How Mega Is the Mega? Exploring the Spillover Effects of WeChat Using Graphical Model

Abstract

WeChat, an instant messaging app, is considered a mega app because of its dominance in terms of use among Chinese smartphone users. A major concern for such an app is whether its increasing usage would crowd out the usage of other apps in the broader app market. This study estimates the spillover effects of WeChat on the other top 50 most frequently used apps in China, using users’ weekly app usage data. Given the challenge of determining causal inference from observational data, this study borrows a machine-learning method and integrates it with econometrics. We find that WeChat does not crowd out the other apps’ use. In fact, only two other apps, Tencent News and Taobao, are affected by WeChat usage causally, and interestingly, both receive positive spillover effects as a result of the complementary effects. This finding alleviates concerns about the threat by WeChat and indicates that WeChat’s success is not in exchange for squeezing out the use of other major apps. Instead, WeChat might contribute to the platform by transforming users’ nonmobile activities to the mobile setting and by exhibiting some positive spillovers. In addition, this study shows the strength of graphical models in identifying causal relationships from observational data.