Abstract: We propose a constructive, multivariate framework for assessing agreement
between (generally misspecified) dynamic equilibrium models and data,
which enables a complete second-order comparison of the dynamic properties
of models and data. We use bootstrap algorithms to evaluate the significance
of deviations between models and data, and we use goodness-of-fit criteria
to produce estimators that optimize economically relevant loss functions.
We provide a detailed illustrative application to modeling the U.S. cattle
cycle.
Keywords: Evaluation, multivariate, frequency domain, bootstrap
Full paper (3038 KB PDF)
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Last update: July 16, 1997
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