Topic outline

  • General

    • This course provides an introduction to data analysis in applied microeconomics. We have designed it to complement the First Course in Probability and Statistics (MS-A0503) or equivalent introductory course in statistics. Our aim is to give a non-technical and intuitive overview of the modern microeconometric approaches with a particular focus on critically evaluating alternative data sources and research designs. 

      Preliminary outline:

      Part 1:
      Descriptive statistics and randomized experiments

      1. Introduction to data
      2. Descriptive statistics I
      3. Descriptive statistics II
      4. Causality and randomization
      5. Statistical significance
      6. Testing errors and human errors
      7. Compliance and limits of RCTs

      Part 2:
      Quasi-experimental approaches. Topics covered:

      1. Observational data and quasi experimental methods: intro
      2. Instrumental Variables (IV)
      3. Regression Discontinuity Design (RDD)
      4. Difference in Differences(DID)

      Matti Sarvimäki will teach lectures 1-7 and Miri Stryjan lectures 8-12. In addition, Aapo Stenhammar will give six exercise lectures, which will cover an introduction to the statistical software Stata (available for Aalto students at Grading will be based on exercises and pre-class assignments (50%) and final exam (50%).

      Outstanding textbooks covering most of the course's material include the modern classic Mastering 'Metrics by Josh Angrist and Steve Pischke and the new (and free) Causal Inference: The Mixtape by Scott Cunningham. The overlap is not perfect: we will cover material that is not discussed in these books and quite a bit of the books' material will be left for later courses. The exam will be based solely on material covered in class, assignments and exercises.