Please use this identifier to cite or link to this item: https://doi.org/10.1108/14635780710733852
DC FieldValue
dc.titleModeling the structure of CV formation and expectations: The commercial retail real estate sector
dc.contributor.authorHo, K.H.
dc.date.accessioned2013-10-14T05:10:09Z
dc.date.available2013-10-14T05:10:09Z
dc.date.issued2007
dc.identifier.citationHo, K.H. (2007). Modeling the structure of CV formation and expectations: The commercial retail real estate sector. Journal of Property Investment and Finance 25 (2) : 179-206. ScholarBank@NUS Repository. https://doi.org/10.1108/14635780710733852
dc.identifier.issn1463578X
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/46189
dc.description.abstractPurpose - 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. Design/methodology/approach - 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). Findings - 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. Originality/value - 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.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1108/14635780710733852
dc.sourceScopus
dc.subjectCapital
dc.subjectReal estate
dc.subjectRetail trade
dc.subjectSingapore
dc.subjectValue analysis
dc.typeArticle
dc.contributor.departmentREAL ESTATE
dc.description.doi10.1108/14635780710733852
dc.description.sourcetitleJournal of Property Investment and Finance
dc.description.volume25
dc.description.issue2
dc.description.page179-206
dc.identifier.isiut000212806600006
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