Dynamic Causal Effects in Econometrics by Emphasizing the Non Parametric Method : Review Papers

Recent advances and research in applications of causal inference have shown that the understanding of applied modeling in causal effects is of particular importance in econometrics. Our special focus is on reviewing dynamic causal research. This paper presents a review of the dynamic causality study method as well as linear method include of LP and VAR and non-linear statistical modeling and their application in econometrics. In particular, we study recent research in two categories: randomized experiments and observational studies. We finally show that the Bayesian Non parametric Causal Inference has the least bias in a non-parametric framework