Bayesian econometrics
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Bayesian econometrics is a branch of econometrics which applies Bayesian principles to economic modelling. Bayesianism is based on a degree-of-belief interpretation of probability, as opposed to a relative-frequency interpretation.
The Bayesian principle relies on Bayes' theorem which states that the probability of B conditional on A is the ratio of joint probability of A and B divided by probability of B. Bayesian econometricians assume that coefficients in the model have prior distributions.
This approach was first propagated by Arnold Zellner.[1]
References
- Tony Lancaster (2004) An Introduction to Modern Bayesian Econometrics, Blackwell Publishing. ISBN 1-4051-1720-6
- Gary Koop, Dale J. Poirier, Justin L. Tobias (2007) Bayesian Econometric Methods, Cambridge University Press. ISBN 0-521-85571-3
- Zellner, A. (1996) An Introduction to Bayesian Inference in Econometrics, Wiley. ISBN 0-471-16937-4 (reprint of 1971 edition)
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- ^ Greenberg, Edward. Introduction to Bayesian econometrics. Cambridge University Press, 2012.