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Erscheinungsjahr: 
2016
Schriftenreihe/Nr.: 
cemmap working paper No. CWP24/16
Verlag: 
Centre for Microdata Methods and Practice (cemmap), London
Zusammenfassung: 
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.
Schlagwörter: 
t-statistic
bootstrap
subsampling
similar tests
Persistent Identifier der Erstveröffentlichung: 
Dokumentart: 
Working Paper

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