causality in economics and econometrics
From The New Palgrave Dictionary of Economics, Second Edition, 2008
Edited by
Steven
N.
Durlauf
and
Lawrence
E.
Blume
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Abstract
Economics was conceived as early as the classical period as a science of causes. The philosopher–economists David Hume and J. S. Mill developed the conceptions of causality that remain implicit in economics today. This article traces the history of causality in economics and econometrics, showing that different approaches can be classified on two dimensions: process versus structural approaches, and a priori versus inferential approaches. The variety of modern approaches to causal inference is explained and related to this classification. Causality is also examined in relationship to exogeneity and identification.
Keywords
Aristotle; causal inference; causality in economics and econometrics; correlation; Cowles Commission; econometrics; Edgeworth, F. Y.; endogeneity and exogeneity; Granger–Sims causality; graph theory; Hume, D.; identification; index numbers; Induction; instrumental variables; Jevons, W. S.; microfoundations; Mill, J. S.; Mises, L. von; natural experiments; observational equivalence; process analysis; Quetelet, A.; rational expectations; regression; Robbins, L. C.; Simon, H.; Smith, A.; statistical inference; structural vector autoregressions; Tinbergen, J.; vector autoregressions; Wold, H. O. A.
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How to cite this article
Hoover, Kevin D. "causality in economics and econometrics." The New Palgrave Dictionary of Economics. Second Edition. Eds. Steven N. Durlauf and Lawrence E. Blume. Palgrave Macmillan, 2008. The New Palgrave Dictionary of Economics Online. Palgrave Macmillan. 23 May 2013 <http://www.dictionaryofeconomics.com/article?id=pde2008_C000569> doi:10.1057/9780230226203.0209

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