arXiv (OAI Expanded)
open access
When Can You Trust Your Synthetic Users? Diagnostics and Corrections for LLM Consumer Panels
Large language models are increasingly deployed as synthetic consumer panels, promising $97\%$ cost reductions over traditional surveys. Yet aggregate validation metrics conceal systematic failures: variance compression, coefficient sign-flips, subgroup error balloons of 10--30 percentage points, an
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