Are Forecasting Models Usable for Policy Analysis?
Author(s) -
Christopher Sims
Publication year - 1986
Publication title -
quarterly review
Language(s) - English
Resource type - Journals
eISSN - 2163-4378
pISSN - 0271-5287
DOI - 10.21034/qr.1011
Subject(s) - usable , computer science , econometrics , operations research , economics , engineering , world wide web
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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