Blue Lies

We introduce the “blue lies game,” a sender-receiver interaction where lying benefits both the liar and her ingroup member at the outgroup’s expense. Across 9,672 U.S. participants assigned to groups based on either random allocation or political partisanship, 38–57% of senders lie. An ingroup truth-telling norm reduces blue lies, but the same norm attributed to the outgroup has no effect or backfires among strong identifiers. Adding the option to remain silent cuts blue lies sharply and raises aggregate welfare. We structurally estimate via GMM a model that separates lying motives into monetary self-interest, ingroup loyalty, outgroup disregard, and honesty costs, and use it to quantify the welfare losses that blue lies impose. These findings have implications for understanding deception in polarized environments and designing interventions to reduce misinformation.