ScPo 2nd Year Econometrics
Syllabus
1
Introduction to
R
1.1
Getting Started
1.2
Starting R and RStudio
1.3
Basic Calculations
1.4
Getting Help
1.5
Installing Packages
1.6
Code
vs Output in this Book
1.7
ScPoEconometrics
Package
1.8
Data Types
1.9
Data Structures
1.10
Data Frames
1.11
Programming Basics
2
Working With Data
2.1
Summary Statistics
2.2
Plotting
2.3
Summarizing Two Variables
2.4
The
tidyverse
3
Linear Regression
3.1
How are
x
and
y
related?
3.2
Ordinary Least Squares (OLS) Estimator
3.3
Predictions and Residuals
3.4
Correlation, Covariance and Linearity
3.5
Analysing
\(Var(y)\)
3.6
Assessing the
Goodness of Fit
3.7
An Example: California Student Test Scores
4
Multiple Regression
4.1
All Else Equal
4.2
Multicolinearity
4.3
California Test Scores 2
4.4
Interactions
5
Categorial Variables
5.1
Categorical Variables in
R
:
factor
5.2
Saturated Models: Main Effects and Interactions
6
Standard Errors
6.1
What is
true
? What are Statistical Models?
6.2
The Classical Regression Model
6.3
What’s in my model? (And what is not?)
7
Quantile Regression
8
Panel Data
8.1
fixed effects
8.2
DiD
8.3
RDD
8.4
Example
9
Instrumental Variables
9.1
Simultaneity Bias
10
Logit and Probit
11
Principal Component Analysis
12
Advanced
R
12.1
More Vectorization
12.2
Calculations with Vectors and Matrices
12.3
Matrices
13
Notes
13.1
Book usage
14
Slides
References
Published with bookdown
Introduction to Econometrics with R
Chapter 11
Principal Component Analysis