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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Double/debiased ML framework for average derivative effects in panel data with continuous treatments, two-way fixed effects, and endogeneity.
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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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Double/Debiased Machine Learning for Continuous Treatment Effects in Panel Data with Endogeneity
Double/debiased ML framework for average derivative effects in panel data with continuous treatments, two-way fixed effects, and endogeneity.
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