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Conducting Research with Quasi-Experiments: A Guide for Marketers

SSRN Electronic Journal
2022
  • 46
    Citations
  • 10,741
    Usage
  • 127
    Captures
  • 0
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

  • Citations
    46
    • Citation Indexes
      46
  • Usage
    10,741
    • Abstract Views
      7,980
    • Downloads
      2,761
  • Captures
    127
  • Ratings
    • Download Rank
      9,732

Article Description

This paper 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 paper explores how to identify settings and data where it is interesting to understand whether an action causally affects a marketing outcome. Second, the paper outlines how to structure an empirical strategy that allows the author to identify a causal empirical relationship. The paper 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 paper emphasizes the importance of clearly communicating the identifying assumptions underlying the assertion of causality. Last, the paper explains how exploring the behavioral mechanism— whether individual, organizational, or market-level— can actually reinforce arguments of causality.

Bibliographic Details

Avi Goldfarb; Catherine E. Tucker; Yanwen Wang

Elsevier BV

Quasi-Experiments; Econometric Methods; Marketing; Practioner's Guide

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