This paper studies unobserved heterogeneity in hedonic price models, arising from missing property and locational characteristics. Specifically, commercial real estate is very heterogeneous, and data on detailed property characteristics are often lacking. We show that adding mutually independent property random effects to a hedonic price model results in more precise out-of-sample price predictions, both for commercial multifamily housing in Los Angeles and owner-occupied single-family housing in Heemstede, the Netherlands. The standard hedonic price model does not take advantage of the fact that some properties sell more than once. We subsequently show that adding spatial random effects leads to an additional increase in prediction accuracy. The increase is highest for properties without prior sales.

中文翻译：

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对享乐价格模型中未观察到的异质性进行建模

本文研究了享乐价格模型中未观察到的异质性，这是由缺失的财产和位置特征引起的。具体而言，商业地产的异质性很强，往往缺乏详细的房产特征数据。我们表明，将相互独立的财产随机效应添加到享乐价格模型会导致更精确的样本外价格预测，无论是对于洛杉矶的商业多户住宅还是荷兰海姆斯泰德的自住独户住宅。标准的享乐价格模型没有利用某些房产不止一次销售的事实。我们随后表明，添加空间随机效应会导致预测精度的额外增加。对于没有事先销售的物业，增幅最高。