局部投影、自相关和效率

Amaze Lusompa
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引用次数: 13

摘要

众所周知,局部投影残差是自相关的。传统观点认为LP必须用Newey和West(1987)(或某种类型的异方差和自相关一致性(HAC))标准误差的OLS来估计,而GLS是不可能的,因为自相关过程是未知的。我证明了LP的自相关过程是已知的,并且使用GLS可以校正自相关。使用GLS估计LP有三个主要含义:1)LP GLS比使用new - west标准误差的OLS估计更有效,偏差更小。2)由于自相关过程可以显式建模,因此有可能给出LP的完全贝叶斯处理。也就是说,LP可以使用频率/经典或全贝叶斯方法来估计。3)由于自相关过程可以显式建模,现在可以估计时变参数LP。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Local Projections, Autocorrelation, and Efficiency
It is well known that Local Projections (LP) residuals are autocorrelated. Conventional wisdom says that LP have to be estimated by OLS with Newey and West (1987) (or some type of Heteroskedastic and Autocorrelation Consistent (HAC)) standard errors and that GLS is not possible because the autocorrelation process is unknown. I show that the autocorrelation process of LP is known and that autocorrelation can be corrected for using GLS. Estimating LP with GLS has three major implications: 1) LP GLS can be substantially more efficient and less biased than estimation by OLS with Newey-West standard errors. 2) Since the autocorrelation process can be modeled explicitly, it is possible to give a fully Bayesian treatment of LP. That is, LP can be estimated using frequentist/classical or fully Bayesian methods. 3) Since the autocorrelation process can be modeled explicitly, it is now possible to estimate time-varying parameter LP.
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