
Sign up to save your podcasts
Or
Welcome to this week’s episode of The Mixtape with Scott. Today’s podcast guest is our 127th guest on the show—Vitor Possebom, Assistant Professor in the Department of Economics at the Fundação Getulio Vargas. Vitor’s research sits at the intersection of two areas — econometrics and causal inference, and policy evaluation in Latin America, particularly Brazil.
His contributions revolve around refining and extending tools for estimating causal effects in observational data, especially under common data imperfections like selection bias, measurement error, and treatment effect heterogeneity.
* Sample selection and marginal treatment effects (e.g., “Identifying Marginal Treatment Effects in the Presence of Sample Selection” (Journal of Econometrics), “Crime and Mismeasured Punishment” (Review of Economics and Statistics))
* Misclassification and measurement error (e.g., “Potato Potahto in the FAO-GAEZ Productivity Measures?”)
* Inference and sensitivity in synthetic control methods (e.g., “Cherry Picking with Synthetic Controls”, “Synthetic Control Method: Inference, Sensitivity Analysis and Confidence Sets”)
* Probability of causation in non-experimental settings (e.g., “Probability of Causation with Sample Selection”)
I invited Vitor onto the podcast because of his creative contributions to causal inference, as he fits into a larger informal series I’ve been for the last several years on causal inference in general. In today’s conversation, we talk about Vitor’s path from Brazil to Yale University and then back. Vitor, thank you so much for joining us.
Scott's Mixtape Substack is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.
4.9
77 ratings
Welcome to this week’s episode of The Mixtape with Scott. Today’s podcast guest is our 127th guest on the show—Vitor Possebom, Assistant Professor in the Department of Economics at the Fundação Getulio Vargas. Vitor’s research sits at the intersection of two areas — econometrics and causal inference, and policy evaluation in Latin America, particularly Brazil.
His contributions revolve around refining and extending tools for estimating causal effects in observational data, especially under common data imperfections like selection bias, measurement error, and treatment effect heterogeneity.
* Sample selection and marginal treatment effects (e.g., “Identifying Marginal Treatment Effects in the Presence of Sample Selection” (Journal of Econometrics), “Crime and Mismeasured Punishment” (Review of Economics and Statistics))
* Misclassification and measurement error (e.g., “Potato Potahto in the FAO-GAEZ Productivity Measures?”)
* Inference and sensitivity in synthetic control methods (e.g., “Cherry Picking with Synthetic Controls”, “Synthetic Control Method: Inference, Sensitivity Analysis and Confidence Sets”)
* Probability of causation in non-experimental settings (e.g., “Probability of Causation with Sample Selection”)
I invited Vitor onto the podcast because of his creative contributions to causal inference, as he fits into a larger informal series I’ve been for the last several years on causal inference in general. In today’s conversation, we talk about Vitor’s path from Brazil to Yale University and then back. Vitor, thank you so much for joining us.
Scott's Mixtape Substack is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.
4,226 Listeners
32,174 Listeners
2,380 Listeners
25,772 Listeners
111,294 Listeners
529 Listeners
6,756 Listeners
2,519 Listeners
730 Listeners
174 Listeners
2,134 Listeners
5,425 Listeners
15,206 Listeners
8,591 Listeners
265 Listeners