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https://doi.org/10.20955/r.91....
Article . 2009 . Peer-reviewed
Data sources: Crossref
SSRN Electronic Journal
Article . 2008 . Peer-reviewed
Data sources: Crossref
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Challenges in Macro-Finance Modeling

Authors: Don H. Kim;

Challenges in Macro-Finance Modeling

Abstract

This paper discusses various challenges in the specification and implementation of "macro-finance" models in which macroeconomic variables and term structure variables are modeled together in a no-arbitrage framework. I classify macro-finance models into pure latent-factor models ("internal basis models") and models which have observed macroeconomic variables as state variables ("external basis models"), and examine the underlying assumptions behind these models. Particular attention is paid to the issue of unspanned short-run fluctuations in macro variables and their potentially adverse effect on the specification of external basis models. I also discuss the challenge of addressing features like structural breaks and time-varying inflation uncertainty. Empirical difficulties in the estimation and evaluation of macro-finance models are also discussed in detail.

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Keywords

Term structure of interest rates, inflation expectations, macro-finance modeling, no-arbitrage models, Econometric models ; Macroeconomics

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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!
14
Average
Top 10%
Top 10%
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