Bayesian Estimation of NOEM Models: Identification and Inference in Small Samples

Enrique Martínez-García, Diego Vilán and Mark Wynne
Authors registered in the RePEc Author Service: Enrique Martínez García ()

A chapter in DSGE Models in Macroeconomics: Estimation, Evaluation, and New Developments, 2012, pp 137-199 from Emerald Group Publishing Limited

Abstract: Open-Economy models are central to the discussion of the trade-offs monetary policy faces in an increasingly more globalized world (e.g., Marínez-García & Wynne, 2010), but bringing them to the data is not without its challenges. Controlling for misspecification bias, we trace the problem of uncertainty surrounding structural parameter estimation in the context of a fully specified New Open Economy Macro (NOEM) model partly to sample size. We suggest that standard macroeconomic time series with a coverage of less than forty years may not be informative enough for some parameters of interest to be recovered with precision. We also illustrate how uncertainty also arises from weak structural identification, irrespective of the sample size. This remains a concern for empirical research and we recommend estimation with simulated observations before using actual data as a way of detecting structural parameters that are prone to weak identification. We also recommend careful evaluation and documentation of the implementation strategy (specially in the selection of observables) as it can have significant effects on the strength of identification of key model parameters.

Keywords: Global slack hypothesis; new open economy macroeconomics; Phillips curve; Bayesian estimation (search for similar items in EconPapers)
Date: 2012
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Working Paper: Bayesian estimation of NOEM models: identification and inference in small samples (2012)
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Persistent link: https://EconPapers.repec.org/RePEc:eme:aecozz:s0731-9053(2012)0000028007

DOI: 10.1108/S0731-9053(2012)0000028007

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