Spatial ML: Estimating Land Values in Phoenix (AZ)?
A neural networks that accounts for spatial correlation and time dynamics?
A neural networks that accounts for spatial correlation and time dynamics?
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.
Summary of our total return paper in German and French.
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.
My previous website went down in flames (or rather: is now hosted in a black cloud).
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.
This paper first collects binary classifications of house pictures from a large group of participants and then trains personalized ML classifiers for each participant.
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.