Valuing Product Attributes Using Single Market Data: A Comparison of Hedonic and Discrete Choice Approaches
通过模拟数据比较多项Logit模型和特征价格模型在估计消费者对产品属性偏好上的表现，发现线性Box-Cox特征价格函数在估计边际属性出价上不逊于线性Logit模型，但Logit模型在评估非边际属性变化时更优。
This paper compares, via simulation, the perfor- mance of the multinomial logit and hedonic models in esti- mating consumer preferences for product attributes. We as- cribe preferences over the attributes of houses to a population of consumers, and, by having them bid for a set of houses, calculate equilibrium prices. The resulting data are used to estimate the two models. We find that the gradient of a linear Box-Cox hedonic price function estimates marginal attribute bids at least as well as a linear logit model, although the difference between the two is small when some variables are not observed or are replaced by proxies. The logit model, however, outperforms the he- donic model in valuing non-marginal attribute changes. This is true when the researcher knows the true form of consumers' utility functions and when the utility function must be approx- irnated.