Data-Driven Public Policy

ECN435 Data-Driven Public Policy

Autumn 2022

  • Topics

    Should there be a wealth tax? How generous should social insurance benefits, like unemployment benefits, be? Is a universal basic income a good idea? How can we combat climate change? These pressing public policy questions seem unrelated but as you will learn in this course one can think about these issues as an optimal tax problem. This course discusses the tools of public economics to thoroughly analyze the above-mentioned questions and puts particular emphasis on data analysis to provide evidence-based policy recommendations.

    The teaching block of this course is divided into four parts:

    • Taxation and Inequality (with a special focus on wealth taxes).
    • Social Insurance.
    • Universal Basic Income.
    • Climate Change.

    The course will give students an introduction to frontier research and policy applications in public economics in a manner that makes the course suitable both for students starting a major in economics, as well as for students exploring economics as a supplement to their profile. In the context of these topics, the course will provide a non-technical introduction to both basic public economics theory and basic methods in data analysis, including causal inference and machine learning. The course should equip students with tools to thoroughly analyze data and public policy questions as well as enable students to provide evidence-based policy recommendations.

    The teaching block will take place in the first half of the semester with classical lectures, in-class discussions, and problem sets. In the second half of the course, students work out a research proposal on any topic of their choice. Students will present an early version of their proposal and receive repeated feedback. The idea of the research proposal is that students use this opportunity to develop ideas for their Master thesis and learn how to answer a question of their choice in a structured way.

  • Learning outcome

    Knowledge

    Upon completion of the course, students will know how to:

    • analyze policy issues using the public economics framework (equity vs. efficiency trade-offs)
    • use data to inform policy discussions / answer research questions
    • use empirical methods for testing the implications of theoretical economic models, evaluating policies, and interpret the results.

    Skills

    Upon completion of the course, students will:

    • be able to analyze the impact of various public policy proposals
    • be able to analyze the economic and social consequences of public policy reforms
    • formulate a research question of their choice and develop a plan to answer this question in a structured way.

    General Competence

    Upon completion of the course, students will:

    • be able to debate public policy issues in a structured way
    • be able to evaluate consequences of government policies
    • be able to provide evidence-based policy recommendations
    • be able to present research proposals.

  • Teaching

    Plenary lectures (in classroom), labs, assignments, and class presentations (in groups).

  • Recommended prerequisites

    None.

  • Required prerequisites

    None.

  • Credit reduction due to overlap

    None.

  • Compulsory Activity

    Presentation of research proposal.

  • Assessment

    The final grade will be based on

    1. Individual midterm written 2-hour at home exam (50%)

    2. Term paper in groups of 2 students (50%): Students develop a research proposal of at most 3 pages that outlines a clear research question, motivates the relevance of the research question and presents a plan to answer the research question (what methods are suitable to answer the research question, what data is needed). The research proposal has to be handed in by the end of November. Students need to present their proposal in class during the semester and will receive feedback on their ideas/proposals. The presentation does not count towards the grade but is necessary to qualify to be evaluated.

    Language: English.

  • Grading Scale

    A-F

  • Computer tools

    Stata, R

  • Literature

    Papers.

Overview

ECTS Credits
7.5
Teaching language
English.
Semester

Autumn. Offered autumn 2022.

Course responsible

Assistant Professor Andreas Haller, Department of Economics