A critical value function approach, with an application to persistent time-series

Marcelo Moreira, Rafael Mourão and Humberto Moreira
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Rafael Mourão: Institute for Fiscal Studies
Humberto Moreira: Institute for Fiscal Studies

No CWP24/16, CeMMAP working papers from Centre for Microdata Methods and Practice, Institute for Fiscal Studies

Abstract: 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. Supplement for CWP24/16

Keywords: t-statistic; bootstrap; subsampling; similar tests. (search for similar items in EconPapers)
Date: 2016-06-14
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Citations: View citations in EconPapers (4)

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Working Paper: A critical value function approach, with an application to persistent time-series (2016)
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