Regression modelQuasi-experimental / causal inference
Bayesian Instrumental Variables (Bayesian IV)
Bayesian Instrumental Variables combines the instrumental variable strategy for addressing endogeneity with Bayesian posterior inference. Instead of relying on asymptotic sampling distributions, it places prior distributions over all structural parameters and recovers a full posterior distribution for the causal effect, providing probability statements about the parameter rather than p-values — especially valuable when instruments are weak or the sample is small.
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Sources
- Kleibergen, F., & Zivot, E. (2003). Bayesian and classical approaches to instrumental variable regression. Journal of Econometrics, 114(1), 29-72. DOI: 10.1016/S0304-4076(02)00221-8 ↗
- Lancaster, T. (2004). An Introduction to Modern Bayesian Econometrics. Blackwell Publishing. ISBN: 978-1405117203