Romano, Joseph P.; Wolf, Michael Stepwise multiple testing as formalized data snooping. (English) Zbl 1153.62310 Econometrica 73, No. 4, 1237-1282 (2005). Summary: In econometric applications, often several hypothesis tests are carried out at once. The problem then becomes how to decide which hypotheses to reject, accounting for the multitude of tests. This paper suggests a stepwise multiple testing procedure that asymptotically controls the familywise error rate. Compared to related single-step methods, the procedure is more powerful and often will reject more false hypotheses. In addition, we advocate the use of studentization when feasible. Unlike some stepwise methods, the method implicitly captures the joint dependence structure of the test statistics, which results in increased ability to detect false hypotheses. The methodology is presented in the context of comparing several strategies to a common benchmark. However, our ideas can easily be extended to other contexts where multiple tests occur. Some Simulation studies show the improvements of our methods over previous proposals. We also provide an application to a set of real data. Cited in 1 ReviewCited in 51 Documents MSC: 62F03 Parametric hypothesis testing 62P20 Applications of statistics to economics 62J15 Paired and multiple comparisons; multiple testing Keywords:bootstrap; data snooping; familywise error; multiple testing; stepwise method PDFBibTeX XMLCite \textit{J. P. Romano} and \textit{M. Wolf}, Econometrica 73, No. 4, 1237--1282 (2005; Zbl 1153.62310) Full Text: DOI Link