The New Palgrave Dictionary of Economics

2018 Edition
| Editors: Macmillan Publishers Ltd

Theory Appraisal

  • Ellery Eells
  • Daniel M. Hausman
Reference work entry


Economists and other scientists appraise theories in terms of criteria such as evidential support, predictive accuracy, usefulness, and reliability in research and practice. This entry addresses three general problems concerning theory appraisal. 1. What is it for evidence to be confirmationally relevant to a theory? 2. How can evidential support be measured? 3. On what other criteria should theory appraisal in economics depend? The third question raises special problems, since economic models so often incorporate statements that appear to be false. But answers to general questions concerning confirmation matter to the conduct of economics, too.


Bayes, T. Bayesian confirmation theory Ceteris paribus Confirmation Duhem–Quine problem Experimental economics Friedman, M. Habit Hempel, C. Hume, D. Hypothetico-deductive method Induction Likelihood McCloskey, D. Mill, J. S. Popper, K. Prior probability Probability Rhetoric of economics Subjective probability Testing Theory appraisal 

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  1. Bayes, T. 1764. An essay towards solving a problem in the doctrine of chance. Philosophical Transactions of the Royal Society of London 53: 370–418.CrossRefGoogle Scholar
  2. Blaug, M. 1976. Kuhn versus Lakatos or Paradigms versus research programmes in the history of economics. In Method and appraisal in economics, ed. S. Latsis. Cambridge: Cambridge University Press.Google Scholar
  3. Card, D., and A. Krueger. 1995. Myth and measurement: The new economics of the minimum wage. Princeton: Princeton University Press.Google Scholar
  4. de Finetti, B. 1937. La prévision: ses lois logiques, ses sources subjectives. Annales de lInstitute Henri Poincaré 7, 1–68. English translation in Studies in Subjective Probability, ed. H. Kyburg and H. Smokler. New York: John Wiley, 1964.Google Scholar
  5. Duhem, P. 1954. The aim and structure of physical theory, trans. P. Wiener. Princeton: Princeton University Press, 1954.Google Scholar
  6. Earman, J. 1992. Bayes or bust: A critical examination of bayesian confirmation theory. Cambridge, MA/London: MIT Press.Google Scholar
  7. Edwards, A. 1972. Likelihood. Cambridge: Cambridge University Press.Google Scholar
  8. Eells, E. 1982. Rational decision and causality. Cambridge/New York: Cambridge University Press.CrossRefGoogle Scholar
  9. Fitelson, B. 2001. Studies in Bayesian confirmation theory. Ph.D. dissertation, University of Wisconsin-Madison.Google Scholar
  10. Forster, M., and E. Sober. 2002. Why likelihood? In The nature of scientific evidence, ed. M. Taper and S. Lee. Chicago: University of Chicago Press.Google Scholar
  11. Friedman, M. 1953. The methodology of positive economics. In Essays in positive economics. Chicago: University of Chicago Press.Google Scholar
  12. Glymour, C. 1980. Theory and evidence. Princeton: Princeton University Press.Google Scholar
  13. Hall, R., and C. Hitch. 1939. Price theory and business behaviour. Oxford Economic Papers 2: 12–45.CrossRefGoogle Scholar
  14. Hands, D. 2001. Reflection without rules: Economic methodology and contemporary science theory. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  15. Harsanyi, J. 1977. Rational behavior and bargaining equilibrium in games and social situations. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  16. Hempel, C. 1945. Studies in the logic of confirmation. Mind 54, 1–26, 97–121. Reprinted, with his Postscript, in Aspects of Scientific Explanation and other Essays in the Philosophy of Science. New York: Free Press, 1965.Google Scholar
  17. Hume, D. 1748. An inquiry concerning human understanding, 1955. Indianapolis: Bobbs-Merrill.Google Scholar
  18. Jeffrey, R. 1983. The logic of decision. 2nd ed. Chicago/London: University of Chicago Press.Google Scholar
  19. Joyce, J. 1999. The foundations of causal decision theory. Cambridge/New York: Cambridge University Press.CrossRefGoogle Scholar
  20. Kydland, F., and E. Prescott. 1996. The computational experiment: An econometric tool. Journal of Economic Perspectives 10(1): 69–85.CrossRefGoogle Scholar
  21. Lester, R. 1946. Shortcomings of marginal analysis for wage-employment problems. American Economic Review 36: 62–82.Google Scholar
  22. McCloskey, D. 1985. The rhetoric of economics. Madison: University of Wisconsin Press.Google Scholar
  23. Mill, J.S. 1843. A system of logic, 1949. London: Longman, Green & Co..Google Scholar
  24. Ramsey, F. 1931. Truth and probability. In The foundations of mathematics and other logical essays, ed. R. Braithwaite. London: Routledge and Kegan Paul.Google Scholar
  25. Royall, R. 1997. Statistical evidence: A likelihood paradigm. Boca Raton: Chapman and Hall.Google Scholar
  26. Savage, L. 1972. The foundations of statistics. 2nd ed. New York: Dover Publications, Inc..Google Scholar

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© Macmillan Publishers Ltd. 2018

Authors and Affiliations

  • Ellery Eells
    • 1
  • Daniel M. Hausman
    • 1
  1. 1.