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Ex Ante Facts, Causal Structures, and Prediction

  1. Journals
  2. Economics, Finance, Business & Management
  3. Journal of Contextual Economics – Schmollers Jahrbuch
  4. Online First
  5. pp. 1–15

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Harris, C. Ex Ante Facts, Causal Structures, and Prediction. Journal of Contextual Economics – Schmollers Jahrbuch, 99999(), 1-15. https://doi.org/10.3790/schm.2025.401889
Harris, Chad "Ex Ante Facts, Causal Structures, and Prediction" Journal of Contextual Economics – Schmollers Jahrbuch 99999., 2025, 1-15. https://doi.org/10.3790/schm.2025.401889
Harris, Chad (2025): Ex Ante Facts, Causal Structures, and Prediction, in: Journal of Contextual Economics – Schmollers Jahrbuch, vol. 99999, iss. , 1-15, [online] https://doi.org/10.3790/schm.2025.401889
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Ex Ante Facts, Causal Structures, and Prediction

Harris, Chad

Journal of Contextual Economics – Schmollers Jahrbuch, Online First : pp. 1–15

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Additional Information

Article Details

Publisher Name
Duncker & Humblot
DOI
https://doi.org/10.3790/schm.2025.401889
Language
Multiple languages
Pages
15
License
open-access CC BY 4.0
Keywords

Author Details

Chad Harris, Department of Philosophy, University of Johannesburg, Kingsway Campus Auckland Park, 2092 Johannesburg, South Africa

References

  1. Campbell, D. 1957. “Factors Relevant to the Validity of Experiments in Social Settings.” Psychological Bulletin 54 (4): 297 – 312.  Google Scholar
  2. Cartwright, N. 1999. The Dappled World: A Study of the Boundaries of Science. Cambridge: Cambridge University Press.  Google Scholar
  3. Cartwright, N. 2007. Hunting Causes and Using Them. Cambridge: Cambridge University Press.  Google Scholar
  4. Dörge, F. C. and M. Holweger. 2021. “The Non-Existence of Institutional Facts.” Synthese 199 (3): 4953 – 4974.  Google Scholar
  5. Guala, F. 2003. “Experimental Localism and External Validity.” Philosophy of Science 70 (5): 1195 – 1205.  Google Scholar
  6. Guala, F. 2005. The Methodology of Experimental Economics. New York: Cambridge University Press.  Google Scholar
  7. Guala, F. 2012. “Experimentation in Economics.” In: Handbook of the Philosophy of Science, edited by U. Mäki, 597 – 640. Amsterdam: Elsevier.  Google Scholar
  8. Heckman, J. and R. Pinto. 2015. “Causal Analysis after Haavelmo.” Econometric Theory 31 (1): 115 – 151.  Google Scholar
  9. Mittermaier, K. 2023. A Realist Philosophy of Economics. Bristol, UK: Bristol University Press.  Google Scholar
  10. Moural, J. 2002. “Searle’s Theory of Institutional Facts: A Program of Critical Revision.” In: Speech Acts, Mind, and Social Reality, edited by G. Grewendorf and G. Meggle, 271 – 286. Dordrecht: Springer.  Google Scholar
  11. Pearl, J. (2000) 2009. Causality: Models, Reasoning and Inference. Cambridge: Cambridge University Press.  Google Scholar
  12. Pearl, J. and E. Bareinboim. 2011. “Transportability of Causal and Statistical Relations: A Formal Approach.” Proceedings of the Twenty-Fifth National Conference on Artificial Intelligence (AAAI 2011), 247 – 54. Accessed 4 Feb 2025. https://cdn.aaai.org/ojs/7861/7861-13-11389-1-2-20201228.pdf.  Google Scholar
  13. Pearl, J. and E. Bareinboim. 2013. “A General Algorithm for Deciding Transportability of Experimental Results.” Journal of Causal Inference 1 (1): 107 – 134.  Google Scholar
  14. Pearl, J. and E. Bareinboim. 2015. “External Validity: From Do-Calculus to Transportability Across Populations.” Statistical Science 29 (4): 579 – 595.  Google Scholar
  15. Rubin, D. 2005. “Causal Inference Using Potential Outcomes.” Journal of the American Statistical Association 100 (469): 322 – 331.  Google Scholar
  16. Searle, J. 1995. The Construction of Social Reality. New York: Free Press.  Google Scholar
  17. Searle, J. 2005. “What Is an Institution?” Journal of Institutional Economics 1 (1): 1 – 22.  Google Scholar
  18. Steel, D. 2008. Across the Boundaries: Extrapolation in Biology and Social Science. Oxford: Oxford University Press.  Google Scholar

Abstract

In his A Realist Philosophy of Economics Karl Mittermaier (2023) commends the importance of distinguishing between two order of facts which he designates as ex post and ex ante facts. He argues that making this distinction allows us to identify and exploit useful ex ante facts such as structural and causal factors, which in turn can be used as an epistemic warrant for making predictions. This article scrutinises work in philosophy, economics and the social sciences where attempts are made to follow through on this strategy and make predictions underpinned by structural and causal facts. It explores points of comparison and contrasts between this work and the exposition of ex ante facts provided by Mittermaier.

Table of Contents

Section Title Page Action Price
Chad Harris: Ex Ante Facts, Causal Structures, and Prediction 1
1. Introduction 1
2. Mittermaier’s Distinction 2
3. Institutional Facts 3
4. External Validity and Causal Structures 7
5. Conclusion 13
References 14

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