Replication data for: Demand Estimation under Incomplete Product Availability

Principal Investigator(s): View help for Principal Investigator(s) Christopher T. Conlon; Julie Holland Mortimer

Name	File Type	Size	Last Modified
CPP-Code-MSL			12/07/2019 03:18:PM
Matlab-Code			12/07/2019 03:18:PM
NL-Code-AMPL			12/07/2019 03:18:PM
AEJ-ReadMe.pdf	application/pdf	140.5 KB	12/07/2019 10:18:AM
setup.do	text/plain	5.2 KB	12/07/2019 10:18:AM
tables.do	text/plain	4.5 KB	12/07/2019 10:18:AM

Project Description

Summary: 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.

Scope of Project

JEL Classification:
      D12 Consumer Economics: Empirical Analysis
      D25 Intertemporal Firm Choice: Investment, Capacity, and Financing
      G31 Capital Budgeting; Fixed Investment and Inventory Studies; Capacity
      L81 Retail and Wholesale Trade; e-Commerce
      M11 Production Management

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Published Versions

V1 [2019-12-07]

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Dublin Core

DDI 2.5

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