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Causal Instrumental Variables and Interventions

Published online by Cambridge University Press:  01 January 2022

Abstract

The aim of this paper is to introduce the instrumental variables technique to the discussion about causal inference in econometrics. I show that it may lead to causally incorrect conclusions unless some fairly strong causal background assumptions are made, assumptions which are usually left implicit by econometricians. These assumptions are very similar to, albeit not identical with, James Woodward's definition of an ‘intervention’. I discuss similarities and differences of the two points of view and argue that—understood as a practical method of causal inference—the set presented here is superior.

Type
Philosophy of Social Science
Copyright
Copyright © The Philosophy of Science Association

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Footnotes

Work on this paper was conducted under the CPNSS research project Causality: Metaphysics and Methods. I am very grateful to the AHRB for funding. Many thanks to Nancy Cartwright for valuable comments on an earlier draft.

References

Angrist, Joshua (1990), “Lifetime Earnings and the Vietnam Era Draft Lottery: Evidence from Social Security Administrative Records”, Lifetime Earnings and the Vietnam Era Draft Lottery: Evidence from Social Security Administrative Records 80:313336.Google Scholar
Bartels, Larry (1991), “Instrumental and ‘Quasi-Instrumental’ Variables”, Instrumental and ‘Quasi-Instrumental’ Variables 35:777800.Google Scholar
Card, David, and Krueger, Alan (1995), Myth and Measurement: The New Economics of the Minimum Wage. Princeton, NJ: Princeton University Press.Google Scholar
Cartwright, Nancy (forthcoming), “Causal Inference à la Herbert Simon: A Primer”, in Cartwright, Nancy, Hunting Causes—and Using Them. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Greene, William (2000), Econometric Analysis. Upper Saddle River, NJ: Prentice-Hall.Google Scholar
Hammond, J. Daniel (1996), Theory and Measurement: Causality Issues in Milton Friedman’s Economics. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Hausman, Daniel, and Woodward, James (2004), “Modularity and the Causal Markov Condition: A Restatement”, Modularity and the Causal Markov Condition: A Restatement 55:147162.Google Scholar
Hoover, Kevin (2003), “Nonstationary Time Series, Cointegration, and the Principle of the Common Cause”, Nonstationary Time Series, Cointegration, and the Principle of the Common Cause 54:527551.Google Scholar
McDermott, Michael (1995), “Redundant Causation”, Redundant Causation 46:523544.Google Scholar
Mitchell, Wesley (1927), Business Cycles: The Problem and Its Setting. New York: National Bureau of Economic Research.Google Scholar
Pearl, Judea (1993), “Mediating Instrumental Variables”, Mediating Instrumental Variables 8:266273.Google Scholar
Pearl, Judea (1997), “The New Challenge: From a Century of Statistics to an Age of Causation”, manuscript, University of California, Los Angeles.Google Scholar
Pearl, Judea (2000), Causality: Models, Reasoning, and Inference. Cambridge: Cambridge University Press.Google Scholar
Pearson, Karl (1911), The Grammar of Science. London: Walter Scott.Google Scholar
Reiss, Julian (forthcoming), Error in Economics: Toward a More Evidence-Based Methodology. London: Routledge.CrossRefGoogle Scholar
Sober, Elliott (2001), “Venetian Sea Levels, British Bread Prices, and the Principle of the Common Cause”, Venetian Sea Levels, British Bread Prices, and the Principle of the Common Cause 52:331346.Google Scholar
Woodward, James (2003), Making Things Happen. Oxford: Oxford University Press.Google Scholar