Bayesian Factor Model Shrinkage for Linear IV Regression With Many Instruments
多工具变量线性 IV 回归的贝叶斯因子模型收缩
A Bayesian approach for the many instruments problem in linear instrumental variable models is presented. The new approach has two components. First, a slice sampler is developed, which leverages a decomposition of the likelihood function that is a Bayesian analogue to two-stage least squares. The new sampler permits nonconjugate shrinkage priors to be implemented easily and efficiently. The new computational approach permits a Bayesian analysis of problems that were…