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Primarily based on Alonso’s bid-rent model, the purpose of this paper is to examine the dynamics of the Singapore’s overall retail rental market by adopting a vector error correction model (VECM) estimation.

This paper uses the proxy for the overall retail rental value, which is indicated by a combination of the shop rent index from 2004 to 2013 and the retail rent index (RRI) in 2014, maintained by the Urban Redevelopment Authority (URA). The independent factors are the real gross domestic product (GDP), monthly earnings of individuals and vacancy rates (VR).

Such a behavioral model examines the dynamic structures that overshoot and/or diverge from equilibrium.

The variables LOGGDP and VR are co-integrated of order one, I(1), while variables LOGME and LOGSRI are co-integrated of order two, I(2), to enable them to be employed in the VECM model.

The VECM model shows a good fit that allows the error correction term (ecm) together with the economic, financial and rental variables to jointly explain about 79.2 percent of the variation in the overall RRI. With a positive CoinEq1 coefficient that is positive and statistically significant at 5 percent level, it would take a long time for the system to return to its equilibrium once it has been shocked. Another variable that shows significant explanatory relationships includes past rents (index points) in the second order lags [D(LOGSRI(−2))]. The variable [D(LOGGDP(−3))], with a significant t-statistic value at 2.916, also helps to explain the changes in the overall rents.

This paper highlights the importance of the first and third differences of the lagged macroeconomic variables of the monthly earnings of individuals is moderately significant. The VR in the first and second differences is significant in accounting for the variation in changes of overall retail rents with their t-statistics values being above 3.0. It is thus meaningful for policy makers to so enhance their in-depth understanding.

This paper fulfills an identified need to study how the results from the ex post forecasting estimates from the VECM for overall retail rents in Singapore can be enabled.

The purpose of this paper is to examine the common stock price reaction and the changes to the risk exposure of the cross-listing for real estate investment trusts (REITs).

The paper adopts the event study methodology to assess the abnormal returns (ARs). Pre- and post-cross-listing changes in the risk exposure for the domestic and foreign markets are examined, via a modified two-factor international asset pricing model. A comparison is made for two broad cross-listings, namely, the depositary receipts and the dual ordinary listings, to examine the impacts from institutional differences.

Cross-listed REITs generally experience positive and significant ARs throughout the event window, implying significant superior returns associated with the cross-listing for REITs. On systematic risks, REITs exhibit significant decline in their domestic market β coefficients after the cross-listing. However, the foreign market β coefficients do not yield conclusive evidence when compared across the sample.

Results are consistent with prudential asset allocation for potential diversification gains from the cross-listing, as the reduction from the domestic market beta is more significant than changes in the foreign market beta.

The results and findings should incentivise REIT managers to explore viable cross-listing.

Such cross-listing for REITs should enhance risk diversification.

This is a pioneer study on cross-listing of REITs. It provides a basis for investment decision making, and could provoke further research and discussion.

This paper aims to examine the behavior of “rational” residential developers, under game theory, for their pricing strategy in a competitive environment.

Results show that residential developers cooperate implicitly for long-term benefit, leading to a slow-down in sales. Developers are motivated to deviate from cooperating at the beginning and at the end of successive periods in a sub-market. Relatively high profits, earnable in the first few periods, provide an allowance to undercut prices and improve sales. For the last few periods, the punishment for any deviation from cooperating is insignificant or zero. Note that the first-mover advantage in a new market is evident. On the effect of uncertainty on the developer’s residential prices, results show that as uncertainty increases, prices decrease while price variability increases.

This study highlights the merits of a uniquely simplified experimental research design for the strategic behavioral pricing of the private residential development market using a game theoretic approach.

This study enhances the understanding of the residential development strategy of developers in the residential development market.

There is limited research on pricing strategy for the private residential development market in Asia.

The purpose of this paper is to help us understand the real estate cycle and offers an analysis using a vector auto regression (VAR) model. The authors study the key international cities of Hong Kong, Kuala Lumpur and Singapore. The authors find four key outcomes. One, the real estate cycle is generally different from the underlying business cycle in local markets for the cities studies. Two, the real estate cycle is more exaggerated in the construction and development areas than in rents and vacancies. Three, the vacancy cycle tends to lead the rental cycle. And four, new construction completions tend to peak when vacancy is also peaking. The authors believe that future research should try to help understand the linkages that drive these outcomes. For example, are rigidities in the local permit and construction markets responsible for the link between construction peaks and vacancy peaks?

Real estate market cyclical dynamics and its estimation via VAR model offers an insightful set of practical and empirical models. It affirms a comprehensive theoretical underpinning for analysing the prime office and residential sectors of the capitol cities of Kuala Lumpur, Singapore and Hong Kong in the fast developing Asia region. Its unrestricted form also provides an effective and insightful way of modelling real estate market cyclical dynamics utilising only real estate market indicators, furnished by real estate market data providers.

The office rental VAR model for Singapore (SOR), KL (KOR) and HK (HOR) show good fits. In the HOR model, rents and vacancies are negatively signed and significant for certain lagged relationships with other variables and with rents themselves. The office CV VAR model for Singapore (SOCV), KL (KOCV) and HK (HOCV) show good fits. In the HOCV model, capital values (CVs) and initial yields are negatively signed and significant for certain lagged relationships with other variables and with CVs themselves. Impulse response functions specified for seven years to mirror a medium-term real estate market cycle “die out” to zero for the stationary VAR models that are estimated for the endogenous variables. The accumulated responses asymptote to some non-zero constant.

The VAR model offers a complete and meaningful dynamic system of solely real estate variables for international real estate investors and policy makers in decision making. Its unrestricted form offers an effective and insightful way of modelling real estate market cyclical dynamics utilising only real estate market indicators, which can be reliably provided by a dedicated real estate information and consultancy provider of international standing.

The theoretical model offers a complete dynamic model system of the real estate space market, comprising a unique system of six linked equations that denote the relationship among supply, demand, construction, vacancy and rent over time, inclusive of price response slopes and lags. The VAR model enables the investigation of the effect of the lagged values of all the variables concerned. It also enables the explicit and rigorous quantitative forecasts of say rents and CVs when the rest of the variable can be forecasted beforehand.

The purpose of this paper is to examine the risk neutral and non-risk neutral pricing of Singapore Real Estate Investment Trusts (S-REITs) via comparing the average of the individual ratios (of deviation between expected and observed closing price/observed closing price) with the ratio (of standard deviation/mean) for closing prices via the binomial options pricing tree model.

If the ratio (of standard deviation/mean) ratio > the ratio (of deviation between expected and observed closing price/observed closing price), then the deviation of closing prices from the expected risk neutral prices is not significant and that the S-REIT is consistent with risk neutral pricing. If the ratio (of deviation between expected and observed closing price/observed closing price) is greater, then the S-REIT is not consistent with risk neutral pricing.

Capitacommercial Trust (CCT), Capitamall Trust (CMT) and Keppel Real Estate Investment Trust (REIT) have large positive differences between the two ratios (39.86, 30.79 and 18.96 percent, respectively), implying that these S-REITs are not trading at risk neutral pricing. Suntec REIT has a small positive difference of 2.35 percent between both ratios, implying that it is trading at risk neutral pricing. Ascendas REIT has the largest negative difference between the two ratios at −4.24 percent, to be followed by Mapletree Logistics Trust at −0.44 percent. Both S-REITs are trading at risk neutral pricing. The analysis shows that CCT, CMT and Keppel REIT exhibit risk averse pricing.

Results are consistent with prudential asset allocation for viable S-REIT portfolio investing but that not all these S-REITs exhibit strong market efficiency in their pricing.

Pricing may be risk neutral over a certain period but investor sentiments, fear of risks and speculative activities could affect an S-REIT’s risk neutrality.

With enhanced risk diversification activities, the S-REITs should attain risk neutral pricing.

Virtually no research of this nature has been undertaken for S-REITS.

From the perspective of the macro‐economy and real estate sector interaction, this paper aims to examine the maturing prime retail real estate sector versus the developing suburban retail real estate sector.

This paper adopts a highly specific dynamic computable general equilibrium model under system dynamics programming to structure the resulting system complexity within the context of Singapore.

Ex post and ex ante model estimations find that the suburban retail real estate sector is on the whole more susceptible to gross domestic product (GDP) growth policy that affects both GDP expansion and retail rents in actual and expectation terms as well as returns.

The DCGE model ex ante estimations for the planned scenarios, under low or high GDP growth for the prime and suburban retail real estate sectors, enhances understanding of structural factors and dynamic interaction in the maturation phase of the prime retail real estate sector in Singapore.

In comparison, Singapore's suburban retail real estate sector is found to be in a developing phase.

There is limited local research on the underlying relationship between the economy and the retail real estate sector, although Singapore's retail sector and retail real estate sector form an integral part of sustainable economic expansion.

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.

The purpose of this paper is to conceptualise a workable strategic asset allocation (SAA) model, given the data paucity problem, and involve an ex ante framework that is distributional free.

The SAA model is developed within a semi‐quantitative and expert‐based framework – the analytic hierarchy process (AHP) – and not a purely time‐series one. It is developed on the basis of consensus by a group of real estate investment experts, who agree on a fixed investment time horizon so that the time factor is disregarded as a variant. The SAA becomes the interface around which a set of tactical bands is imposed, subject to the Markowitz mean‐variance optimisation, and utilizing the total‐return data set of the Jones Lang LaSalle Real Estate Intelligence Service‐Asia. The lower and upper limits of the tactical bands represent the cyclical attractiveness of the various Asian office markets as growth and value‐added markets

The SAA‐AHP model robustly reflects expert judgement among a cohesive group of real estate investment experts, with regard to a Pan‐Asia office market portfolio of eight major Asian cities. Through pair‐wise comparisons and subject to consistency checks in terms of the consistency ratio of <0.10, then the comparative expert assessment of the macro‐economic and the real estate specific factors driving individual Asian real estate markets, would be consistent (i.e. non conflicting). Then the total weighted evaluations of individual markets are derived and deployed as the SAA portfolio mix. This portfolio mix thus becomes the appropriate interface, around which the tactical asset allocation (TAA) is developed within defined tactical bands. These bands must be in line with the underlying Asian real estate market analysis and their cyclical positions. The TAA is obtained through the Markowitz mean‐variance portfolio optimisation, with the objective of locating the optimally efficient TAA on the Markowitz efficient frontier, under a maximising risk‐adjusted‐return Sharpe ratio.

The SAA‐AHP model is reliant on an ex ante assessment of alternative asset allocation strategies on the basis of expert judgement of the macroeconomic environment and the Asian office markets. It is an appropriate SAA alternative to one based on the typical economic‐sized indicators, for example, the urban GDP.

The paper aims to form system dynamics modeling in introduced in conjunction with econometric analysis and planned scenario analysis which will uniquely structure the process whereby the ex ante capital values of the prime retail real estate sector.

The integrated system dynamics model investigates the structural factors affecting a unique expectation‐centered capital value (CV) formation of the prime retail real estate sector, through system dynamics modeling, econometric analysis , and the analysis of planned scenarios. This model extends beyond the usual lags and time line aspect of the price discovery process. The retail real estate sector is investigated within the Singapore context, as this sector changes dynamically and non‐linearly in relation to rental, cost and general demand expectations and to exogenous shocks like the Severe Advanced Respiratory Syndrome (SARS) outbreak. These macroeconomic factors are introduced to investigate their impact on retail space CVs through sensitivity analysis, during the simulation period of 20 quarters from the zero reference quarter (2Q2002).

The paper finds that simulation runs of the expectations‐centered system dynamics model are based on three scenarios. Sensitivity analysis is conducted for each scenario. Optimistic scenarios' CVs are lower than those of the likely scenario, owing to developers forming excessively high expectations that cannot be met by the actual rental levels. Pessimistic scenarios' CVs are highest. Based on bounded logic and the conditions for all scenarios, there are huge differences in expectations resulting in a large disparity in the endogenous CVs. Low actual rents are primarily due to poor informational efficiency, as the prime retail real estate sector is not transparent enough, and that many transactions are privately closed. Expectations cannot be met as the market information is not disseminated extensively through the agents and players. The scenarios clearly highlight the problem of informational non‐availability in the sector. The main policy implication is a need for a more transparent system of sharing rental and pricing information for the retail real estate sector, which is meaningful for real estate developers, investors and urban planners to sustain the retail real estate sector's viability.

This paper takes system dynamics modeling to the next level of incorporating econometric analysis, to estimate the sensitivity of retail rent to cost and the change in retail rent, for effectively structuring the dynamic process whereby the ex ante CVs of the prime retail sector in Singapore are formed and assessed, through a unique and rigorous expectations‐centered system dynamics model of rents, cost, retail stock, general demand and exogenous factors.

Although the modern portfolio theory (MPT) asset allocation framework can be adopted to enable decision making for international and direct real estate investing, and that many institutional investors adopt it to support their decision making, this framework can be enhanced to capture the multi‐causal factors influencing international and direct real estate investing. The purpose of this paper is to explain how a fuzzy decision‐making approach is a more intuitive, yet rigorous alternative in this regard.

This paper is concerned with the model formation and estimation of a unique fuzzy tactical asset allocation (FTAA), which in turn comprises the FTAA flexible programming model and the FTAA robust programming model.

Both these FTAA models enhance the classical, Markowitz MPT portfolio theory on asset allocation through making it more intuitively appropriate for decision making in international and direct real estate investing.

These two FTAA models achieve the benefits of intuitively greater risk diversification by city or real estate sector and enable effective risk management. These two short‐run fuzzy models would be accepted and more such models would emerge as an effective extension of quadratic programming optimization, as more computable software programs of this kind are widespread.

Fuzzy approaches to asset allocation in the short run, are limited by some drawbacks. Fuzzy models possess the common feature of converting the equality function under quadratic programming optimization into inequality functions. Such inequality optimization replaces the point solution of the MPT TAA optimization problem, obtained through the rigid intersection of all functions, via a generalized or intuitive answer over a defined space of alternatives. The product of the fuzzy process with fuzzy inputs, in the form of fuzzy outcome is in actual fact a more natural and intuitive approach to asset optimization.