Template-type: ReDIF-Paper 1.0
Author-Name: Andrew T. Ching
Author-Workplace-Name: Rotman School of Management, University of Toronto, Canada
Author-Email: Andrew.Ching@rotman.utoronto.ca
Author-Name: Tülin Erdem 
Author-Workplace-Name: Stern School of Business, New York University, USA
Author-Email: terdem@stern.nyu.edu
Author-Name: Michael P. Keane
Author-Workplace-Name: Nuffield College, University of Oxford
Author-Email: michael.keane@nuffield.ox.ac.uk
Title: A Simple Method to Estimate the Roles of Learning, Inventories and Category Consideration in Consumer Choice
Abstract: Models of consumer learning and inventory behavior have both proven to be valuable for explaining 
consumer choice dynamics. In their pure form these models assume consumers solve complex dynamic 
programming (DP) problems to determine optimal choices. For this reason, these models are best viewed as
“as if” approximations to consumer behavior. In this paper we present an estimation method, based on 
Geweke and Keane (2000), which allows us to estimate dynamic models without solving a DP problem and 
without strong assumptions about how consumers form expectations about the future. The relatively low 
computational burden of this method allows us to nest the learning and inventory models. We also 
incorporate the “price consideration” mechanism of Ching, Erdem and Keane (2009), which essentially 
says that consumers may not pay attention to a category in every period. The resulting model may be 
viewed as providing a more “realistic” or “descriptive” account of consumer choice behavior.
X-Classification-JEL: 
X-Keywords: 
Length: 25 pages
Creation-Date: 2014-07-07
Number: 2014-W01
File-URL: http://www.nuffield.ox.ac.uk/economics/papers/2014/learn_inventory_JOCM_1.pdf
File-Format: application/pdf
Handle: RePEc:nuf:econwp:1401