Dealing with misspecification in structural macroeconometric models
نویسندگان
چکیده
We consider a set of potentially misspecified structural models, geometrically combine their likelihood functions, and estimate the parameters using composite methods. In Monte Carlo study, estimators dominate likelihood?based in mean squared error models are superior to individual Kullback–Leibler sense. describe Bayesian quasi?posterior computations compare our approach model averaging, finite mixture, robust control procedures. robustify inference posterior distribution pool models. provide estimates marginal propensity consume evaluate role technology shocks for output fluctuations.
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ژورنال
عنوان ژورنال: Quantitative Economics
سال: 2021
ISSN: ['1759-7331', '1759-7323']
DOI: https://doi.org/10.3982/qe1413