Loss aversion is a widely-recognized cognitive bias that can affect house price determination. Existing empirical approaches to quantify its effects require hedonic methods to predict what prices would be in the absence of loss aversion. However, conventional methods for making this counterfactual prediction unrealistically preclude time variation in the hedonic values of housing attributes, thereby exacerbating specification error and reducing the accuracy of point estimates. We show how time-varying hedonic regression (TVHR) can overcome this deficiency by allowing hedonic values to change over time. Applying the method to a dataset of residential transactions from Auckland, New Zealand, that spans 2009 to 2018, we find that loss aversion significantly inflates transaction prices. However, by comparison, existing methods yield imprecise estimates of this premium that are implausibly large and sensitive to the sample period selected. Our findings suggest that THVR is an attractive alternative to conventional approaches to quantifying loss aversion.

损失规避是一种公认​​的认知偏见，可能会影响房价的确定。现有的量化其影响的经验方法需要享乐主义方法来预测在没有损失厌恶的情况下的价格。但是，用于进行这种反事实预测的常规方法不切实际地排除了房屋属性的特征值的时间变化，从而加剧了规格误差并降低了点估计的准确性。我们展示了时变享乐回归（TVHR）如何通过允许享乐值随时间变化来克服此缺陷。将方法应用于从2009年到2018年的新西兰奥克兰市的住宅交易数据集，我们发现损失回避会大大抬高交易价格。但是，相比之下，现有方法得出的溢价估算不精确，而且难以估计，而且对所选的采样周期非常敏感。我们的发现表明，THVR是量化损失规避的传统方法的一种有吸引力的替代方法。