But it does raise a question: would academics who study real estate be better off spending less time modeling and more time talking to practitioners? As someone who enjoys talking to people in the business, I would say the answer is no. While models have their problems--particularly with respect to precision--well specified models should be free of bias. To give one example, modeling drove me to conclude three years ago that capitalization rates for commercial real estate were unsustainably low. I wasn't sure when they would rise, I was just sure that they would--and as a consequence drive down commercial real estate values. My views were treated with derision by practitioners, who were convinced that we had entered a "new paradigm" wherein cap rates would always stay low and values would forever stay high.
Jim Shilling summed up the issue in his AREUEA Presidential Address. Here is the abstract:
This paper is based on my Presidential Address to the American Real Estate and Urban Economics Association delivered at Washington, D.C., in January 2003. The paper asks whether there is a risk premium puzzle in real estate. I examine this question by reporting on an empirical investigation of real estate investors' expectations over the last 15 years. The results suggest that ex ante expected risk premiums on real estate are quite large for their risk, too large to be explained by standard economic models. Further, the results suggest that ex ante expected returns are higher than average realized equity returns over the past 15 years because realized returns have included large unexpected capital losses. The latter conclusion suggests that using historical averages to estimate the risk premium on real estate is misleading.
I actually do learn a lot by talking to people who do real estate. I just don't learn a lot about future returns.