Macroeconomics and Methodology
Probabilistic reasoning is essential to discourse in economics. This is true in any discipline in which, as in economics, data collection is constrained and beliefs about the phenomena being studied are crucial to decisions that cannot be delayed. Some economists have recently turned away from form probabilistic inference, in part because of legitimate discontent with the prescriptions of specialized econometricians. However, this turning away has gone in mutually inconsistent directions and is in the long run unsustainable. It should be more widely recognized that careful applied work in macroeconomics, using steadily advancing probabilistic modeling techniques, has been steadily increasing.
Volume (Year): 10 (1996)
Issue (Month): 1 (Winter)
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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Sims, Christopher A., 1988.
"Bayesian skepticism on unit root econometrics,"
Journal of Economic Dynamics and Control,
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American Economic Review,
American Economic Association, vol. 82(4), pages 901-21, September.
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- Martin Eichenbaum & Charles L. Evans, 1993.
"Some Empirical Evidence on the Effects of Monetary Policy Shocks on Exchange Rates,"
NBER Working Papers
4271, National Bureau of Economic Research, Inc.
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"Measures of fit for calibrated models,"
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91-9, Federal Reserve Bank of Chicago.
- Christopher A. Sims, 1989. "Models and their uses," Discussion Paper / Institute for Empirical Macroeconomics 11, Federal Reserve Bank of Minneapolis.
- McCloskey, Donald N, 1983. "The Rhetoric of Economics," Journal of Economic Literature, American Economic Association, vol. 21(2), pages 481-517, June.
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