Can Tightness in the Housing Market Help Predict Subsequent Home Price Appreciation? Evidence from the United States and the Netherlands

Paul E. Carrillo, Erik R. de Wit, W. Larson
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引用次数: 27

Abstract

This article 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 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‐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 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.
住房市场的紧缩能帮助预测随后的房价升值吗?来自美国和荷兰的证据
本文评估了衡量市场紧张程度的变量的预测能力,如卖方的议价能力和销售概率,对未来房价的预测能力。从一个程式化的搜索和匹配模型的理论见解表明,这些指标可以与随后的房价升值相关联。实证分析采用了荷兰和美国某些地区的房地产经纪人提供的待售住宅单元的清单数据。个人记录用于构建季度房价指数,该指数衡量卖方的议价能力和(经质量调整的)房屋销售概率。使用传统的时间序列模型,我们发现当前的销售概率和议价能力可以显著降低房价升值预测误差,并有助于预测当地住房市场的拐点。本文中的措施和方法有助于展示研究人员和从业人员如何利用房源数据来获取有关房地产市场当前和未来状况的知识。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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