Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/79566
Authors: 
Dickhaus, Thorsten
Year of Publication: 
2012
Series/Report no.: 
SFB 649 Discussion Paper 2012-033
Abstract: 
Based on the theory of multiple statistical hypothesis testing, we elaborate simultaneous statistical inference methods in dynamic factor models. In particular, we employ structural properties of multivariate chi-squared distributions in order to construct critical regions for vectors of likelihood ratio statistics in such models. In this, we make use of the asymptotic distribution of the vector of test statistics for large sample sizes, assuming that the model is identified and model restrictions are testable. Examples of important multiple test problems in dynamic factor models demonstrate the relevance of the proposed methods for practical applications.
Subjects: 
family-wise error rate
false discovery rate
likelihood ratio statistic
multiple hypothesis testing
multivariate chi-squared distribution
time series regression
Wald statistic
JEL: 
C12
C32
C52
Document Type: 
Working Paper

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