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Abstract
What features of the data are the key sources of information about the parameters in structural macroeconomic models? As such models grow in size and complexity, the answer to this question has become increasingly difficult. This article shows how to identify the main sources of parameter information across different parts of the moment structure of macroeconomic models. In particular, we propose a measure of the relative contribution of information by a given subset of moments with respect to any parameter of interest. The measure is trivial to compute even for large-scale models with many free parameters and observed variables. We illustrate our method with an application to a news-driven business cycle model developed by Schmitt-Grohé and Uribe.
Citation
@article{Iskrev2022,
author = {Nikolay Iskrev},
title = {On the Sources of Information in the Moment Structure of Dynamic Macroeconomic Models},
journal = {Journal of Business \& Economic Statistics},
volume = {40},
number = {1},
pages = {272--284},
year = {2022},
publisher = {Taylor \& Francis},
doi = {10.1080/07350015.2020.1803079},
URL = {https://doi.org/10.1080/07350015.2020.1803079},
eprint = {https://doi.org/10.1080/07350015.2020.1803079}
}