Showing 1 - 10 of 37
This paper proposes a novel regularisation method for the estimation of large covariance matrices, which makes use of insights from the multiple testing literature. The method tests the statistical significance of individual pair-wise correlations and sets to zero those elements that are not...
Persistent link: https://www.econbiz.de/10010361374
Persistent link: https://www.econbiz.de/10010366306
This paper takes a multiple testing perspective on the problem of determining the cointegrating rank in macroeconometric panel data with cross-sectional dependence. The testing procedure for a common rank among the panel units is based on Simes' (1986) intersection test and requires only the...
Persistent link: https://www.econbiz.de/10011616223
This paper takes a multiple testing perspective on the problem of determining the cointegrating rank in macroeconometric panel data with cross-sectional dependence. The testing procedure for a common rank among the panel units is based on Simes’ (1986) intersection test and requires only the...
Persistent link: https://www.econbiz.de/10011453075
Consider the problem of testing s hypotheses simultaneously. In order to deal with themultiplicity problem, the classical approach is to restrict attention to procedures that controlthe familywise error rate (FWE). Typically, it is known how to construct tests of the individualhypotheses, and...
Persistent link: https://www.econbiz.de/10005868541
This paper introduces a computationally efficient bootstrap procedure for obtaining multiplicity-adjusted p-values in situations where multiple hypotheses are tested simultaneously. This new testing procedure accounts for the mutual dependence of the individual statistics, and is shown under...
Persistent link: https://www.econbiz.de/10005585311
It is common in econometric applications that several hypothesis tests are carried out at the same time. The problem then becomes how to decide which hypotheses to reject, accounting for the multitude of tests. In this paper, we suggest a stepwise multiple testing procedure which asymptotically...
Persistent link: https://www.econbiz.de/10005771987
Consider the problem of testing k hypotheses simultaneously. In this paper, we discuss finite and large sample theory of stepdown methods that provide control of the familywise error rate (FWE). In order to improve upon the Bonferroni method or Holm's (1979) stepdown method, Westfall and Young...
Persistent link: https://www.econbiz.de/10005772539
It is common in econometric applications that several hypothesis tests are carried out at the same time. The problem then becomes how to decide which hypotheses to reject, accounting for the multitude of tests. The classical approach is to control the familywise error rate (FWE), that is, the...
Persistent link: https://www.econbiz.de/10005627940
It is common in econometric applications that several hypothesis tests are carried out at the same time. The problem then becomes how to decide which hypotheses to reject, accounting for the multitude of tests. In this paper, we suggest a stepwise multiple testing procedure which asymptotically...
Persistent link: https://www.econbiz.de/10010547259