Efficient Estimation of Hedonic Inverse Input Demand Systems
提出一种基于扩展随机系数模型的改进估计方法，替代Brown和Rosen的两阶段法，利用冰岛鱼拍卖的172,946个观测数据估计质量特征的需求，结果显示新方法更高效，并发现质量需求普遍上升。
This article is concerned with efficient estimation of characteristics demand. We derive and estimate an inverse input demand system for quality characteristics by using 172,946 observations over 881 trading days in the Icelandic fish auctions. An improved estimation method based on an expanded random coefficient model is suggested as an alternative to the currently used two‐stage method of Brown and Rosen. The estimates demonstrate the improved efficiency of the suggested method. A number of empirical results emerge, including a general increase in the demand for quality.