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William C. Wheaton. Sykora, Jiri,S.M.Massachusetts Institute of Technology. Massachusetts Institute of Technology. Center for Real Estate. Program in Real Estate Development. Massachusetts Institute of Technology. Center for Real Estate. Program in Real Estate Development Massachusetts Institute of Technology. Center for Real Estate 2020-01-23T16:59:14Z 2020-01-23T16:59:14Z 2019 2019 https://hdl.handle.net/1721.1/123599 1135865480 This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. Thesis: S.M. in Real Estate Development, Massachusetts Institute of Technology, Program in Real Estate Development in conjunction with the Center for Real Estate, 2019 Cataloged from PDF version of thesis. Includes bibliographical references (pages 49-50). The durations of other indicators have been researched extensively in real estate studies, primarily the time on market and the duration of residence in housing units. Despite their importance, empirical research on the duration of vacancies is relatively limited and focused mainly on the housing sector. This paper aims to fill this gap and analyze the determinants of vacancy durations in the office sector. The analysis is based on a dataset of individual office suites located in New York City, NY that became vacant between 2012 and 2015. Vacancy durations are a form of time-to-event data and as such can be examined using survival analysis. We present several parametric and non-parametric survival models. Four key characteristics -- unit size, asking rent, building height, and floor number -- are found significant across all model specifications. Specifically, vacancy durations are affected the most by unit size and asking rent. Survival probabilities are found to considerably vary over time, which appears to be driven by variations in employment growth. by Jiri Sykora. S.M. in Real Estate Development S.M.inRealEstateDevelopment Massachusetts Institute of Technology, Program in Real Estate Development in conjunction with the Center for Real Estate 50 pages eng Massachusetts Institute of Technology MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. http://dspace.mit.edu/handle/1721.1/7582 Center for Real Estate. Program in Real Estate Development. Vacancy durations in the office market Thesis application/pdf 2020-03-09T19:59:03Z Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="78a14843-a14e-40b7-bb06-207f3290b9de"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Vacancy durations in the office market</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2019</PublicationDate> <Authors> <Author> <DisplayName>Sykora, Jiri,S.M.Massachusetts Institute of Technology.</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://dspace.mit.edu/handle/1721.1/7582</License> <Keyword>Center for Real Estate. Program in Real Estate Development.</Keyword> <Abstract>The durations of other indicators have been researched extensively in real estate studies, primarily the time on market and the duration of residence in housing units. Despite their importance, empirical research on the duration of vacancies is relatively limited and focused mainly on the housing sector. This paper aims to fill this gap and analyze the determinants of vacancy durations in the office sector. The analysis is based on a dataset of individual office suites located in New York City, NY that became vacant between 2012 and 2015. Vacancy durations are a form of time-to-event data and as such can be examined using survival analysis. We present several parametric and non-parametric survival models. Four key characteristics -- unit size, asking rent, building height, and floor number -- are found significant across all model specifications. Specifically, vacancy durations are affected the most by unit size and asking rent. Survival probabilities are found to considerably vary over time, which appears to be driven by variations in employment growth.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>