Brown, Imai, Vieider, Camerer (JEL 2024) — meta-analysis of 607 loss-aversion estimates; mean λ = 1.955, CI [1.820, 2.102]

Claim: The most comprehensive synthesis of empirical loss-aversion estimates to date. Brown, Imai, Vieider, and Camerer (2024) draw on 607 empirical estimates from 150 articles spanning economics, psychology, and neuroscience (studies 1992–2017). They report a mean loss-aversion coefficient λ = 1.955 with a 95% credible interval of [1.820, 2.102].

The canonical Tversky-Kahneman 1992 estimate of λ = 2.25 — the "losses loom twice as large as gains" rule of thumb that has dominated marketing-strategy discourse for three decades — falls outside this credible interval.

Source: Brown, A. L., Imai, T., Vieider, F. M., & Camerer, C. F. (2024). "Meta-analysis of Empirical Estimates of Loss Aversion." Journal of Economic Literature 62(2): 485–516. https://www.aeaweb.org/articles?id=10.1257%2Fjel.20221698

Confidence: Verified.

Caveat: Brown et al. note that "few characteristics are substantially correlated with differences in the mean estimates." We cannot confidently claim GCs as a population show higher-than-average λ, though it is plausible given high-salience loss exposure. Research gap.

For Candid: The "loss is 2× a gain" rule is defensible as rough magnitude but not as precise multiplier. Stop citing "losses loom twice as large as gains" as if it were a precise constant — it overstates the empirical mean by ~15%. The directional point (loss aversion is real and substantial) remains.

Refines: [[kahneman-tversky-prospect-theory-loss-aversion-2to1]].