Improving on ‘Data mining reconsidered’ by K.D. Hoover and S.J. Perez

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Abstract

Kevin Hoover and Stephen Perez take important steps towards resolving somekey issues in econometric methodology. They simulate general-to-specific selection for linear, dynamic regression models, and find that their algorithm performs well in re-mining the ‘Lovell databasersquo;. We discuss developments that improve on their results, automated in PcGets. Monte Carlo experiments and re-analyses of empirical studies show that pre-selection F-tests, encompassing tests, and sub-sample reliability checks all help eliminate ‘spuriously-significant’ regressors, without impugning recovery of the correct specification.

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