Distinguishing Spurious and Real Peer Effects: Evidence from Artificial Societies, Small-Group Experiments, and Real Schoolyards

Abstract

In a variety of important domains, there is considerable correlational evidence suggestive of what are variously referred to as social norm effects, contagion effects, information cascades, or peer effects. It is difficult to statistically identify whether such effects are causal, and there are various non-causal mechanisms that can produce such apparent norm effects. Lab experiments demonstrate that real peer effects occur, but also that apparent cascade or peer effects can be spurious. A curious feature of American local school configuration policy provides an opportunity to identify true peer influences among adolescents. Some school districts send 6th graders to middle school (e.g., 6th-8th grade "junior high"); others retain 6th graders for one additional year in K-6 elementary schools. Using administrative data on public school students in North Carolina, we have found that sixth grade students attending middle schools are much more likely to be cited for discipline problems than those attending elementary school, and the effects appear to persist at least through ninth grade. A plausible explanation is that these effects occur because sixth graders in middle schools are suddenly exposed to two cohorts of older, more delinquent peers.

The Causal Impact of Exposure to Deviant Peers

“…Of course, experiments are not without their own limitations (Berk 2005; Sampson 2010), but the impact of experimentally manipulated deviant peer exposure on behavior would provide clear and direct commentary on the debate about causality, adding to the extant research in a meaningful and less ambiguous way. Small, group experiments examining the role of peer influence have long been a staple in social psychological research but these studies have frequently examined the role of peer influence on innocuous behaviors such as estimating line length, littering, or food preferences rather than criminal conduct (Asch 1951, 1955; Birch 1980; Cialdini, Reno, and Kallgren 1990; Keizer, Lindenberg, and Steg 2008; MacCoun et al 2008). Thus, a direct focus on deviant behavior (that can also be considered illegal) is an important contribution.…”

Alternative maps of the world of collective behaviors

“…Most but not all of the plotted data points in Figures 1 and 2 come from controlled experiments. But as we journey out into the deeper waters of big data, our parameter estimates will be increasingly susceptible to bias due to spurious correlations and causal endogeneity (see MacCoun et al 2008). So our explorations promise new discoveries, but for now we might annotate our maps with the ancient warning: “Here be dragons.”…”

“…The Age of Big Data holds the promise of great discoveries, but Bentley et al make a strong case that we'll need a good map if we want to avoid aimless wandering, and they outline an impressive candidate: their map of collective behavior (henceforth “BOB”). Recently, in Psychological Review, I offered a similar “map” of social influence based on a family of logistic threshold models called BOP (“Balance of Pressures” or “Burden of Proof”; MacCoun 2012; also see Kerr & MacCoun 2012; MacCoun et al 2008). In this brief commentary, I compare and contrast the BOB and BOP maps, highlighting important points of convergence and possible divergence.…”

The burden of social proof: Shared thresholds and social influence.

“…15The agent-based simulations examined in this article allowed agents to change opinions upon contact with other agents but did not allow them to move to another location. A model variant in which agents cannot change their opinion but can move to another location can produce strikingly similar clustering patterns (MacCoun, Cook, Muschkin, & Vigdor, 2008). …”