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What is Robust Two-Sample Mean Inference Under Serial Dependence about?

This paper introduces robust two-sample tests for comparing means in time series data, addressing issues of serial dependence and heterogeneity. The authors propose a series HAR two-sample t-test and a wild bootstrap test that improve upon traditional methods by ensuring valid inference under complex dependence structures. Empirical applications demonstrate that the proposed methods yield no significant differences in average performance across groups when accounting for sampling variation and autocorrelati

Author

aadis202020

Language

EN