Working Paper: NBER ID: w14315
Authors: Christopher T. Conlon; Julie Holland Mortimer
Abstract: Incomplete product availability is an important feature of many markets; ignoring changes in availability may bias demand estimates. We study a new dataset from a wireless inventory system installed on 54 vending machines to track product availability every four hours. The data allow us to account for product availability when estimating demand, and provides a valuable source of variation for identifying substitution patterns. We develop a procedure that allows for changes in product availability even when availability is only observed periodically. We find significant differences in demand estimates, with the corrected model predicting significantly larger impacts of stock-outs on profitability.
Keywords: demand estimation; product availability; vending machines; stockouts; inventory management
JEL Codes: L0
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| stockouts (L81) | demand underestimation (R22) |
| incomplete product availability (L15) | biased demand estimates (C51) |
| forced substitution during stockouts (C69) | overstated demand for available products (J23) |
| stockouts (L81) | profitability (L21) |