{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/62104"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/62104","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Examination of the real estate market risk and volatility : focusing on the U.S. office property","abstract":"The high risk and volatility in the current real estate market has sparked investor interest in understanding what determines real estate market volatility. This study examines the U.S. office markets' overall and decomposed volatilities in vacancy and revenue across 45 metropolitan areas from 1987 to 2010. The relationships of the volatilities with economic and physical market characteristics are also analyzed. The study examines five overall or decomposed market volatilities: volatility in vacancy, volatility in revenue, demand-oriented vacancy change volatility, occupancy-oriented revenue change, and covariance of occupancy rent change. The linear regression analyses are used to explain the movements of the volatilities with market determinants, which include market size, employment growth, jobs in specific industries, submarket structures and geography. This study finds that geographical land availability and employment growth are significantly important for predicting market volatilities. Market size does not affect the decomposed volatility, but it reduces overall vacancy change volatility. Moreover, submarket structure becomes more meaningful when the revenue change volatility is decomposed into occupancy and rent changes. This study gives developers some tools for strategic decision-making in office property development issues.","abstract_html":"The high risk and volatility in the current real estate market has sparked investor interest in understanding what determines real estate market volatility. This study examines the U.S. office markets' overall and decomposed volatilities in vacancy and revenue across 45 metropolitan areas from 1987 to 2010. The relationships of the volatilities with economic and physical market characteristics are also analyzed. The study examines five overall or decomposed market volatilities: volatility in vacancy, volatility in revenue, demand-oriented vacancy change volatility, occupancy-oriented revenue change, and covariance of occupancy rent change. The linear regression analyses are used to explain the movements of the volatilities with market determinants, which include market size, employment growth, jobs in specific industries, submarket structures and geography. This study finds that geographical land availability and employment growth are significantly important for predicting market volatilities. Market size does not affect the decomposed volatility, but it reduces overall vacancy change volatility. Moreover, submarket structure becomes more meaningful when the revenue change volatility is decomposed into occupancy and rent changes. This study gives developers some tools for strategic decision-making in office property development issues.","abstract_has_math":false,"creators":["Kim, Hyun Jae"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Center for Real Estate. 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