GMM Repeat Sales Price Indices
提出一种基于广义矩方法的重复销售回归模型，用于估计非流动性资产价格指数，能处理自定义加权、享乐变量和样本偏差问题，模拟显示比传统方法更准确。
Illiquid assets are widely spread within the economy but their indices are difficult to measure. This paper proposes a Generalized Method of Moment (GMM) repeat sales regression for estimating illiquid asset price indices. This method has estimators that are arithmetic averages of individual asset returns. This method is able to estimate custom‐weighted indices, including equal‐ and value‐weighted indices. It can incorporate hedonic variables to improve estimation accuracy, and it can work with a reweighting technique to mitigate a biased sample problem. Simulations based on artificial markets indicate that the method is more accurate than some alternatives in both efficient and sluggish markets, with and without temporal aggregation. As an application, we use this method to estimate a commercial property price index.