Can LLMs Anticipate Behavioral Responses to Social Policies? FlexPension-LLM for Flexible Workers

Evaluating social policy shifts often stalls between costly field trials and brittle econometric extrapolations. To predict pension enrollment choices among China’s flexible workers, researchers introduced FlexPension-LLM, distilling provincial pension rules and Probit-derived marginal effects into an open-weight MoE architecture. Tested on a CHFS 2019 blind split, it achieved a 0.9316 composite F1—surpassing its Claude Sonnet 4.5 teacher and matching Claude Opus 4.6. The framework demonstrates how rationale-guided distillation can simulate micro-level economic behaviors while maintaining auditable policy decision traces.