Summary of Information Value of Property Description: A Machine Learning Approach, with Stephen L. Ross. A machine-learning measure of the soft information in listing text raises sale prices by 15 percent per standard deviation in a hedonic model and 10 percent in a repeat-sales model, and price indices that ignore it overstate prices by 10 to 23 percent and mistime the post-recession stabilization.
Summary of The Odd One Out? The Impact of Property Uniqueness on Selling Time and Selling Price, with Thomas M. Springer. Machine-learning measures of uniqueness from listing text show that a one-standard-deviation increase in market uniqueness raises sale prices by 13 percent ($48,490) while delaying sale by 1.7 days; universal uniqueness raises prices 11 percent ($41,030) at a 3-day delay.
Soft information is what a listing says that structured fields cannot: condition, character, seller circumstances, local demand. This explainer defines the term, contrasts it with hard information, and summarizes what my research finds when listing text is measured with machine learning: it is priced, it changes marketing time, and it moves before price indices do.