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ECON526 Final Project:

These guidelines may be subject to change over the next few days. Please check back for updates.

The objective of the final project is to analyze the causal effect of some policy on an outcome. To achieve this, students should:

  1. Choose a policy to analyze: Students should select a treatment or policy that has been implemented in the real world, such as a government program or a corporate policy.

    • The term "policy" should be interpreted loosely in this context. In fact, it does not need to be a government or corporate policy, but can be any event that you want to study the downstream effects of. This could include a natural disaster, a change in the weather, a new innovation, etc.
    • The treatment also does not need to be binary. It can be a continuous variable, such as the amount of money spent on a program, or a categorical variable, such as the type of program implemented.
    • Really, the only requirement is that you answer a question of the form "What is the effect of X on Y?" where X is the treatment and Y is the outcome.

  2. Identify an outcome of interest: Students should identify an outcome that is affected by the policy, such as employment rates or health outcomes.

    • Like the treatment, this outcome does not need to be anything that is "classically economics". It can be anything that you are interested in studying.
    • You should think of this project as a portfolio piece that you can use to demonstrate your skills to potential employers. Therefore, you should choose a policy and outcome that you are interested in and that you think will be interesting to others.

  3. Collect data: Students should collect data on the policy and outcome of interest. This may involve gathering data from existing sources or conducting original research.

  4. Explain your identification strategy.

  5. Estimate the causal effect of the policy on the outcome: Students should use the data to estimate the causal effect of the policy on the outcome of interest. This may involve using a regression model, matching, difference-in-differences, instrumental variables, or some other model.

Guidelines:

  • The final project should be completed alone or with a single partner in a group of 2. If you choose to work with a partner, both students should submit the final report and both students will receive the same grade.

  • The project should include two documents, a PDF report and a Jupyter notebook.

  • The report should be written in clear, concise language and should be well-organized. It should include the following sections: Introduction, Data, Methods, Results, and Conclusion.

  • The report should include a brief literature review and bibliography of sources used.

  • The report should include a title that does not mention the course.

  • The accompanying code should be well-documented, commented, and easy to follow. It should also be reproducible, meaning that the code should always produce the same results when run from start to finish.

  • There is no minimum or maximum length for the report or the code, but it should be long enough to clearly explain the project and the results and include the necessary details.

  • Similarly, there are no specific formatting requirements (e.g. double-spaced, APA style, etc.), but the report should be well-formatted and easy to read.

  • The first deadline is November 27, when you should submit a first draft of the code and report. You may make changes to the code and report until December 15.

  • You are free to use data from previously published studies. However, all sources should be cited. Further, you must explain what you do that is new or different from the previous work.