Don't follow the leader: how ranking performance reduces meritocracy

Editorial verdict

Theoretically rigorous simulation study with clear limitations — the agent-based model generates compelling dynamics showing imitation undermines meritocracy, but the stylized assumptions (no agent memory, static payoffs, no network structure) constrain direct real-world applicability; treat the directional findings as hypothesis-generating, not prescriptive.

Executive summary

This paper addresses the tension between performance ranking systems and genuine meritocratic outcomes in modern economies. The author argues that ranking-driven imitation of top performers is a self-defeating strategy that consolidates early advantages of lucky — rather than necessarily talented — individuals. Using an agent-based numerical simulation with N agents selecting among M actions, the study contrasts two action-selection mechanisms: imitation of better-ranked peers (parameterised by q) and random exploration (serendipity). Key findings demonstrate that higher imitation propensity (high q) increases aggregate utility but simultaneously raises inequality (measured via Gini coefficient), reduces correlation between agents' intrinsic fitness and ranking outcomes, homogenizes the action space, and freezes ranking mobility. Conversely, lower imitation propensity (low q) preserves upward ranking mobility, maintains diversity of strategies, and produces outcomes more aligned with agents' intrinsic capabilities. The model draws on Goodhart's Law, the Hawthorne effect, and empirical parallels in academia, financial markets, and sports. The author concludes that performance ranking systems, as currently implemented, structurally undermine the meritocratic goals they purport to serve.

Frameworks mentioned

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