Foundation of Economics Science (for Computer Scientists)

Course Outline:

  1. Understanding Individual Choices using Machine Learning
  2. Data as a Good
  3. Taxation in the Age of Information Technologies
  4. Growth and Innovation
  5. Discrimination and AI Bias
  6. Networks and Social Media
  7. Blockchain & Bitcoin

Politics and Economics

Course Outline:

  1. Interpersonal Utility Comparison
  2. Politics/Politicians/Ideology
  3. Lobbying
  4. Efficiency: Behaviroul Biases and Addiction
  5. Efficiency: Market Power
  6. Efficiency: Negative Externalities
  7. Equality: Theories of Justice
  8. Equality: Social Insurance
  9. Equality: Discrimination
  10. Conflict
  11. Social Media

Machine Learning Applications in Economics

Course Outline:

  1. Introduction Machine Learning and Economics
  2. A Short Introduction to Natural Language Processing
  3. Applications of Supervised Machine Learning
    • Demand Estimation
    • Measuring Racial and Gender Biases Word Embeddings
    • Measuring Visual Bias using Image Classification
  4. Applications of Unsupervised Machine Learning
    • Measuring Ideology using Clustering
    • Measuring Knowledge Transfers with LSA
    • Measuring Central Bank Communication using LDA

Machine Learning Reading Group

Reading Group Outline:

  1. Text as Data
  2. Supervised Machine Learning
  3. Supervised Machine Learning Classifiers
  4. Causal Machine Learning
  5. Unsupervised Machine Learning
  6. Topic Models

A Primer in Social Media Research

Lecture Outline:

  1. Why Social Media Research is Relevant
  2. How to Collect Social Media Data
  3. Using Machine Learning for Social Media Research
  4. Examples of Social Media Research