Demand Estimation Under Incomplete Product Availability
研究了产品可用性不完全时需求估计的偏差问题，利用自动售货机无线库存系统的数据，每四小时追踪产品可用性，提出一种考虑周期性观测可用性变化的估计方法，发现修正模型预测缺货事件对盈利的影响显著更大。
Incomplete product availability is an important feature of many markets, and ignoring changes in availability may bias demand estimates. We study a new dataset from a wireless inventory system on vending machines to track product availability every four hours. The data allow us to account for product availability when estimating demand, and provide valuable variation for identifying substitution patterns when products stock out. We develop a procedure that allows for changes in product availability when availability is only observed periodically. We find significant differences in demand estimates: the corrected model predicts significantly larger impacts of stock-out events on profitability.