Simultaneous Statistical Inference in Dynamic Factor Models
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.
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- Mario Forni & Marc Hallin & Lucrezia Reichlin & Marco Lippi, 2000.
"The generalised dynamic factor model: identification and estimation,"
ULB Institutional Repository
2013/10143, ULB -- Universite Libre de Bruxelles.
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"Opening the black box: structural factor models with large cross-sections,"
Working Paper Series
0712, European Central Bank.
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Journal of the American Statistical Association,
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Discussion Paper Series 1: Economic Studies
2005,38, Deutsche Bundesbank, Research Centre.
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