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This paper assesses the predictive power of variables that measure market tightness, such as seller's bargaining power and sale probabilities, on future home prices. Theoretical insights from a stylized search-and-matching model illustrate that such indicators can be associated with subsequent home price appreciation. The empirical analysis employs data on all residential units offered for sale through a real estate broker in the Netherlands and a large suburb in the Washington, DC area. Individual records are used to construct a quarterly home price index, an index that measures seller's bargaining power, and (quality adjusted) home sale probabilities. Using conventional time-series models we show that current sale probabilities and bargaining power can significantly reduce home price appreciation forecast errors.

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