Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/220910
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dc.titleREAL ESTATE MARKET CYCLES: WHICH IS THE LEADING SECTOR?
dc.contributor.authorSOH MEI TING, CHERYL
dc.date.accessioned2012-05-10T01:52:07Z
dc.date.accessioned2022-04-22T17:22:20Z
dc.date.available2019-09-26T14:13:58Z
dc.date.available2022-04-22T17:22:20Z
dc.date.issued2012-05-10
dc.identifier.citationSOH MEI TING, CHERYL (2012-05-10). REAL ESTATE MARKET CYCLES: WHICH IS THE LEADING SECTOR?. ScholarBank@NUS Repository.
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/220910
dc.description.abstractThough important to industry practitioners, academics and regulators, there has been a dearth of literature on determining the leader in cyclical movement in the local real estate market and sectoral response to Gross Domestic Product (GDP) changes. This dissertation aims to fill up the gaps in existing literature by 1) tracing the movement of real estate market cycles in Singapore, 2) determining which sector is the leading indicator in real estate cyclical movement; and 3) verifying if the particular leading indicator reacts fastest to changes in GDP. Utilising Property Price Index data from the Urban Redevelopment Authority (URA) across the industrial, office, residential and retail sectors, as well as Singapore’s GDP; informal tests such as graphs and property clocks, as well as formal tests such as a Vector Autoregressive (VAR) model and Impulse Response Function (IRF) analyses are carried out. Results from both informal and formal tests established that the residential sector is the leader in reaching a peak and/or trough in the real estate market cycle and also the first to react to changes in GDP. In addition, the four sectors are proven to move in a similar cyclical pattern. As industrial, office and retail space are more commonly leased than transacted, robustness tests are carried out to ensure that the findings presented earlier are not due to the dynamics of the real estate price cycle alone. The entire methodology is repeated using data from the Property Rental Index and results from the robustness tests justified the validity of the earlier results.
dc.language.isoen
dc.sourcehttps://lib.sde.nus.edu.sg/dspace/handle/sde/1905
dc.subjectReal Estate
dc.subjectOoi Thian Leong Joseph
dc.subject2011/2012 RE
dc.typeDissertation
dc.contributor.departmentREAL ESTATE
dc.contributor.supervisorOOI THIAN LEONG JOSEPH
dc.description.degreeBachelor's
dc.description.degreeconferredBACHELOR OF SCIENCE (REAL ESTATE)
dc.embargo.terms2012-06-01
Appears in Collections:Bachelor's Theses

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