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Lecture 2: Simple Regression Model: Regression with One Regressor (Part I:…
Lecture 2: Simple Regression Model: Regression with One Regressor
Part I: Estimation
An example: "Return to education"
Definition of the simple regression model
Terminology
Graphically Representation of population regression function (PRF)
Estimation of the model: OLS
Basic idea
Getting OLS estimator: computation vs. Stata.
Algebra properties
The effects of scaling and translation on estimates
Nonlinearities
Measure of fit
R²
SER: Standard Error of the Regression
Desirable properties of OLS estimator and required assumptions
Unbiasedness, consistency and large sample distribution
The least squares model and sampling scheme assumption
Causality and condition mean assumption
Definition of causality
Conditioning vs. fixing
RCTs and the simple regression model
RCTs basics
Simple regression methods for RCTs
Part II: Statistical Inference