Topic outline

  • General

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      Topic: Lecture 12: Principles of Empirical Analysis
      Time: Feb 14, 2024 14:15 Helsinki
      Meeting ID: 618 5597 7680

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      This detailed course plan contains details on the course setup, grading and deadline policies, as well as the topics, dates and locations of each lecture and exercise session and the relevant deadlines.

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      Here is a link to join the course’s Slack channel:

      There you can ask questions related to assignments (channel #assignments) and to general course matters (channel #general). Also, please feel free to answer each other’s questions there!

    • Course description and learning objectives

      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. See the uploaded Course plan for a detailed outline of the lectures and course components!

      Brief outline: 

      Part 1:

      1. Introduction to data
      2. Samples and descriptive statistics
      3. Conditional descriptive statistics
      4. Causality and randomization
      5. Statistical inference
      6. Revealed preferences in observed data
      Part 2:

      1. Observational data and quasi experimental methods: intro
      2. Difference in Differences(DID)
      3. Regression Discontinuity Design (RDD)
      4. Compliance 
      5. Instrumental Variables (IV)
      Prottoy A. Akbar will teach lectures 1-6 and Miri Stryjan lectures 7-12. In addition, Martta Rautala will lead five exercise sessions, which will cover an introduction to the statistical software Stata (available for Aalto students at Grading will be based on homework assignments (40%), pre-class and in-class assignments (15%) and a final exam (45%).

      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.

      Other course policies

      Disability information: If you have a disability that requires special testing accommodations or other classroom modifications, you need to notify the instructor no later than the first week of the course period. You may be asked to provide documentation of your disability to determine the appropriateness of accommodations. See for more information!

      Classroom recording: To ensure the free and open discussion of ideas, students may not record classroom lectures, discussion and/or activities without the advance written permission of the instructor, and any such recording properly approved in advance can be used solely for the student's own private use.