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Identification of Economic Shocks by Inequality Constraints in Bayesian Structural Vector Autoregression

机译:贝叶斯结构载体自我评级不等式限制识别经济冲击

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摘要

Theories often make predictions about the signs of the effects of economic shocks on observable variables, thus implying inequality constraints on the parameters of a structural vector autoregression (SVAR). We introduce a new Bayesian procedure to evaluate the probabilities of such constraints, and, hence, to validate the theoretically implied economic shocks. We first estimate a SVAR, where the shocks are identified by statistical properties of the data, and subsequently label these statistically identified shocks by the Bayes factors calculated from their probabilities of satisfying given inequality constraints. In contrast to the related sign restriction approach that also makes use of theoretically implied inequality constraints, no restrictions are imposed. Hence, it is possible that only a subset or none of the theoretically implied shocks can be labelled. In the latter case, we conclude that the data do not lend support to the theory implying the signs of the effects in question. We illustrate the method by empirical applications to the crude oil market, and U.S. monetary policy.
机译:理论经常预测对可观察变量对经济冲击影响的迹象,从而暗示了对结构载体自动增加(SVAR)参数的不平等约束。我们介绍了一种新的贝叶斯程序,以评估这种限制的概率,从而验证理论上隐含的经济冲击。我们首先估计SVAR,其中通过数据的统计特性来识别冲击,随后通过从其履约的概率计算的贝叶斯因子来标记这些统计学上识别的冲击。与相关的符号限制方法相比,也利用理论上隐含的不等式限制,没有施加限制。因此,可以仅标记只有子集或理论上隐含的冲击。在后一种情况下,我们得出结论,数据不支持对该理论的支持,这意味着有问题的效果的迹象。我们通过对原油市场和美国货币政策的经验应用来说明该方法。

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