methodology proposed for market value and in particular for mortgage lending determination, as the model may have the capability to reach prudent opinion of value in all the real estate market phase.

Research limitation consists mainly in a limited number of sample of time series of rent and in the forecast of more than a cap rate or yield rate even if it is quite commonly accepted the cyclical nature of the real estate market.

The implication of the proposed methodology is a modified approach to direct capitalization finding more flexible approaches to appraise income producing properties sensitive to the upturn and downturn of the real estate market.

The model proposed can be considered useful for the valuation process of those property affected by the property market cycle, both in the mortgage lending and market value determination.

These methodologies try to integrate in the appraisal process the role of property market cycles. Cyclical capitalization modelling includes in the traditional dividend discount model more than one g-factor to plot property market cycle dealing with the future in a different way. It must be stressed the countercyclical nature of the cyclical capitalization that may be helpful in the determination of mortgage lending value. This is a very important characteristic of such models.

The purpose of this study is providing a possible methodological solution to the valuation of cyclical.assets. International Valuation Standards introduce a brand new definition of property: the cyclical asset (International Valuation Standards Council 2017, IVS 105, p. 39 and p. 41). Among different property valuation methods, normally this kind of properties is appraised using income approach. In this group of methodology, the opinion of value is based on a proportional relationship between property value and rent. In the past years, a group of methods called cyclical capitalization has been proposed (d’Amato, 2003; d’Amato, 2013;d’Amato, 2015; d’Amato, 2017a; d’Amato 2017 b; d’Amato, 2017c). This method proposes an integration between property valuation and property market cycle.

Cyclical capitalization method is applied using a time series of property market rent of offices in prime location in the South Bank area in London. It consists of the determination of more than one all-risk yield to reproduce the property market cycle.

A comparison between the cyclical capitalization and two traditional capitalization rate shows how the proposed model is able to provide a stable opinion of value.

The method may represent a contribution for the determination of the value of cyclical assets or for the mortgage lending value.

This paper provides the possibility to have a property valuation method less sensitive to upturn and downturn of the property market.

The valuation based on cyclical capitalization are less sensitive to the upturn and the downturn of the market.

It is one of the first scientific paper addressing the problem of the determination of the value of cyclical assets.

The paper is motivated by the paucity of empirical research on the determinants of capitalisation rates/yield in the commercial property market. Compared to property price determinants, the capitalisation rate has received significantly less attention. This is somewhat surprising given that the capitalisation rate is a more insightful indicator for investors on commercial property market performance than merely price changes or trends. The capitalisation rate, measured as the ratio of net operating income to the property’s capital value, captures the asset’s overall ability to generate income which is crucial for investors who typically invest in property for their income-generating capacity. The purpose of this paper is to address these issues.

To evaluate the determinants of capitalisation rates, time series analysis was used. The data capture performance in the Australian commercial property market between 2005 and 2018. All macroeconomic and financial data are freely available from official sources such as the Australian Bureau of Statistics and the nation’s central bank. Methodology wise, given the problematic nature of the data such as a mixed order of integration and the possibility of cointegration amongst some of the I (1) variables, the autoregressive distributed lag model was selected given its flexibility and relative lack of assumptions.

Bond rates, market risk premiums, stock market excess returns and other macroeconomic variables were found to drive capitalisation rates of Australian commercial properties. A 1% increase in the bond rate results in approximately 0.3–2.4% increase in capitalisation rates depending on the sub-market. Further, a 1% increase in excess market returns results in a 0.01–0.02% increase in capitalisation rates. Regarding risk premiums, a 100 basis point increase in the BBB spread results in approximately 0.92–1.27% reduction in cap rates in certain markets.

Asset managers will find these results useful in asset allocation strategies. Commercial properties offer attractive investment qualities such as yield stability in periods of economic uncertainty while allowing for the possibility of capital growth through appreciation of the underlying asset. By understanding the factors that affect the capitalisation rate, practitioners may predict emerging trends and identify threats to portfolio return and stability. This allows better integration of commercial property in the construction of portfolios that remain robust in a variety of market conditions.

The contribution to literature is significant given the lack of similar studies in the Australian market. The performance of real estate assets using cap rates as a comparative measure to equities and bonds influences decisions in asset allocation strategies. It provides crucial information for investors to estimate the performance of commercial property. This research supports the notion that both space and capital market indicators jointly affect capitalisation rates. The findings expand the knowledge base relating to commercial properties and validate the assessments of investors, developers and valuers who utilise yield as a performance benchmark for asset allocation strategies.

The purpose of this paper is to extend the studies of commercial property yields by providing a cross-field approach through the implementation of methods used in physics.

Based on the equations used to describe real gases in physics, the commercial property yields are expressed through a model, as a product of two terms. The first term estimates the influence of the income change and investment on yields. The second estimates the yield variation as a function of property size. Additionally, the model combines the macroeconomic and microeconomic components influencing yield adjustment. Calculation of each component involves procedures developed in physics, with the investment volume being linked to the amount of gas and the microeconomic yield being linked to the gas compressibility.

The model was applied to the Auckland office and industrial markets, both to the historic and current cycle. At the macro-level, it was found that the use of accumulation of investment over a relevant cycle, results in a high data to model correlation. When modelling the yields at the micro-level, a relationship between the outlying properties and the yield softening was observed.

The paper provides an enhanced modelling power through association of the cyclic and investment activity with the yield change. Moreover, the model may be used to decouple the local and the international investment components and the extent of their influence on the local property market. Furthermore, it may be used to estimate the influence of the property size on the yield.

This research provides a new cross-field application of modelling techniques and enhances the understanding of factors influencing yield adjustments.

Establishing the strength of a novel variable–mortgage debt as a fraction of US gross domestic product (GDP)–on forecasting capitalisation rates in both the US office and multifamily sectors.

The authors specify a vector error correction model (VECM) to the data. VECM are used to address the nonstationarity issues of financial variables while maintaining the information embedded in the levels of the data, as opposed to their differences. The cap rate series used are from Green Street Advisors and represent transaction cap rates which avoids the problem of artificial smoothness found in appraisal-based cap rates.

Using a VECM specified with the novel variable, unemployment and past cap rates contains enough information to produce more robust forecasts than the traditional variables (return expectations and risk premiums). The method is robust both in and out of sample.

This has direct implications for governmental policy, offering a path to real estate price stability and growth through mortgage access–functions largely influenced by the Fed and the quasi-federal agencies Fannie Mae and Freddie Mac. It also offers a timely alternative to interest rate-based forecasting models, which are likely to be less useful as interest rates are to be held low for the foreseeable future.

This study offers a new and highly explanatory variable to the literature while being among the only to model either (1) transactional cap rates (versus appraisal) (2) out-of-sample data (versus in-sample) (3) without the use of the traditional variables thought to be integral to cap rate modelling (return expectations and risk premiums).

The purpose of this paper is to assess US-based firms from 2005 to 2015 to determine whether firms with better corporate social responsibility (CSR) performance will allocate capital through their life-cycle to better maintain or extend total assets.

Kinder, Lydenberg, Domini Research & Analytics social performance rating scores were used to measure CSR performance in an initial sample of 19,707 firm-year observations. Firms are first classified into stages including introduction, growth, maturity, and decline, and use multiclass linear discriminant analysis, the Dickinson classification scheme (Dickinson, 2011), and the ratio of retained earnings to total assets (RETA) as life-cycle proxies. Life-cycle was formulated based on a broad set of accounting data sourced from Compustat. Various corporate characteristics from the CRSP database were used to classify all sample firms into five equal groups based on their CSR performance.

A firm’s equity and debt issuance assume a hump shape over the life-cycle under CSR practice, and higher-CSR firms face fewer significant issues as they mature; payout, RETA, and free cash flow decreased from high-CSR performance firms to low-CSR performance firms; and cash holdings also exhibit a hump shape over the life-cycle and higher-CSR practices are associated with significantly lower cash holdings.

CSR performance is a useful predictor for forecasting firm life-cycle and superior CSR performance ensures efficient capital allocation throughout firm life-cycle. Furthermore, CSR practice is an indicator of firm life-cycle sustainability and indicates a firm’s future cash flow patterns.

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.

Off-site manufacturing (OSM) application in vertically higher and spatially larger projects within Western Australian (WA) commercial sector has demonstrated the potential of benefitting from such a construction technique, but introducing a new methodology to a traditional sector such as commercial sector is not always straightforward. The acceptance of the new methodology, level of awareness of the stakeholders involved and the readiness of the supply chain to deliver, for instance, may influence the success of its implementation. Given the infancy of such methodology in the WA construction industry, this research project aims to analyse factors influencing the implementation of OSM construction method in WA.

Following a thorough literature review, an existing research agenda in OSM was used to inform the direction of this research, i.e. focussing on external macro aspects of the decision making to implement OSM. Three projects in WA were studied, and the data collection was facilitated through archival study and semi-structured interviews with construction practitioners who were the stakeholders of the three projects. Data analysis was conducted through content analysis to draw the findings and conclusion of this research.

The analysis of the studied cases revealed relevant economic/financial, technological and regulatory factors, as well as social factors influencing the implementation of OSM, particularly in WA commercial projects. These findings were then used to develop an overall understanding of the external macro factors influencing decision making in implementing OSM that forms a formal research agenda aimed at enabling successful implementation of OSM in WA construction industry, particularly in its commercial sector.

The research findings presented in this paper identified factors that significantly influence the implementation of such alternative technology in a traditional sector. These factors were then structured to form the subsequent research agenda to continuously pursue the implementation of OSM in the sector. While the research agenda takes into account the unique characteristics of the WA construction industry, it contributes to the global and the Australian national research agenda, and the research methodology reported in this paper can be used to develop similar research agenda elsewhere.