New paper: Testing machine learning systems in real estate
How do ML-models arrive at their predictions? Do they do what we hope they do—or are corners cut?. New paper out at Real Estate Economics
Posts by Tag
research
New Paper: Urban land valuation with bundled good and land residual assumptions
Paper out: This paper develops a new approach to estimate the value of urban land and indirectly tests land residual assumptions. Bonus: Value surfaces estimated with a spatial ANN.
New Working Paper: “Growth and Predictability of Urban Housing Rents”
This paper studies urban rental prices for half a millennium (1500–2020) and seven cities: Amsterdam, Antwerp, Bruges, Brussels, Ghent, London, and Paris. Based on a dataset of 436,000 rental cash flow observations, we build continuous annual indices of housing rents, which we employ to study the long-term developments in rental cash flows, as well as their predictability. We find that real rent growth has been limited, but with large differences across cities: average annual growth rates range between 0.12 percent for the Belgian cities to 0.30 percent for Paris. At the market level, we show that sluggish supply adjustment implies that past population growth negatively predicts current rental growth. At the individual asset level, we find that past excess rental growth rates are predictive of future rent revisions, and that increasing steepness of the term structure of contract rents is predictive for future rent levels.
Spatial ML: Estimating Land Values in Phoenix (AZ)?
A neural networks that accounts for spatial correlation and time dynamics?
Are Estimates of Rapid Growth in Urban Land Values an Artifact of the Land Residual Model?
New paper out: A closer look at urban land and structure values – this is important for national accounts and for analysis of real estate risk over time. With John Clapp and Jeff Cohen.
Immobilienanlagen: Angebliches Renditewunder entzaubert / Le « miracle » de l’investissement immobilier démystifié
Summary of our total return paper in German and French.
New Publication: The Total Return To Real Estate
New research accepted for publication at the Review of Financial Studies (RFS) suggests that returns to real estate are solid but not exceptional: No sign of a housing risk premium puzzle.
Machine Learning, Architectural Styles and Property Values
New research accepted for publication at the Journal of Real Estate Finance and Economics: This paper couples a traditional hedonic model with architectural style classifications from human experts and machine learning (ML) enabled classifiers to estimate sales price premia over architectural styles, both at the building and the neighborhood-level.
Aesthetic Preferences for Residential Architecture: Finding Ground Truth with Machine Learning Approaches
This paper first collects binary classifications of house pictures from a large group of participants and then trains personalized ML classifiers for each participant.
Valuable Words: The Price Dynamics of Internet Domain Names
This article estimates the first constant quality price index for Internet domain names. The suggested index provides a benchmark for domain name traders and investors looking for information on price trends, historical returns, and the fundamental risk of Internet domain names.
publications
Are Estimates of Rapid Growth in Urban Land Values an Artifact of the Land Residual Model?
New paper out: A closer look at urban land and structure values – this is important for national accounts and for analysis of real estate risk over time. With John Clapp and Jeff Cohen.
Immobilienanlagen: Angebliches Renditewunder entzaubert / Le « miracle » de l’investissement immobilier démystifié
Summary of our total return paper in German and French.
New Publication: The Total Return To Real Estate
New research accepted for publication at the Review of Financial Studies (RFS) suggests that returns to real estate are solid but not exceptional: No sign of a housing risk premium puzzle.
Machine Learning, Architectural Styles and Property Values
New research accepted for publication at the Journal of Real Estate Finance and Economics: This paper couples a traditional hedonic model with architectural style classifications from human experts and machine learning (ML) enabled classifiers to estimate sales price premia over architectural styles, both at the building and the neighborhood-level.
working papers
New Working Paper: “Growth and Predictability of Urban Housing Rents”
This paper studies urban rental prices for half a millennium (1500–2020) and seven cities: Amsterdam, Antwerp, Bruges, Brussels, Ghent, London, and Paris. Based on a dataset of 436,000 rental cash flow observations, we build continuous annual indices of housing rents, which we employ to study the long-term developments in rental cash flows, as well as their predictability. We find that real rent growth has been limited, but with large differences across cities: average annual growth rates range between 0.12 percent for the Belgian cities to 0.30 percent for Paris. At the market level, we show that sluggish supply adjustment implies that past population growth negatively predicts current rental growth. At the individual asset level, we find that past excess rental growth rates are predictive of future rent revisions, and that increasing steepness of the term structure of contract rents is predictive for future rent levels.
Aesthetic Preferences for Residential Architecture: Finding Ground Truth with Machine Learning Approaches
This paper first collects binary classifications of house pictures from a large group of participants and then trains personalized ML classifiers for each participant.
ML
New Paper: Urban land valuation with bundled good and land residual assumptions
Paper out: This paper develops a new approach to estimate the value of urban land and indirectly tests land residual assumptions. Bonus: Value surfaces estimated with a spatial ANN.
Spatial ML: Estimating Land Values in Phoenix (AZ)?
A neural networks that accounts for spatial correlation and time dynamics?
Domain Names
Valuable Words: The Price Dynamics of Internet Domain Names
This article estimates the first constant quality price index for Internet domain names. The suggested index provides a benchmark for domain name traders and investors looking for information on price trends, historical returns, and the fundamental risk of Internet domain names.
machinelearning
New paper: Testing machine learning systems in real estate
How do ML-models arrive at their predictions? Do they do what we hope they do—or are corners cut?. New paper out at Real Estate Economics
August Potuczek
Franz Xaver Rektorzik
Etchings by Franz Xaver Rektorzik, printed by August Potuczek
