Conducting Research in Marketing with Quasi-Experiments
Name
00222429221082977.pdf
Description
Published version
Size
670.71 KB
Format
Adobe PDF
Checksum (MD5)
8db45f65f916e9ca99153ae8374c9963
Author(s)
Goldfarb, Avi
Tucker, Catherine
Wang, Yanwen
Date Issued
May 2022
Journal
Journal of Marketing
Publisher
SAGE Publications
Citation
Goldfarb, Avi, Tucker, Catherine and Wang, Yanwen. 2022. "Conducting Research in Marketing with Quasi-Experiments." Journal of Marketing, 86 (3).
Version
Final published version
Abstract
This article aims to broaden the understanding of quasi-experimental methods among marketing scholars and those who read their work by describing the underlying logic and set of actions that make their work convincing. The purpose of quasi-experimental methods is, in the absence of experimental variation, to determine the presence of a causal relationship. First, the authors explore how to identify settings and data where it is interesting to understand whether an action causally affects a marketing outcome. Second, they outline how to structure an empirical strategy to identify a causal empirical relationship. The article details the application of various methods to identify how an action affects an outcome in marketing, including difference-in-differences, regression discontinuity, instrumental variables, propensity score matching, synthetic control, and selection bias correction. The authors emphasize the importance of clearly communicating the identifying assumptions underlying the assertion of causality. Last, they explain how exploring the behavioral mechanism—whether individual, organizational, or market level—can actually reinforce arguments of causality.
MIT Department
Sloan School of Management
Terms of Use
Creative Commons Attribution NonCommercial License 4.0
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1177/00222429221082977
