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David Geltner and Alexander van de Minne. Gallagher, Stephen James 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 2019-03-01T19:55:19Z 2019-03-01T19:55:19Z 2018 2018 http://hdl.handle.net/1721.1/120652 1088412066 Thesis: S.M. in Real Estate Development, Massachusetts Institute of Technology, Program in Real Estate Development in conjunction with the Center for Real Estate, 2018. Cataloged from PDF version of thesis. Includes bibliographical references (pages 38-39). Using a sample of 1458 industrial properties with 36,450 quarterly observations, we apply a pair of OLS models to predict property-level NOI and capex. We then synthesize the results by modeling capex as a fraction of NOI, which we treat as a measure of property capex performance. We model capex and NOI with a series of hedonic variables that account for property and market characteristics. Travel time to the nearest CBD predicts neither capex nor NOI, but building age strongly predicts both. We find that NOI declines continuously as buildings age, first quickly and then more gradually. Capex is lower in new buildings but rises over time, peaking after 30 years before declining. NOI and capex are strongly associated with building size, but the relationships are not linear. Large buildings experience economies of scale with respect to capex and diseconomies of scale with respect to NOI. Because the capex economies of scale are more pronounced, capex fractions of NOI are smaller in large buildings. Capex fractions of NOI rise and fall over time in a manner roughly similar to total capex, but the initial fractions are low and their peaks lag peak capex by 5 years. We find that capex fraction of NOI is lower in top markets when property characteristics are held constant. But property characteristics are not consistent across markets. We find that this fraction is actually similar across the country, as the economic efficiencies of top markets are offset by the inefficiencies of their smaller and older industrial building stock. by Stephen James Gallagher. S.M. in Real Estate Development 41 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. Capital expenditures in industrial properties Thesis application/pdf false Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="e6689ae0-061e-4ef3-bf30-c4efba9e25b5"> <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>Capital expenditures in industrial properties</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2018</PublicationDate> <Authors> <Author> <DisplayName>Gallagher, Stephen James</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>Using a sample of 1458 industrial properties with 36,450 quarterly observations, we apply a pair of OLS models to predict property-level NOI and capex. We then synthesize the results by modeling capex as a fraction of NOI, which we treat as a measure of property capex performance. We model capex and NOI with a series of hedonic variables that account for property and market characteristics. Travel time to the nearest CBD predicts neither capex nor NOI, but building age strongly predicts both. We find that NOI declines continuously as buildings age, first quickly and then more gradually. Capex is lower in new buildings but rises over time, peaking after 30 years before declining. NOI and capex are strongly associated with building size, but the relationships are not linear. Large buildings experience economies of scale with respect to capex and diseconomies of scale with respect to NOI. Because the capex economies of scale are more pronounced, capex fractions of NOI are smaller in large buildings. Capex fractions of NOI rise and fall over time in a manner roughly similar to total capex, but the initial fractions are low and their peaks lag peak capex by 5 years. We find that capex fraction of NOI is lower in top markets when property characteristics are held constant. But property characteristics are not consistent across markets. We find that this fraction is actually similar across the country, as the economic efficiencies of top markets are offset by the inefficiencies of their smaller and older industrial building stock.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>