Premium
Identification and Estimation of Online Price Competition With an Unknown Number of Firms
Author(s) -
An Yonghong,
Baye Michael R.,
Hu Yingyao,
Morgan John,
Shum Matt
Publication year - 2015
Publication title -
journal of applied econometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.878
H-Index - 99
eISSN - 1099-1255
pISSN - 0883-7252
DOI - 10.1002/jae.2492
Subject(s) - identification (biology) , competition (biology) , estimation , econometrics , economics , differential (mechanical device) , computer science , microeconomics , botany , ecology , management , biology , engineering , aerospace engineering
Summary This paper considers identification and estimation of a general model for online price competition. We show that when the number of competing firms is unknown the underlying parameters of the model can still be identified and estimated employing recently developed results on measurement errors. We illustrate our methodology using UK data for personal digital assistants and employ the estimates to simulate competitive effects. Our results reveal that heightened competition has differential effects on the prices paid by different consumer segments. Copyright © 2015 John Wiley & Sons, Ltd.