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Forecasting models for the German office market

In every market with free floating prices, all market participants are interested in the future developments of these prices. However, there is an evident research gap for forecasting models for the German office market. Alexander Bönner closes this gap by focusing on an empirical investigation of several rent and total yield forecasting models for nine major German cities. The applicability and performance of ARIMA, GARCH and multivariate regression models are analyzed and city as well as forecasting horizon-specific patterns are determined and interpreted. Univariate rent forecasting models generally outperform multivariate rent forecasting regression models in the short run. In the long run, multivariate regression models dominate. However, one must bear in mind that in some cities one model permanently outperforms the other. Eventually, the rent level is mainly determined by its economic fundamentals, which is also demonstrated for the total yield examination.

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  • "In every market with free floating prices, all market participants are interested in the future developments of these prices. However, there is an evident research gap for forecasting models for the German office market. Alexander Bönner closes this gap by focusing on an empirical investigation of several rent and total yield forecasting models for nine major German cities. The applicability and performance of ARIMA, GARCH and multivariate regression models are analyzed and city as well as forecasting horizon-specific patterns are determined and interpreted. Univariate rent forecasting models generally outperform multivariate rent forecasting regression models in the short run. In the long run, multivariate regression models dominate. However, one must bear in mind that in some cities one model permanently outperforms the other. Eventually, the rent level is mainly determined by its economic fundamentals, which is also demonstrated for the total yield examination."@en
  • "Dieses Buch ist motiviert durch die Forschungsluecke im Bereich der Prognosemodelle fuer den deutschen Bueroimmobilienmarkt. Miet-, Preis- oder Yieldprognosemodelle werden hauptsaechlich von kommerziell arbeitenden Instituten erstellt. Diese Arbeit ist aus akademisch wissenschaftlicher Perspektive geschrieben und setzt den Fokus auf empirische Untersuchungen verschiedener Miet- und Total Yield Prognosemodelle fuer neun bedeutende deutsche Staedte. Die Analyse zielt auf deren Anwendbarkeit und Performance fuer die verschiedenen Staedte und fuer verschiedene Prognosehorizonte. Nach Darstellung der massgeblichen, hauptsaechlich angelsaechsischen Literatur zu Immobilienprognosemodellen werden die theoretischen Grundlagen fuer den empirischen Teil der Arbeit gelegt. Neben allgemeinen Immobilienmarktcharakteristika werden auch die Besonderheiten von Zeitreihen- und Paneldaten, grundlegende Prognosemodelle wie auch Prognosetechniken und Performancemasse dargestellt. Die Haupterkenntnisse des ersten Teils der Empirie, der Mieten untersucht, sind, dass ARIMA, GARCH und multivariate Regressionsmodelle grundsaetzlich fuer Mietprognosen im deutschen Bueroimmobilienmarkt geeignet sind. Es wird weiterhin beobachtet, dass GARCH Modelle eine hoehere Prognoseguete als ARIMA Modelle im drei bis fuenf Jahres Prognosehorizont erzielen, wenn in den untersuchten Staedten erhoehte Volatilitaet feststellbar ist. Ebenso wird festgestellt, dass univariate Modelle die multivariaten Regressionsmodelle bzgl. der Prognoseguete in der kurzen Frist uebertreffen. Das Gegenteil ist der Fall in der langen Frist. Abweichend von diesem Grundmuster gibt es allerdings Staedte in denen eine Modellart permanent dominant ist. Es stellt sich auch heraus, dass Regressionsmodelle mit wenigen Faktoren hoehere Prognoseguete liefern als solche mit komplexen Strukturen. Weiterhin laesst sich zeigen, dass das Mietniveau in der langen Frist hauptsaechlich durch oekonomische Zusammenhaenge bestimmt ist, praezise Prognosen allerdings Startwerte auf oekonomisch nachvollziehbarem Niveau benoetigen. Die Haupterkenntnisse des zweiten Teils der Empirie, der Total Yields untersucht, sind, dass multivariate Regressionsmodelle grundsaetzlich fuer Total Yield Prognosen im deutschen Bueroimmobilienmarkt geeignet sind. Ebenso stellt sich heraus, dass Regressionsmodelle mit wenigen Faktoren hoehere Prognoseguete liefern als solche mit komplexen Strukturen. Weiterhin laesst sich zeigen, dass das Total Yield Niveau in der langen Frist hauptsaechlich durch oekonomische Zusammenhaenge bestimmt ist. Im Gegensatz zur Mietuntersuchung sind Startwerte auf oekonomisch nachvollziehbarem Niveau fuer praezise Prognosen weniger wichtig."
  • "This work is motivated by the research gap evident in the area of forecasting models for the German office market. Since rent, price or yield forecasting research is mainly done by commercially oriented organizations, this work delivers an examination from a scientific point of view. Thus the focus is set on an empirical investigation of several rent and total yield forecasting models for nine major German cities. Their applicability and performance are analyzed and city as well as forecasting horizon-specific patterns are determined and interpreted. After the literature review, mainly covering Anglo-Saxon research, I derive the theoretical foundations which are important in executing the empirical part of the work. Therefore, I discuss theoretically general real estate market characteristics, the specifics of time series and panel data, common forecasting models, and forecasting techniques as well as performance measures. The major findings of the first part of the empirical work, which contains the rent series investigation, is that ARIMA, GARCH and multivariate regression models are generally able to forecast rent series in the German office market. Furthermore, I observed that GARCH models are able to outperform single ARIMA models for forecasting horizons of three to five years, when increased volatility appears within the respective city rent series. Moreover, univariate models outperform multivariate regression models in the short run. On the other hand, multivariate regression models outperform the univariate models in the longer run. However, I found cities where one model permanently dominates. Furthermore, parsimoniously constructed multivariate regression models lead to considerably better forecasting performances than more complex multivariate ones. For the long run I also show that the rent level is mainly determined by its economic fundamentals. Nevertheless, precise forecasts require starting values at economically reasonable rent levels. The major finding of the second part of the empirical work, which contains the total yield series investigation, is the general ability of multivariate regression models to forecast total yield series in the German office market. Again, parsimoniously constructed models outperform more complex models for the short run and for the long run. For the long run, I additionally demonstrate that the total yield is mainly determined by its economic fundamentals. The rent analysis prerequisite of starting values at economically reasonable levels cannot be neglected but can be relativized to some extent."

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  • "Online-Publikation"
  • "Electronic books"
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  • "Forecasting models for the German office market"@en
  • "Forecasting models for the German office market"
  • "Forecasting Models for the German Office Market"
  • "Forecasting Models for the German Office Market"@en

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