The DOI matches its Crossref record; 136 of the 136 references it cites were found in a registry or an index.
1. The Scientific Model of Causality
Abstract
Causality is a very intuitive notion that is difficult to make precise without lapsing into tautology. Two ingredients are central to any definition: (1) a set of possible outcomes (counterfactuals) generated by a function of a set of ‘‘factors’ ’ or ‘‘determinants’ ’ and (2) a manipulation where one (or more) of the ‘‘factors’ ’ or ‘‘determinants’’ is changed. An effect is realized as a change in the argument of a stable function that produces the same change in the outcome for a class of interventions that change the ‘‘factors’ ’ by the same amount. The outcomes are compared at different levels of the factors or generating variables. Holding all factors save one at a constant level, the change in the outcome associated with manipulation of the varied factor is called a causal effect of the manipulated factor. This definition, or some version of it, goes back to Mill (1848) and Marshall (1890). Haavelmo’s (1943) made it more precise within the context of linear equations models. The phrase ‘ceteris paribus’ (everything else held constant) is a mainstay of economic analysis
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Cites
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Cited by
Using matching, instrumental variables and control functions to estimate economic choice models
Heckman, J., & Navarro-Lozano, S. (2004) · Review of Economics and Statistics · doi:10.1162/003465304323023660 · Cited by 768
Self-citationAn Introduction to Causal Inference
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Metadata
- Authors
- Heckman, J. J.
- Venue
- Sociological Methodology
- Publisher
- SAGE Publications
- Published
- 2005-08
- Volume
- 35
- Issue
- 1
- Pages
- 1-97
- ISSN
- 0081-1750 (ISSN-L)
- 1467-9531
- OpenAlex
- W2087875390
- Cited by
- 401
- References
- 136
- FWCI
- 15.29
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- journals.sagepub.com/page/policies/text-and-data-mining-license (tdm)
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