G2TT
来源类型Discussion paper
规范类型论文
来源IDDP13511
DP13511 Dealing with misspecification in structural macroeconometric models
Fabio Canova; Christian Matthes
发表日期2019-02-05
出版年2019
语种英语
摘要We consider a set of potentially misspecified structural models, geometrically combine their likelihood functions, and estimate the parameters using composite methods. Composite estimators may be preferable to likelihood-based estimators in the mean squared error. Composite models may be superior to individual models in the Kullback-Leibler sense. We describe Bayesian quasi-posterior computations and compare the approach to Bayesian model averaging, finite mixture methods, and robustness procedures. We robustify inference using the composite posterior distribution of the parameters and the pool of models. We provide estimates of the marginal propensity to consume and evaluate the role of technology shocks for output fluctuations.
主题Monetary Economics and Fluctuations
关键词Model misspecification Composite likelihood Bayesian model averaging Finite mixture
URLhttps://cepr.org/publications/dp13511
来源智库Centre for Economic Policy Research (United Kingdom)
资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/542328
推荐引用方式
GB/T 7714
Fabio Canova,Christian Matthes. DP13511 Dealing with misspecification in structural macroeconometric models. 2019.
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