• 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 14 Slides

  • chapter 1
  • chapter 2
  • chapter 3
  • chapter 4