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New papers out:
J. Clapp and T. Lindenthal (2022). "Urban land valuation with bundled good and land residual assumptions", Journal of Housing Economics.
Wan, W. and T. Lindenthal (2022). "Testing Machine Learning Systems in Real Estate". Real Estate Economics.
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Dr Lindenthal is an Associate Professor for Real Estate Finance. His research interests are twofold: First, he analyzes property investments in the very long-term, tracking rents, prices, and returns for up to 500 years. The second research line focuses on applied machine learning techniques to utilize high-dimensional “Big(ish)” data. Put differently, he uses images and other data that are too complex for spreadsheets to better understand property values, household preferences, and decisions made by very human and not always rational agents.
Thies takes pride in teaching. He is the course director for Cambridge’s postgraduate MPhil programme in Real Estate Finance. He is also a fellow at Murray Edwards College and at the Cambridge Endowment for Research in Finance. In addition, he received a JM Keynes Fellowship in Financial Economics.
Before joining the University of Cambridge, he did a postdoc at MIT's Center for Real Estate, working on the market for virtual locations such as Internet domain names. His PhD is from Maastricht University.
Thies is a board member for the American Real Estate And Urban Economics Association (AREUA) and has served as an expert witness for internet domain names at US courts.
In response to the Covid lockdown, Thies co-organised a virtual research seminar series Seminar.RE.
Thies is interested in supervising new PhD students in Real Estate Finance, preferably with a focus on new (somewhat "big") data or, alternatively, property markets in the very long run. However, candidates might have a look at this debate first ...
