Home About Latest Browse RSS Advanced Search

Federal Reserve Bank of Dallas
Globalization Institute Working Papers
Bayesian estimation of NOEM models: identification and inference in small samples
Enrique Martínez-García
Diego Vilán
Mark A. Wynne

This paper studies the (potential) weak identification of these relationships in the context of a fully specified structural model using Bayesian estimation techniques. We trace the problems to sample size, rather than misspecification bias. We conclude that standard macroeconomic time series with a coverage of less than forty years are subject to potentially serious identification issues, and also to model selection errors. We recommend estimation with simulated data prior to bringing the model to the actual data as a way of detecting parameters that are susceptible to weak identification in short samples.

Download Full text
Cite this item
Enrique Martínez-García & Diego Vilán & Mark A. Wynne, Bayesian estimation of NOEM models: identification and inference in small samples, Federal Reserve Bank of Dallas, Globalization Institute Working Papers 105, 2012, revised 01 Mar 2012.
More from this series
Note: Published as: Martínez-García, Enrique, Diego Vilán and Mark A. Wynne (2012), "Bayesian Estimation of NOEM Models: Identification and Inference in Small Samples," in DSGE Models in Macroeconomics: Estimation, Evaluation, and New Development, ed. Nathan Balke, Fabio Canova, Fabio Milani and Mark A. Wynne (Bingley, UK: Emerald Group Publishing Limited), 137-199.
JEL Classification:
Subject headings:
For corrections, contact Amy Chapman ()
Fed-in-Print is the central catalog of publications within the Federal Reserve System. It is managed and hosted by the Economic Research Division, Federal Reserve Bank of St. Louis.

Privacy Legal