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|
|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.