A new approach to integrating expectations into VAR models *

• 成果类型: Article
• 署名作者: Doh, Taeyoung; Smith, A. Lee
• 署名单位: Federal Reserve System - USA; Federal Reserve Bank - Kansas City
• 刊物名称: JOURNAL OF MONETARY ECONOMICS
• ISSN/ISSBN: 0304-3932
• DOI: 10.1016/j.jmoneco.2022.08.001
• 发表日期: 2022
• 页码: 24-43
• 关键词: Bayesian vector autoregression (VAR); sign restrictions; Information rigidities; monetary policy; Forward guidance; Inflation expectations

摘要

Expectations play a central role in macroeconomics. Expectations are empirically measured from surveys or financial markets and are frequently analyzed in Vector autoregressive (VAR) models alongside realized data of the same variable. However, this leads to two dif-ferent expectations for the same variable: the VAR-based forecast and the external forecast. This paper proposes a Bayesian prior over the VAR parameters which allows for varying degrees of consistency between these two forecasts. As we demonstrate in two applica-tions, our approach can sharpen structural VAR identification of forward guidance shocks and enhances VAR forecasts of inflation tail risks.(c) 2022 Elsevier B.V. All rights reserved.