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Labor Economics

Welcome to EC 350: Labor Economics (Winter 2022) at the University of Oregon.

This course applies insights from economic theory and real-world data to explore the causes of inequality in the labor market. Building upon concepts from introductory microeconomics, we will analyze the responses of workers and employers to changes in incentives, and consider the roles of policy, institutions, and other social phenomena in shaping labor market outcomes. As part of this line of inquiry, we will develop a toolkit that integrates theory and data, paying special attention to the ways in which we can identify—or fail to identify—causal relationships from data. Beyond refining their understanding of mechanisms that drive income inequality, successful students will leave the course with a framework for evaluating evidence and policy.

Lectures

The HTML versions of the lecture slides allow you to view animations and interactive features, provided that you have an internet connection. The PDF slides don't require an internet connection, but they cannot display the animations or interactive features.

  1. What is Labor Economics?
    .html | .pdf

  2. Inequality, Opportunity, and Science
    .html | .pdf

  3. Data and Causation
    .html | .pdf

  4. All About Regression
    .html | .pdf

  5. Learning from Observational Data
    .html | .pdf

  6. The Worker's Dilemma
    .html | .pdf

  7. Welfare and Work Incentives
    .html | .pdf

  8. The Employer's Dilemma
    .html | .pdf

  9. Robots and Taxes
    .html | .pdf

  10. Labor Markets
    .html | .pdf

  11. Monopsony
    .html | .pdf

  12. The Great Minimum Wage Debate
    .html | .pdf

  13. Compensating Wage Differentials
    .html | .pdf

  14. Human Capital
    .html | .pdf

  15. Signaling
    .html | .pdf

  16. Discrimination I
    .html | .pdf

  17. Discrimination II
    .html | .pdf

  18. Unions
    .html | .pdf

Other course content

For supplemental lecture documents, problem sets, and other materials, please see Canvas.

Contributors

I am indebted to Glen Waddell (@glenwaddell) for his generous contribution of course materials. I also source material from Ed Rubin (@edrubin) and Nick Huntington-Klein (@NickCH-K).

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