Directed acyclic graphs (DAGs) provide a transparent framework for encoding causal structures and identifying causal effects. This paper demonstrates how DAGs help specify local projections (LPs) for estimating causal impulse responses. Examples illustrate how graphical rules can be used to...

'Cause, Effect, and Everything in Between' introduces readers to causal inference: the science of cause-and-effect. Using examples and case studies, Aboozar Hadavand provides an accessible introduction to the fundamental concepts and methodology of causal inference. By the end of the book,...

This paper examines the econometric causal model for policy analysis developed by the seminal ideas of Ragnar Frisch and Trygve Haavelmo. We compare the econometric causal model with two popular causal frameworks: Neyman-Holland causal model and the do-calculus. The Neyman-Holland causal model...