Peer Effects in Product Adoption

Abstract

We study the nature of peer effects in the market for new cell phones. Our analysis builds on deidentified data from Facebook that combine information on social networks with information on users' cell phone models. To identify peer effects, we use variation in friends' new phone acquisitions resulting from random phone losses and carrier-specific contract terms. A new phone purchase by a friend has a substantial positive and long-term effect on an individual's own demand for phones of the same brand, most of which is concentrated on the particular model purchased by the friend. We provide evidence that social learning contributes substantially to the observed peer effects. While peer effects increase the overall demand for cell phones, a friend's purchase of a new phone of a particular brand can reduce individuals' own demand for phones from competing brands-in particular those running on a different operating system. We discuss the implications of these findings for the nature of firm competition. We also find that stronger peer effects are exerted by more price-sensitive individuals. This positive correlation suggests that the elasticity of aggregate demand is substantially larger than the elasticity of individual demand. Through this channel, peer effects reduce firms' markups and, in many models, contribute to higher consumer surplus and more efficient resource allocation.

Informative Social Interactions

“…We also experimented with the respondent perception about the proportion of peers in the respondent's …nancial circle who are homeowners. This turns out to be a valid and predictive instrument, and the estimated coe¢ cients are four-fold bigger than those reported under columns (6) and (7), respectively, in Table 2a. 39 Since we …nd no statistical evidence against the null of exogeneity, the non-instrumented results reported in Table 2a are preferred.…”

“…Although the tight control of information ‡ows in both these …eld experiments helps separate information from social e¤ects, it may arti…cially magnify the importance of each signal, possibly biasing upwards the estimate of information e¤ects relative to what would have been observed for well-established …nancial products (stocks) in a mature …nancial market, where investors may be informed through a multitude of channels. 6 Finally, recent empirical work by Ozsoylev, Walden, Yavuz and Bildik (2014) attempts to identify an empirical (professional) investor network by assuming that time proximity of transactions implies network connectivity between investors. The similarities and di¤erences with these papers are further evaluated, in light of our …ndings, in Section 4.…”

“…6 SeeTable A1in the not-for-publication appendix, under columns (3) and (4), respectively. Corresponding …rst-stage regression results are reported under columns (3) and (4), respectively, in the online appendixTable A2.3 7 SeeTable A1in the online appendix, under columns (5) and (6), respectively.…”

“…Corresponding …rst-stage regression results are reported under columns (3) and (4), respectively, in the online appendixTable A2.3 7 SeeTable A1in the online appendix, under columns (5) and (6), respectively. Corresponding …rst-stage regression results are reported under columns(5) and(6), respectively, in the online appendixTable A2.3 8 A good recent example of this approach is Bailey et al (2019), which uses Facebook data to assess peer e¤ects in product adoption.…”

Technical Perspectives of Contact-Tracing Applications on Wearables for COVID-19 Control

“…The chances that the users will adopt a novel application are higher if their friends are already using it [20]. Another factor is the service provider being known and trustable along with the application not conveying large false positives or false negatives errors.…”