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Bayesian and classical approaches to instrumental variable regression

机译:贝叶斯和经典方法进行工具变量回归

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摘要

We establish relationships between certain Bayesian and classical approaches to instrumental variable regression. We determine the form of priors that lead to posteriors for structural parameters that have similar properties as classical 2SLS and LIML and in doing so provide some new insight, especially in the context of weak instruments, to the small sample behavior of Bayesian and classical procedures. Using a reduced rank restriction on a multivariate linear model, we determine the priors that give rise to posteriors that are identical in functional form to the sampling densities of the classical 2SLS and LIML estimators.
机译:我们在工具变量回归的某些贝叶斯方法和经典方法之间建立关系。我们确定先验形式,这些先验形式导致具有与经典2SLS和LIML相似的属性的结构参数的后验,从而为贝叶斯和经典过程的小样本行为提供一些新的见解,尤其是在弱仪器的情况下。在多元线性模型上使用降低的秩限制,我们确定了导致后验的先验函数,后验函数在功能形式上与经典2SLS和LIML估计量的采样密度相同。

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