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    When are purely predictive models best?

    Northcott, Robert (2017) When are purely predictive models best? Disputatio 9 (47), pp. 631-656. ISSN 0873-626X.

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    Abstract

    Can purely predictive models be useful in investigating causal systems? I argue ‘yes’. Moreover, in many cases not only are they useful, they are essential. The alternative is to stick to models or mechanisms drawn from well-understood theory. But a necessary condition for explanation is empirical success, and in many cases in social and field sciences such success can only be achieved by purely predictive models, not by ones drawn from theory. Alas, the attempt to use theory to achieve explanation or insight without empirical success therefore fails, leaving us with the worst of both worlds – neither prediction nor explanation. Best go with empirical success by any means necessary. I support these methodological claims via case studies of two impressive feats of predictive modelling: opinion polling of political elections, and weather forecasting.

    Metadata

    Item Type: Article
    School: Birkbeck Faculties and Schools > Faculty of Humanities and Social Sciences > School of Historical Studies
    Depositing User: Robert Northcott
    Date Deposited: 13 Feb 2017 15:41
    Last Modified: 02 Aug 2023 17:31
    URI: https://eprints.bbk.ac.uk/id/eprint/18061

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