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Journal of Applied Econometrics
Article . 2023 . Peer-reviewed
License: CC BY NC
Data sources: Crossref
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Using arbitrary precision arithmetic to sharpen identification analysis for DSGE models

Authors: Qu, Zhongjun; Tkachenko, Denis;

Using arbitrary precision arithmetic to sharpen identification analysis for DSGE models

Abstract

SummaryWe introduce arbitrary precision arithmetic to resolve practical difficulties arising in the identification analysis of dynamic stochastic general equilibrium (DSGE) models. A three‐step procedure is proposed to address local and global identification and the empirical distance between models. The method is applied to monetary and fiscal policy interaction models, revealing exact observational equivalence in a small‐scale model between an indeterminate passive monetary and fiscal policy regime and determinate regimes, and near observational equivalence in a medium‐scale model. Additionally, the method yields new insights for a model with news shocks, demonstrating that wage markup shocks can be replaced by unanticipated moving average shocks, resulting in near observational equivalence.

Country
United States
Keywords

Global identification, 330, Arbitrary precision arithmetic, Dynamic stochastic general equilibrium models, Local identification

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
hybrid