Pitfalls of post-model-selection testing: experimental quantification |
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Authors: | Matei Demetrescu Uwe Hassler Vladimir Kuzin |
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Affiliation: | 1.Statistics and Econometric Methods (PF 49),Goethe University Frankfurt,Frankfurt,Germany;2.DIW Berlin,Berlin,Germany |
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Abstract: | Traditional specification testing does not always improve subsequent inference. We demonstrate by means of computer experiments under which circumstances, and how severely, data-driven model selection can destroy the size properties of subsequent parameter tests, if they are used without adjusting for the model-selection step. The investigated models are representative of macroeconometric and microeconometric workhorses. The model selection procedures include information criteria as well as sequences of significance tests (“general-to-specific”). We find that size distortions can be particularly large when competing models are close, with closeness being defined relatively to the sample size. |
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