Bayesian econometrics

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

1. Greenberg, Edward (2012). Introduction to Bayesian Econometrics (Second ed.). Cambridge University Press. ISBN 978-1-107-01531-9.

• Koop, Gary; Poirier, Dale J.; Tobias, Justin L. (2007). Bayesian Econometric Methods. Cambridge University Press. ISBN 0-521-85571-3.
• Lancaster, Tony (2004). An Introduction to Modern Bayesian Econometrics. Blackwell. ISBN 1-4051-1720-6.
• Zellner, A. (1996). An Introduction to Bayesian Inference in Econometrics (Reprint of 1971 ed.). Wiley. ISBN 0-471-16937-4.