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Cited by 1,197

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Are Forecasting Models Usable for Policy Analysis?

Sims, Christopher·1986·Quarterly Review

Abstract

In this article, Christopher A. Sims argues the answer to his title is yes. Sims explains that any decisionmaking model must incorporate some identifying assumptions to enable it to forecast the effects of alternative decisions. He argues that although all identifying assumptions in econometric policymaking models are of uncertain validity, those incorporated in vector autoregression (VAR) forecasting models have the advantage of allowing their uncertainty to be measured. Sims concludes by demonstrating a method for identifying a small macroeconomic VAR model so that it can be used to analyze monetary policy

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Metadata

Authors
Sims, C.
Venue
Quarterly Review
Published
1986-12
Volume
10
Issue
1
ISSN
0271-5287 (ISSN-L)
OpenAlex
W2996121507
Cited by
1,197
References
0
FWCI
17.54
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Are Forecasting Models Usable for Policy Analysis? https://app.cochat.ai/papers/10.21034/qr.1011
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Sims, C. (1986). Are Forecasting Models Usable for Policy Analysis? Quarterly Review. https://doi.org/10.21034/qr.1011

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.