Hostname: page-component-76fb5796d-vfjqv Total loading time: 0 Render date: 2024-04-30T06:56:56.013Z Has data issue: false hasContentIssue false
  • English
  • Français

How to Design Galilean Fall Experiments in Economics

Published online by Cambridge University Press:  01 January 2022

Marcel Boumans
Get access Rights & Permissions [Opens in a new window]

Abstract

In the social sciences we hardly can create laboratory conditions, we only can try to find out which kinds of experiments Nature has carried out. Knowledge about Nature's designs can be used to infer conditions for reliable predictions. This problem was explicitly dealt with in Haavelmo's (1944) discussion of autonomous relationships, Friedman's (1953) as-if methodology, and Simon's (1961) discussions of nearly-decomposable systems. All three accounts take Marshallian partitioning as starting point, however not with a sharp ceteris paribus razor but with the blunt knife of negligibility assumptions. As will be shown, in each account reflection on which influences are negligible, for what phenomena and for how long, played a central role.

Type
Research Article
Information
Philosophy of Science , Volume 70 , Issue 2 , April 2003 , pp. 308 - 329
Copyright
Copyright © The Philosophy of Science Association

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

‡

Part of this research for this paper was conducted while the author was a fellow of the Netherlands Institute for Advanced Study, during 2001–2002. Their support is gratefully acknowledged. This paper was presented at the workshop “Measurement in Economics and Natural Sciences,” 13–16 May 2002, at Amsterdam. I thank my two discussants James Woodward and Hasok Chang and the other participants for their helpful comments. I am grateful to the two anonymous referees who provided constructive suggestions.

References

Aldrich, John (1989), “Autonomy”, in Marchi, Neil de and Gilbert, Christopher (eds.), History and Methodology of Econometrics. Oxford: Clarendon Press, 15–34.Google Scholar
Ando, Albert (1963), “Introduction”, in Ando, Albert, Fisher, Franklin M., and Simon, Herbert A. (eds.), Essays on the Structure of Social Science Models. Cambridge: MIT Press, 1–4.Google Scholar
Cartwright, Nancy (1983), How the Laws of Physics Lie. Oxford: Clarendon Press.CrossRefGoogle Scholar
Cartwright, Nancy (1999). The Dappled World: A Study of the Boundaries of Science, Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Christ, Carl F. (1951), “A Test of an Econometric Model for the United States, 1921–1947”, in Conference on Business Cycles. New York: National Bureau of Economic Research, 35–107.Google Scholar
Christ, Carl F. (1952), “History of the Cowles Commission 1932–1952”, in Economic Theory and Measurement. Chicago: Cowles Commission for Research in Economics, 3–65.Google Scholar
Christ, Carl F. (1994), “The Cowles Commission’s Contributions to Econometrics at Chicago, 1939–1955”, The Cowles Commission’s Contributions to Econometrics at Chicago, 1939–1955 32(1): 30–59.Google Scholar
Dawson, Richard E. (1962), “Simulation in the Social Sciences”, in Guetzkow, Harold (ed.), Simulation in Social Science: Readings. Englewood Cliffs: Prentice Hall, 1–15.Google Scholar
De Marchi, Neil, and Gilbert, Christopher (1989), “Introduction”, in Marchi, Neil de and Gilbert, Christopher (eds.), History and Methodology of Econometrics. Oxford: Clarendon Press, 1–11.Google Scholar
Friedman, Milton (1949), “The Marshallian Demand Curve”, The Marshallian Demand Curve 57(6): 463–495.Google Scholar
Friedman, Milton (1951), “Comment”, in Conference on Business Cycles. New York: National Bureau of Economic Research, 107–114.Google Scholar
Friedman, Milton (1953), “The Methodology of Positive Economics”, in Essays in Positive Economics. Chicago: University of Chicago Press.Google Scholar
Haavelmo, Trygve (1944), “The Probability Approach in Econometrics”, supplement to Econometrica 12.CrossRefGoogle Scholar
Hirsch, Abraham, and Marchi, Neil de (1990), Milton Friedman, Economics in Theory and Practice. Ann Arbor: The University of Michigan Press.CrossRefGoogle Scholar
Hoover, Kevin D. (1988), The New Classical Macroeconomics: A Sceptical Inquiry. Oxford: Basil Blackwell.Google Scholar
Hoover, Kevin D. (1997), Econometrics and Reality. Working paper, Department of Economics, Davis: University of California.Google Scholar
Jeffreys, Harold (1948), Theory of Probability, 2d ed. Oxford: Clarendon Press.Google Scholar
Klein, Lawrence R. (1950), Economic Fluctuations in the United States, 1921–1941. Cowles Commission Monographs No. 11. New York: WileyGoogle Scholar
Mäki, Uskali (1998), “Realisticness”, in Davis, John B., Hands, D. Wade, and Mäki, Uskali (eds.), The Handbook of Economic Methodology. Cheltenham: Edward Elgar, 409–413.Google Scholar
Marshall, Alfred ([1898] 1925), “Mechanical and Biological Analogies in Economics”, in Pigou, A.C. (ed.), Memorials of Alfred Marshall. London: Macmillan, 312–318.Google Scholar
Marshall, Alfred (1920), Principles of Economics, eighth edition. London: Macmillan.Google Scholar
Marshall, Andrew W. (1950a), “A Test of Klein’s Model III for Changes of Structure”, A Test of Klein’s Model III for Changes of Structure 21: 141.Google Scholar
Marshall, Andrew W. (1950b), “A Test of Klein’s Model III for Changes of Structure”, A Test of Klein’s Model III for Changes of Structure 18: 291.Google Scholar
Morgan, Mary S. (1990), The History of Econometric Ideas. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Musgrave, Alan (1981), “‘Unreal Assumptions’ in Economic Theory: The F-Twist Untwisted”, ‘Unreal Assumptions’ in Economic Theory: The F-Twist Untwisted 34:377–387.Google Scholar
Oxford English Dictionary (1933). Oxford: Clarendon Press.Google Scholar
Simon, Herbert A. (1951), “Theory of Automata”, Theory of Automata 19: 72.Google Scholar
Simon, Herbert A. (1962), “The Architecture of Complexity”, The Architecture of Complexity 106(6): 467–482.Google Scholar
Simon, Herbert A. (1968), “On Judging the Plausibility of Theories”, in Rootselaar, B. van and Staal, J.F. (eds.), Logic, Methodology and Philosophy of Science III. Amsterdam: North-Holland, 439–459.CrossRefGoogle Scholar
Simon, Herbert A. (1969), The Sciences of the Artificial. Cambridge: MIT Press.Google Scholar
Simon, Herbert A. (1977), Models of Discovery. Dordrecht: Reidel.CrossRefGoogle Scholar
Simon, Herbert A., and Ando, Albert (1961), “Aggregation of Variables in Dynamic Systems”, Aggregation of Variables in Dynamic Systems 29:111–138.Google Scholar
Von Neumann, John ([1951] 1963), “The General and Logical Theory of Automata”, in Taub, A.H. (ed.), John von Neumann. Collected Works, Vol. 5. Oxford: Pergamon Press, 288–318.Google Scholar
Woodward, James (2000), “Explanation and Invariance in the Special Sciences”, Explanation and Invariance in the Special Sciences 51:197–254.Google Scholar
Zellner, Arnold (1988), “Causality and Causal Laws in Economics”, Causality and Causal Laws in Economics 39:7–21.Google Scholar