Module 0: Formalities

Econometrics I

Max Heinze (mheinze@wu.ac.at)

Department of Economics, WU Vienna

March 6, 2025

 

 

 

Semester Plan

Assessment Criteria

Textbooks

Statistical Software

Schedule

Date Time Location Alternative I Alternative II
Thu, 06 March 12:00–14:00 TC.3.12
Thu, 13 March 12:00–14:00 TC.3.12
Thu, 20 March 12:00–14:00 TC.3.12
Thu, 27 March 12:00–14:00 TC.3.12
Thu, 03 April 12:00–14:00 TC.3.12 1st Midterm (20%)
Thu, 10 April 12:00–14:00 TC.3.12
Easter break; 1 May
Thu, 08 May 12:00–14:00 TC.3.12 Midterm (40%)
Thu, 15 May 12:00–14:00 TC.3.12
Thu, 22 May 12:00–14:00 TC.3.12 2nd Midterm (20%)
Ascension Day
Thu, 05 June 12:00–14:00 TC.3.12
Thu, 12 June 12:00–14:00 TC.3.12
Corpus Christi
Thu, 26 June 12:00–14:00 D4.0.022 Final Exam (40%) Final Exam (40%)

Content Plan

Date Time Location Topics
Thu, 06 March 12:00–14:00 TC.3.12 Module 0: Formalities; Module 1: Introduction (Wooldridge Ch. 1)
Thu, 13 March 12:00–14:00 TC.3.12 Module 2: Simple Linear Regression (Wooldridge Ch. 2)
Thu, 20 March 12:00–14:00 TC.3.12 Module 2: Simple Linear Regression
Thu, 27 March 12:00–14:00 TC.3.12 Module 2: Simple Linear Regression
Thu, 03 April 12:00–14:00 TC.3.12 Module 3: Multiple Linear Regression (Wooldridge Ch. 3)
Thu, 10 April 12:00–14:00 TC.3.12 Module 3: Multiple Linear Regression
Easter break; 1 May
Thu, 08 May 12:00–14:00 TC.3.12 Module 4: Testing and Inference (Wooldridge Ch. 4 and 5)
Thu, 15 May 12:00–14:00 TC.3.12 Module 4: Testing and Inference
Thu, 22 May 12:00–14:00 TC.3.12 Module 5: More on Multiple Regression (Wooldridge Ch. 2.4, 6.1, 6.2, 7)
Ascension Day
Thu, 05 June 12:00–14:00 TC.3.12 Module 6: Heteroskedasticity (Wooldridge Ch. 8)
Thu, 12 June 12:00–14:00 TC.3.12 Buffer and Q&A Session
Corpus Christi
Thu, 26 June 12:00–14:00 D4.0.022 Final Exam (40%)

 

 

Semester Plan

Assessment Criteria

Textbooks

Statistical Software

 

Components

  • 20% Assignments and Participation
  • 40% Midterm Exam
    • Thu, 08 May
    • Simple and Multiple Linear Regression
    • 60 minutes
  • 40% Final Exam
    • Thu, 26 June
    • Entire course content
    • 120 minutes
  • 20% Assignments and Participation
  • 20% 1st Midterm Exam
    • Thu, 03 April
    • Simple Regression
    • 40 minutes
  • 20% 2nd Midterm Exam
    • Thu, 22 May
    • Multiple Linear Regression, Testing and Inference
    • 40 minutes
  • 40% Final Exam
    • Thu, 26 June
    • Entire course content
    • 120 minutes

Grading Scheme

  • The components are weighted as outlined above. The final grade is then determined by the following scale:
Grade from to
1 Very Good 87.5 %
2 Good 75.0 % < 87.5 %
3 Satisfactory 62.5 % < 75.0 %
4 Sufficient 50.0 % < 62.5 %
5 Insufficient < 50.0 %
  • No rounding is applied.

Vote on the Mode




 

Semester Plan

Assessment Criteria

Textbooks

Statistical Software

 

 

Wooldridge (2020): Introductory Econometrics

Type of Literature

  • Primary course textbook
  • Scope of material defined by the lecture slides

Availability

  • Available at the WU library, PDFs of older editions can be found online

Edition

  • We use the 7th edition, but older editions can also be used (mostly differ in page numbers, etc.)

Stock & Watson (2019): Introduction to Econometrics

Type of Literature

  • Supplementary textbook

Availability

  • Online access via WU library catalog

Angrist & Pischke (2008): Mostly Harmless Econometrics

Type of Literature

  • Supplementary literature on advanced topics
  • Introductory chapters can also be used as supplementary reading for Econometrics I

Availability

  • Available at the WU library

Hanck et al. (2024): Intro to Econometrics with R

Type of Literature

  • Online textbook
  • Useful supplementary material especially for working with R

Availability

Cunningham (2021): Causal Inference. The Mixtape

Type of Literature

  • Available in print and online
  • Supplementary reading for advanced topics
  • Introductory chapters also suitable as supplementary reading for Econometrics I

Availability

Hackl (2012): Einführung in die Ökonometrie

Type of Literature

  • German-language textbook
  • Slightly outdated
  • Recommended if understanding the English textbooks is difficult

Availability

  • Online access via the WU library catalog

Semester Plan

Assessment Criteria

Textbooks

Statistical Software

 

 

 

R, Stata, Python

  • The focus of this course is on theoretical foundations, but we will also discuss how to apply concepts using real data.
  • You will also work with data in the homework assignment.
  • You are generally free to choose which software you use to complete the tasks (results should be more or less the same):
    • R is widely used, open source, and free. Code examples in this course are provided in R.
    • Stata is proprietary but preferred by some economists.
    • Python
    • Eviews
    • Julia
    • Microsoft Excel (just don’t)