When are Purely Predictive Models Best?

Disputatio 9 (47):631-656 (2017)
Download Edit this record How to cite View on PhilPapers
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.
(categorize this paper)
PhilPapers/Archive ID
Revision history
Archival date: 2019-05-10
View upload history
References found in this work BETA
Thinking About Mechanisms.Machamer, Peter K.; Darden, Lindley & Craver, Carl F.

View all 23 references / Add more references

Citations of this work BETA
What’s so Special About Empirical Adequacy?Bhakthavatsalam, Sindhuja & Cartwright, Nancy

Add more citations

Added to PP index

Total views
37 ( #41,727 of 46,191 )

Recent downloads (6 months)
22 ( #32,470 of 46,191 )

How can I increase my downloads?

Downloads since first upload
This graph includes both downloads from PhilArchive and clicks to external links.