A critical value function approach, with an application to persistent time-series - Marcelo J. Moreira; Rafael Mour\~ao; Humberto Moreira (Centre for Microdata Methods and Practice (cemmap), 2016)
Researchers often rely on the t-statistic to make inference on parameters in statistical models. It is common practice to obtain critical values by simulation techniques. This paper proposes a novel numerical method to obtain an approximately similar test. This test rejects the null hypothesis when the test statistic is larger than a critical value function (CVF) of the data. We illustrate this procedure when regressors are highly persistent, a case in which commonly-used simulation methods encounter difficulties controlling size uniformly. Our approach works satisfactorily, controls size, and yields a test which outperforms the two other known similar tests.
Keywords: 330; t-statistic; bootstrap; subsampling; similar tests