Bayesian Local Projections

IF 7.6 1区 经济学 Q1 ECONOMICS
L. N. Ferreira, Silvia Miranda-Agrippino, Giovanni Ricco
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引用次数: 7

Abstract

We propose a Bayesian approach to Local Projections that optimally addresses the empirical bias-variance trade-off intrinsic in the choice between direct and iterative methods. Bayesian Local Projections (BLP) regularise LP regressions via informative priors, and estimate impulse response functions that capture the properties of the data more accurately than iterative VARs. BLPs preserve the flexibility of LPs while retaining a degree of estimation uncertainty comparable to Bayesian VARs with standard macroeconomic priors. As regularised direct forecasts, BLPs are also a valuable alternative to BVARs for multivariate out-of-sample projections.
贝叶斯局部预测
我们提出了一种局部投影的贝叶斯方法,该方法最优地解决了在直接方法和迭代方法之间进行选择时固有的经验偏差-方差权衡。贝叶斯局部投影(BLP)通过信息先验对LP回归进行正则化,并估计脉冲响应函数,该函数比迭代VAR更准确地捕捉数据的属性。BLP保留了LP的灵活性,同时保留了与具有标准宏观经济先验的贝叶斯VAR相当的估计不确定性。作为正则化的直接预测,对于多变量样本外预测,BLP也是BVAR的一个有价值的替代方案。
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来源期刊
CiteScore
8.50
自引率
0.00%
发文量
175
期刊介绍: The Review of Economics and Statistics is a 100-year-old general journal of applied (especially quantitative) economics. Edited at the Harvard Kennedy School, the Review has published some of the most important articles in empirical economics.
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