符号约束与外部仪器相结合的SVAR模型识别

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2022-07-29 DOI:10.1080/07350015.2022.2104857
R. Braun, R. Brüggemann
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引用次数: 16

摘要

摘要我们讨论了将符号限制与外部工具(代理变量)中的信息相结合来识别结构向量自回归(SVAR)模型。在一种情况下,我们假设有效的外部仪器可用。然后,可以使用符号限制来识别进一步的正交冲击,或者作为一条附加信息来更准确地确定外部仪器识别的冲击。在第二种情况下,我们假设代理变量只是“看似外生的”,并提出了各种类型的不平等限制,以约束结构性冲击和外部变量之间的关系。这可以与传统的符号限制相结合,以进一步缩小可接受模型的范围。在代理增强SVAR中,我们进行贝叶斯推理,并讨论贝叶斯因子的计算。它们可以用来测试体征或IV限制是否为过度识别。我们说明了我们的方法在估计石油供应和货币政策冲击的影响方面的有用性。
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Identification of SVAR Models by Combining Sign Restrictions With External Instruments
ABSTRACT We discuss combining sign restrictions with information in external instruments (proxy variables) to identify structural vector autoregressive (SVAR) models. In one setting, we assume the availability of valid external instruments. Sign restrictions may then be used to identify further orthogonal shocks, or as an additional piece of information to pin down the shocks identified by the external instruments more precisely. In a second setting, we assume that proxy variables are only “plausibly exogenous” and suggest various types of inequality restrictions to bound the relation between structural shocks and the external variable. This can be combined with conventional sign restrictions to further narrow down the set of admissible models. Within a proxy-augmented SVAR, we conduct Bayesian inference and discuss computation of Bayes factors. They can be useful to test either the sign- or IV restrictions as overidentifying. We illustrate the usefulness of our methodology in estimating the effects of oil supply and monetary policy shocks.
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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