Synthetic Control Explained
Synthetic Control is one of the most important method in economics/social sciences to understand cause and effect. I use the following paper in the video: Andersson, Julius J. "Carbon taxes and CO2 emissions: Sweden as a case study." American Economic Journal: Economic Policy 11.4 (2019): 1-30.

▶︎
Susan Athey: Synthetic Difference in Differences

▶︎
Synthetic control methods: Introduction & overview of recent developments - Dr Carl Bonander

▶︎
1986: How to Spot the Upper Class | That's Life! | BBC Archive

▶︎
Causal Inference - EXPLAINED!

▶︎
Alberto Abadie: A Penalized Synthetic Control Estimator for Disaggregated Data

▶︎
Bayesian Inference: Overview

▶︎
Lecture 14: Canonical Research Designs II: Event Studies, Synthetic Control + Synthetic DinD

▶︎
Synthetic Control Methods

▶︎
The Big Short (2015): The Jenga Scene – Explaining the Financial Collapse

▶︎
Introduction to difference in differences in Stata 17

▶︎
Randomized Controlled Trials (RCTs)

▶︎
KMV model explained: Modelling default risk (Excel)

▶︎
Synthetic Control: Math Explained

▶︎
Nick Jones, Sam Barrows: Uber's Synthetic Control | PyData Amsterdam 2019

▶︎
2021, Methods Lecture, Alberto Abadie "Synthetic Controls: Methods and Practice"

▶︎
Difference-in-differences | Synthetic Control | Causal Inference in Data Science Part 2

▶︎
Data science tutorial: Synthetic Control Models for Causal Inference

▶︎
Once You Learn Economics, You Can't Be MANIPULATED Anymore

▶︎
Difference in Difference : Data Science Concepts

▶︎
