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 download.aalto.fi). 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.


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