Udemy - Instrumental Variables

What you'll learn
Understand the difference between correlation and causation as well as the underlying theory and assumptions of IV.
Identify suitable instrumental variables and assess the plausibility of the IV assumptions.
Estimate local average treatment effects using 2SLS with statistical software and interpret the results.
Critically evaluate published studies that use IV.
Design IV studies in real-world research settings.
Requirements
A basic understanding of statistics and linear regression is recommended. Familiarity with statistical software (like Stata or R) is helpful but not required, all necessary tools will be explained.
Description
Stop wading through countless pages filled with confusing equations. This course is structured in such a way that even those with a limited math background can understand the concepts and apply them.Learning GoalsUpon finishing a course on Instrumental Variables, you will be able to:Understand the difference between correlation and causation as well as the underlying theory and assumptions of IV.Identify suitable instrumental variables and assess the plausibility of the IV assumptions.Estimate local average treatment effects using 2SLS with statistical software and interpret the results.Critically evaluate published studies that use IV.Design IV studies in real-world research settings.Course content12 modules • 1h 46m total lengthCorrelation vs CausationUnmeasured ConfoundersReverse CausalityRandomized Control TrialsQuasi-Experimental MethodsIV - IntuitionNatural ExperimentsTwo Stage Least SquaresIV - AssumptionsStrengths and Weaknesses of IVR COMPUTER LAB: 2SLSStata COMPUTER LAB: 2SLSWho is This Course for?Edooko courses are designed for those who have some grasp of statistics. Our courses are an ideal fit for:Master studentsPh.D. candidatesResearchersPolicy makersData scientistsAnyone looking for training in quantitative methods.The material covered in our courses is not intended for individuals who are new to statistics and data analysis. If you have some grasp of statistical concepts and are seeking to enhance your understanding of quantitative methods, then our courses are the perfect choice for you. However, if you are at the beginning of statistical training, you may find our courses to be challenging and are advised to start with more foundational coursework first.
Who this course is for
This course is ideal for Master's and PhD students, data analysts, policy researchers, and economists interested in learning causal inference techniques and applying instrumental variable methods in real-world research settings.
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