A regime-adaptive projection wild bootstrap achieves uniform validity for two-way clustered regression inference across four feasible asymptotic regimes while permitting serial and spatial dependence.
Journal of econometrics , volume=
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Participatory provenance auditing of Canada's AI strategy consultation shows official AI summaries exclude 15-17% of participants more than random baselines, with 33-88% exclusion for dissent clusters.
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Bootstrap Inference under General Two-way Clustering with Serially and Spatially Dependent Common Effects
A regime-adaptive projection wild bootstrap achieves uniform validity for two-way clustered regression inference across four feasible asymptotic regimes while permitting serial and spatial dependence.
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Participatory provenance as representational auditing for AI-mediated public consultation
Participatory provenance auditing of Canada's AI strategy consultation shows official AI summaries exclude 15-17% of participants more than random baselines, with 33-88% exclusion for dissent clusters.
- Estimation and Inference for the $\tau$-Quantile of Individual Heterogeneous Coefficient