Improving on 'Data Mining Reconsidered' by K. D. Hoover and S. J. Perez.
Kevin Hoover and Stephen Perez take important steps towards resolving some key 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 database";. We discuss d...
| Main Authors: | , |
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| Format: | Journal article |
| Language: | English |
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Blackwell Publishing
1999
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| _version_ | 1797057421936427008 |
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| author | Hendry, D Krolzig, H |
| author_facet | Hendry, D Krolzig, H |
| author_sort | Hendry, D |
| collection | OXFORD |
| description | Kevin Hoover and Stephen Perez take important steps towards resolving some key 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 database";. 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. |
| first_indexed | 2024-03-06T19:36:06Z |
| format | Journal article |
| id | oxford-uuid:1f18c1ec-a19a-4ead-bc33-a705f5500616 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-06T19:36:06Z |
| publishDate | 1999 |
| publisher | Blackwell Publishing |
| record_format | dspace |
| spelling | oxford-uuid:1f18c1ec-a19a-4ead-bc33-a705f55006162022-03-26T11:20:00ZImproving on 'Data Mining Reconsidered' by K. D. Hoover and S. J. Perez.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:1f18c1ec-a19a-4ead-bc33-a705f5500616EnglishDepartment of Economics - ePrintsBlackwell Publishing1999Hendry, DKrolzig, HKevin Hoover and Stephen Perez take important steps towards resolving some key 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 database";. 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. |
| spellingShingle | Hendry, D Krolzig, H Improving on 'Data Mining Reconsidered' by K. D. Hoover and S. J. Perez. |
| title | Improving on 'Data Mining Reconsidered' by K. D. Hoover and S. J. Perez. |
| title_full | Improving on 'Data Mining Reconsidered' by K. D. Hoover and S. J. Perez. |
| title_fullStr | Improving on 'Data Mining Reconsidered' by K. D. Hoover and S. J. Perez. |
| title_full_unstemmed | Improving on 'Data Mining Reconsidered' by K. D. Hoover and S. J. Perez. |
| title_short | Improving on 'Data Mining Reconsidered' by K. D. Hoover and S. J. Perez. |
| title_sort | improving on data mining reconsidered by k d hoover and s j perez |
| work_keys_str_mv | AT hendryd improvingondataminingreconsideredbykdhooverandsjperez AT krolzigh improvingondataminingreconsideredbykdhooverandsjperez |