We investigate the Bayesian approach to model comparison within a two-country framework with nominal rigidities using the workhorse New Keynesian open-economy model of Martínez-García and Wynne (2010). We discuss the trade-offs that monetary policy – characterized by a Taylor-type rule – faces in an interconnected world, with perfectly flexible exchange rates. We then use posterior model probabilities to evaluate the weight of evidence in support of such a model when estimated against more parsimonious specifications that either abstract from monetary frictions or assume autarky by means of controlled experiments that employ simulated data. We argue that Bayesian model comparison with posterior odds is sensitive to sample size and the choice of observable variables for estimation. We show that posterior model probabilities strongly penalize overfitting, which can lead us to favor a less parameterized model against the true data-generating process when the two become arbitrarily close to each other. We also illustrate that the spillovers from monetary policy across countries have an added confounding effect.
We would like to thank Nathan Balke, María Teresa Martínez-García, and Valentín Martínez Mira for helpful suggestions. Diego Vilán was a co-author in a related project and contributed to the early stages of the development of this paper. We gratefully acknowledge the outstanding research assistance provided by Valerie Grossman, the help of Bradley Graves and Kuhu Parasrampuria, and the Federal Reserve Bank of Dallas' support. All remaining errors are ours alone. The views expressed in this paper are those of the authors and do not necessarily reflect the views of the Federal Reserve Bank of Dallas, or the Federal Reserve System.
Martínez-García, E. and Wynne, M.A. (2014), "Assessing Bayesian Model Comparison in Small Samples", Bayesian Model Comparison (Advances in Econometrics, Vol. 34), Emerald Group Publishing Limited, Bingley, pp. 71-115. https://doi.org/10.1108/S0731-905320140000034006
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