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1 – 10 of over 71000Tony McGough, Sotiris Tsolacos and Olli Olkkonen
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…
Abstract
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.
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The purpose of the study is to introduce modeling of common neighborhood amenities as packages, rather than as separate independent variables in a single model. Results from the…
Abstract
Purpose
The purpose of the study is to introduce modeling of common neighborhood amenities as packages, rather than as separate independent variables in a single model. Results from the standard modeling technique of including separate controls for each amenity are provided for comparison. A secondary purpose is to provide price and time‐on‐market implications for amenities in seasoned versus newly constructed properties.
Design/methodology/approach
Common neighborhood amenities are grouped according to the total amenity bundle offered by each neighborhood. Hedonic pricing, hazard modeling, and two‐stage least squares regression are used to estimate price and time‐on‐market impacts for six common amenities.
Findings
Neighborhood tennis courts, clubhouses, boating facilities, and golf courses, as well as several amenity packages, significantly impact property values. Valuation of particular amenity packages differs between newly constructed and seasoned homes. Time‐on‐market results are less convincing.
Research limitations/implications
Neighborhood amenities considered separately can produce misleading results, so amenity packages should be included in future research. Specific numerical results would not apply to other markets and perhaps not to other time periods.
Practical implications
The study offers evidence regarding which neighborhood amenities are valued most highly in newly constructed properties, which is of interest to developers. The study also offers evidence on which amenities are valued more highly in seasoned properties, which is of interest to buyers due to concerns about re‐sale values.
Originality/value
The study offers the first grouping of neighborhood amenities into packages to more closely resemble the way buyers consider amenities during the purchase decision. The study is also the first comprehensive survey of commonly‐offered neighborhood amenities.
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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…
Abstract
Purpose
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).
Design/methodology/approach
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.
Findings
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 limitations/implications
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.
Practical implications
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.
Social implications
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.
Originality/value
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.
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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.
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Practical implications
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.
Originality/value
This research provides a new cross-field application of modelling techniques and enhances the understanding of factors influencing yield adjustments.
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The purpose of this paper is to extend the studies of commercial property cycles by providing a cross-field approach to property markets modelling.
Abstract
Purpose
The purpose of this paper is to extend the studies of commercial property cycles by providing a cross-field approach to property markets modelling.
Design/methodology/approach
The approach allows for the incorporation of market shocks into the property cycle model as fundamental building blocks; assessment of overall market absorption generated through cyclic activity; and timing estimation of major market events. An ideal model is first constructed, which relies on an observation that a property cycle consists of four distinctive phases. These are described formally through appropriate formulae. Subsequently, it is observed that an analogous cyclic behaviour is described in physics as the Otto cycle. The formulae derived in physics for the Otto cycle are now redefined so to be applicable to the property market.
Findings
The model has been applied to the London office market, both to the historic and the current data sets. This allowed for the comparison of model predicted absorption and vacancies with the historic records, providing for assessment of the model accuracy. The model predicted that absorption was also compared with historic space supply allowing for estimation of oversupply and resultant vacancies. London office submarkets were analysed and compared to each other, allowing for estimation of their relative attractiveness as perceived by tenants and developers.
Practical implications
The model may be used to estimate cycle generated absorption; therefore, over and under supply of space due to developers’ activity may be assessed. It is also possible to use the model to assess the timing of future market peaks and troughs.
Originality/value
This is the first research directly applying the methodology developed in physics to commercial property cycles.
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Peter F. Colwell and Catherine Jackson
Models of the commercial property market have become increasingly sophisticated in recent years. However, the retail sector and, more specifically, analysis of retail markets at…
Abstract
Models of the commercial property market have become increasingly sophisticated in recent years. However, the retail sector and, more specifically, analysis of retail markets at the local level, have been comparatively neglected. This paper makes inroads into this gap in property research. Retail rental change at the local level is explored, focusing on consumer expenditure as the key determinant of change. The appropriateness of proxy variables is investigated and the mechanisms of rental change are examined. This highlights issues and difficulties unique to local level analysis. Following this, the relationship between rental change and underlying changes in consumer expenditure is investigated. The stability of a panel model of rental change is examined, with differences in market functioning identified across diverse groups of key local retail investment markets. These differences highlight the re‐emergence of northern markets during both the economic decline and recovery phases of the last decade of the 20th century. Rental levels in larger and smaller markets are also seen to respond to changes in consumer expenditure to significantly different degrees, in periods of both decline and recovery.
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The purpose of this paper is to outline the benefits of using system dynamics modelling as a research tool to understand the dynamics of commercial property markets in the UK and…
Abstract
Purpose
The purpose of this paper is to outline the benefits of using system dynamics modelling as a research tool to understand the dynamics of commercial property markets in the UK and their long-term behaviour. It highlights areas for future work.
Design/methodology/approach
This is a concept paper that outlines a simple systems model of rental change in UK commercial property markets as a way of illustrating how a systems approach can be used to describe and model the market. The model concentrates on the user market and offers a view of market operation, according to which development activity is initiated by demand (linked to economic growth) and to which supply responds by producing development.
Findings
The model demonstrates how a systems approach can be used to model the impact of a wide range of market variables on rental growth. The approach allows non-linear modelling of the complex relationships and behavioural factors that are difficult to include in existing econometric models of the market. It highlights where existing knowledge is deficient, especially with regard to price elasticity of demand, the relationship between economic activity and take up, the potential impact of redevelopment on the supply of new property and rental growth and response times of various parts of the market development process to market signals. It outlines where further research is needed to incorporate real market data.
Originality/value
Despite the wide application of the systems theory to business and other related areas, its use in commercial property research has been limited and has not gained much traction as a research tool. The work represents one of a very few studies applying the systems theory to the UK commercial property market.
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The purpose of this study is to provide a chaos theory-based framework, which can be used to model commercial property market dynamics.
Abstract
Purpose
The purpose of this study is to provide a chaos theory-based framework, which can be used to model commercial property market dynamics.
Design/methodology/approach
The paper is presented in two parts. In the first, rigorous mathematical reasoning is entertained, so to derive an attractor describing a set of feedback formulae. In the second part, the attractor definition is used to model the Auckland commercial office market. The model is exposed through a set of seven scenarios allowing for analysis of the market behaviour under various exogenously imposed conditions.
Findings
The general behaviour of the model is in agreement with the commercial property market conduct observed in Auckland. The model provides information related to the market turning points and allows for an explanation of some intricate market dynamics. These include the anatomy of a market peak and its response to the liquidity oversupply.
Practical implications
The model may be used to expand our understanding of the market performance under various exogenically imposed conditions, which allows for planning of market interventions in a more refined manner.
Originality/value
The paper is original, in the way the chaos theory is applied to the property markets modelling and allows for expanding the understanding of the market behaviour.
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Tracey West and Andrew C Worthington
This paper employs a Generalised Autoregressive Conditional Heteroske‐dasticity in Mean (GARCH‐M) model to consider the effect of macroeconomic factors on Australian property…
Abstract
This paper employs a Generalised Autoregressive Conditional Heteroske‐dasticity in Mean (GARCH‐M) model to consider the effect of macroeconomic factors on Australian property returns over the period 1985 to 2002. Three direct (office, retail and industrial property) and two indirect (listed property trust and property stock) returns are included in the analysis, along with market returns, short, medium and long‐term interest rates, expected and unexpected inflation, construction activity and industrial employment and production. In general, macroeconomic factors are found to be significant risk factors in Australian commercial property returns. However, the results also indicate that forecast accuracy in these models is higher for direct office, listed property trust and property stock returns and that the persistence of volatility shocks varies across the different markets, with volatility half lives of between five and seven months for direct retail and industrial property, two and three months for direct office property and less than two months with both forms of indirect property investment.
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Michael White, Daniel Mackay and Kenneth Gibb
This paper uses time series econometric techniques to model regional property rents in order to build a picture of the distinctiveness and commonality of the Scottish property…
Abstract
This paper uses time series econometric techniques to model regional property rents in order to build a picture of the distinctiveness and commonality of the Scottish property sector. Data used comes from a series stretching from 1970‐1998 and allows Scotland’s market performance (in terms of rents) in each of the three main property sectors to be benchmarked against a selective comparison of other UK regions. In doing so, we pay particular attention to the statistical properties of the time series used, applying tests of data stationarity and cointegration to develop a reduced form model of rents comprising both demand and supply‐side variables. The paper develops a predictive approach to property rents based on the autoregressive moving average (ARMA) methodology. Initial within‐sample predictive power is reasonably high. The implications of our results for a better understanding of the Scottish property market, as well as the more general modelling, are sketched out.
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