Unit     Topics
1    Chap. 1, Intro
2    Chap. 2, Simple regression model
3    Chap. 3, Multiple regression: estimation
4    Chap. 3, Multiple Regression: estimation
5    Chap. 4, Multiple Regression: inference
6    EXAM 1
7    Chap. 5, OLS asymptotics
8    LAB Session
9    Chap. 6, Functional forms
10    Chap. 7, Binary variables
11    Chap. 8, Heteroskedasticity
12    EXAM 2

Introduction to R in class and in a lab session

IMPORTANT: Philipp Steinbrunner the organizes an R and Stata tutorial. Participation in one of the two tutorials is highly recommended. Please note, that both sessions cover the same topics - an introduction to R as well as Stata, so you can choose between

This course provides an introduction to the analysis of economic data using econometric methods that are based on the multiple regression model. After having taken the course, students should be able to ...

• understand and critically reflect empirical studies that apply these methods
• apply the theoretical knowledge acquired in the course to practical problems
  
• carry out econometric work by themselves
  

Weekly course with lectures, exercises and practical examples using R

GRADING

1) 40% exercises and participation
2) 30% Exam I
3) 30% Exam II

(minimum of 40% necessary in both Exams)

>87.5% 1
>75.0% 2
>62.5% 3
>50.0% 4

office hours upon appointment