Dependence‐robust inference using resampled statistics

We develop inference procedures robust to general forms of weak dependence. The use test statistics constructed by resampling data in a manner that does not depend on the unknown correlation structure data. prove are asymptotically normal under requirement target parameter can be consistently estimated at parametric rate. This holds for regular estimators many well-known dependence and justifies claim dependence-robustness. consider applications settings with or complicated dependence, various network as leading examples. tests both moment equalities inequalities.