Search for differentiated products: identification and estimation
研究了消费者搜索差异化产品时，如何区分低搜索成本与低偏好导致的搜索决策，提出利用条件搜索决策数据估计搜索成本分布的方法，并用酒店搜索平台点击流数据验证，发现搜索模型估计的需求价格弹性与静态模型不同，反映了内生性偏差。
When consumers search for differentiated products, a given search decision can be explained either by low search cost or by low tastes for the set of products already found. We propose an identification strategy that allows to estimate the search cost distribution in the presence of unobserved tastes. The required data takes the form of conditional search decisions: observations of search actions combined with previously observed product displays. We develop an application using clickstream data from a hotel search platform. Estimates of price elasticity of demand in the search model differ from those in the static model, reflecting the bias due to endogeneity of search‐generated choice sets.