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Estimating macro models and the potentially misleading nature of Bayesian estimation

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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.

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  • Meenagh, David & Minford, Patrick & Wickens, Michael, 2021. "Estimating macro models and the potentially misleading nature of Bayesian estimation," Cardiff Economics Working Papers E2021/22, Cardiff University, Cardiff Business School, Economics Section.
    • Handle: RePEc:cdf:wpaper:2021/22
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    1. Frank Smets & Rafael Wouters, 2007. "Shocks and Frictions in US Business Cycles: A Bayesian DSGE Approach," American Economic Review, American Economic Association, vol. 97(3), pages 586-606, June.
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    5. Le, Vo Phuong Mai & Meenagh, David & Minford, Patrick & Wickens, Michael, 2011. "How much nominal rigidity is there in the US economy? Testing a new Keynesian DSGE model using indirect inference," Journal of Economic Dynamics and Control, Elsevier, vol. 35(12), pages 2078-2104.
    6. Patrick Minford & Yongdeng Xu & Peng Zhou, 2015. "How Good are Out of Sample Forecasting Tests on DSGE Models?," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 1(3), pages 333-351, November.
    7. David Meenagh & Patrick Minford & Michael Wickens & Yongdeng Xu, 2019. "Testing DSGE Models by Indirect Inference: a Survey of Recent Findings," Open Economies Review, Springer, vol. 30(3), pages 593-620, July.
    8. Vo Le & David Meenagh & Patrick Minford & Michael Wickens & Yongdeng Xu, 2016. "Testing Macro Models by Indirect Inference: A Survey for Users," Open Economies Review, Springer, vol. 27(1), pages 1-38, February.
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    10. Peng Zhou & Huw Dixon, 2019. "The Determinants of Price Rigidity in the UK: Analysis of the CPI and PPI Microdata and Application to Macrodata Modelling," Manchester School, University of Manchester, vol. 87(5), pages 640-677, September.
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    Cited by:

    1. Yang, Xiaoliang & Barros, Lucy & Matthews, Kent & Meenagh, David, 2024. "The dynamics of redistribution, inequality and growth across China’s regions," Journal of Policy Modeling, Elsevier, vol. 46(3), pages 613-637.

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    More about this item

    Keywords

    Bayesian; Maximum Likelihood; Indirect Inference; Estimation Bias;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • E12 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Keynes; Keynesian; Post-Keynesian; Modern Monetary Theory

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