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Author: Burnett, J. Wesley
Resulting in 1 citation.
1. Burnett, J. Wesley
Blackwell, Calvin
Graphical Causal Modelling: an Application to Identify and Estimate Cause-and-Effect Relationships
Applied Economics published online (7 May 2023): DOI: 10.1080/00036846.2023.2208856.
Also: https://www.tandfonline.com/doi/full/10.1080/00036846.2023.2208856
Cohort(s): NLSY79
Publisher: Taylor & Francis
Keyword(s): College Degree; High School Completion/Graduates; Modeling; Propensity Scores; Student Loans / Student Aid

This paper offers an accessible discussion of graphical causal models and how such a framework can be used to help identify causal relations. A graphical causal model represents a researcher’s qualitative assumptions. As a result of the credibility revolution, there is growing interest to properly estimate cause-and-effect relationships. Using several examples, we illustrate how graphical models can and cannot be used to identify causation from observational data. Further, we offer a replication of a previous study that explored college enrollment by high school seniors who were eligible for student aid. From the original study, we use a graphical causal model to motivate the quantitative and qualitative modelling assumptions. Using a similar difference-in-difference approach based on propensity score matching, we estimate a smaller average treatment effect than the original study. The smaller estimated effect arguably stems from the graphical causal model’s delineation of the original model specification.
Bibliography Citation
Burnett, J. Wesley and Calvin Blackwell. "Graphical Causal Modelling: an Application to Identify and Estimate Cause-and-Effect Relationships." Applied Economics published online (7 May 2023): DOI: 10.1080/00036846.2023.2208856.