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Published online by Cambridge University Press:  08 February 2005

Hannes Leeb
Yale University
Benedikt M. Pötscher
University of Vienna


Model selection has an important impact on subsequent inference. Ignoring the model selection step leads to invalid inference. We discuss some intricate aspects of data-driven model selection that do not seem to have been widely appreciated in the literature. We debunk some myths about model selection, in particular the myth that consistent model selection has no effect on subsequent inference asymptotically. We also discuss an “impossibility” result regarding the estimation of the finite-sample distribution of post-model-selection estimators.

Research Article
© 2005 Cambridge University Press

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