Estimating macro models and the potentially misleading nature of Bayesian estimation

David Meenagh, A. Patrick Minford and Michael Wickens

No E2021/22, Cardiff Economics Working Papers from Cardiff University, Cardiff Business School, Economics Section

Abstract: 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.

Keywords: Bayesian; Maximum Likelihood; Indirect Inference; Estimation Bias (search for similar items in EconPapers)
JEL-codes: C11 E12 (search for similar items in EconPapers)
Pages: 10 pages
Date: 2021-09
New Economics Papers: this item is included in nep-dge, nep-ets, nep-isf, nep-mac and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Working Paper: Estimating macro models and the potentially misleading nature of Bayesian estimation (2021)
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