Optimal HAR inference
最优异方差与自相关稳健推断
This paper considers the problem of deriving heteroskedasticity and autocorrelation robust (HAR) inference about a scalar parameter of interest. The main assumption is that there is a known upper bound on the degree of persistence in data. I derive finite‐sample optimal tests in the Gaussian location model and show that the robustness‐efficiency tradeoffs embedded in the optimal tests are essentially determined by the maximal persistence. I find that with an appropriate…