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Document type:
Masterarbeit
Author(s):
Thesis
Title:
Automated Valuation for Office Property Prices
Abstract:
The aim of this paper is to investigate the influence of different price determinants on the Munich office real estate market. Based on a relatively small dataset of 202 transaction prices between 2014 and 2020, several OLS models are successively estimated using hedonic regression. For this purpose, the data was generated from different sources, processed and supplemented with GIS (geographic information system) data and proprietary variables. Previous studies have extensively investigated the influence of price determinants, especially in the US and UK. A large number of variables were determined and found to be significant. To the author's knowledge, little research has been dedicated to the German office real estate market or the determination of office real estate prices. Moreover, the studies conducted so far have focused on the determination of asking or contract rents. Only the paper by Fürst & McAllister (2011) also examined the variation of purchase prices of office properties as a function of sustainability certifications (LEED and Energy Star). The structural building variables of rentable area, building age, and dummy variables for potential renovation or refurbishment and green building certification of the building were found to be critical factors in determining the purchase price. Furthermore, location and neighborhood characteristics improved the estimated models. In particular, distance to CBD was highly significant in all models. The model with the best explanatory power achieved an adjusted R2 of 85.7%. The use of out-of-sample predictions also demonstrated good predictive power of the models.
Keywords:
hedonic regression, office buildings, office property prices, Munich office property market
Advisor:
Muckenhaupt, Jan
Year:
2021
Language:
de
University:
Technische Universität München
TUM Institution:
Professur für Immobilienentwicklung
Status:
Abgeschlossen
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