1. bookVolume 9 (2017): Issue 47 (December 2017)
Journal Details
License
Format
Journal
eISSN
2182-2875
First Published
16 Apr 2017
Publication timeframe
4 times per year
Languages
English
access type Open Access

When are Purely Predictive Models Best?

Published Online: 16 Oct 2018
Volume & Issue: Volume 9 (2017) - Issue 47 (December 2017)
Page range: 631 - 656
Received: 05 Sep 2017
Accepted: 02 Nov 2017
Journal Details
License
Format
Journal
eISSN
2182-2875
First Published
16 Apr 2017
Publication timeframe
4 times per year
Languages
English
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.

Keywords

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