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Theoretical insights from a stylized search\u2010and\u2010matching model illustrate that such indicators can be associated with subsequent home price appreciation. The empirical analysis employs listings data on residential units offered for sale through a real estate broker in the Netherlands and for certain U.S. regions. Individual records are used to construct quarterly home price indices, an index that measures seller's bargaining power and (quality\u2010adjusted) home sale probabilities. Using conventional time\u2010series models we show that current sale probabilities and bargaining power can significantly reduce home price appreciation forecast errors and help to predict turning points in local area housing markets. The measures and approaches in this article help to demonstrate ways in which researchers and practitioners can leverage listings data to gain knowledge about the current and future state of the housing market.</jats:p>",51 "DOI": "10.1111/1540-6229.12082",52 "type": "journal-article",53 "created": {54 "date-parts": [55 [56 2015,57 1,58 1359 ]60 ],61 "date-time": "2015-01-13T03:08:35Z",62 "timestamp": 142111851500063 },64 "page": "609-651",65 "source": "Crossref",66 "is-referenced-by-count": 34,67 "title": [68 "Can Tightness in the Housing Market Help Predict Subsequent Home Price Appreciation? 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