DP15684 Estimating macro models and the potentially misleading nature of Bayesian estimation

Author(s): David Meenagh, Patrick Minford, Michael R. Wickens
Publication Date: January 2021
Keyword(s): Bayesian, Estimation Bias, indirect inference, maximum likelihood
JEL(s): C11, E12
Programme Areas: Monetary Economics and Fluctuations
Link to this Page: cepr.org/active/publications/discussion_papers/dp.php?dpno=15684

We ask whether Bayesian estimation creates a potential estimation bias as compared with standard estimation techniques based on the data, such as maximum likelihood or indirect estimation. We investigate this with a Monte Carlo experiment in which the true version of a New Keynesian model may either have high wage/price rigidity or be close to pure flexibility; we treat each in turn as the true model and create Bayesian estimates of it under priors from the true model and its false alternative. The Bayesian estimation of macro models may thus give very misleading results by placing too much weight on prior information compared to observed data; a better method may be Indirect estimation where the bias is found to be low.