Imagination Exercise
All materials can be found at alexcardazzi.github.io.
Completion Requirements: Complete the following questions in RStudio via the imagination template. When you are ready, submit your rendered html to Canvas. For online students: be sure to also upload your video abstract to Canvas. For in person students: be sure to prepare your pitch for an in class discussion.
Grading Criteria: Full credit will be given to well formatted and detailed answers. Partial credit will be given if I can follow your work and/or see your thought process via code, comments, and text. Point totals are listed next to each question.
Assignment Summary
Malcolm Gladwell, the host of Revisionist History, spends six episodes asking (social) scientists about what their “magic wand experiment” would be.
What if you could design any experiment you wanted? Without worrying about money, ethics, logistics, or even the laws of nature? Revisionist History kicks off the season by giving some of the world’s smartest scientists a magic wand to create the experiment of their dreams.
These scientists come up with a bunch of different studies and research designs that would allow them to differentiate between correlation and causality. In this assignment, students will have to imagine up their own magic wand experiments with one condition: each experiment must use the particular causal inference strategy being studied. Students will have to write up their research designs and pitch them to the class.
Your imagination exercise should address the following questions. Write your answers in a Quarto document and submit a rendered HTML file on Canvas. Your submission should contain the exact same 5 headings shown below along with your text and graphs, where appropriate, addressing all questions.
Application Description
Describe the application you imagine using the particular method we’re studying. Be sure to include a testable hypothesis and/or an answerable, specific research question. Describe any backdoors that pose a threat to your identification strategy and how you might address them. (4 Points)
Data Description
Describe the ideal data set for identifying the causal effect of interest described in the application above. You don’t need to constrain yourself to known, existing variables and data sets, although identifying actual data is OK. You can also assume you have unlimited ability/resources to measure variables if you want. Identify the dependent variable in your regression model and the explanatory variables. (4 Points)
Causal Inference Method Description
Discuss why the method we’re studying is suited to the application and data described above. What assumptions must hold for the method to deliver plausibly causal estimates? (4 Points)
Expected Results
What is the expected sign of the causal parameter of interest? Explain what this parameter means in words, in terms of this specific application. Explain why (or why not) you think that the estimated relationship reflects causality, and not just correlation. (4 Points)
What Will Be Learned?
What will you learn from this empirical analysis? Why is this causal relationship important in the context of your application? How can this evidence be used to inform policy, business decisions, or your own behavior? (4 Points)
Video Abstract (online students only)
Submit a short (e.g. 3-5 minutes) video pitch of your imagination exercise. Be sure to cover all of the above topics including (but not limited to) institutional knowledge/background, specific research question, general and specific threats to your identification strategy, necessary assumptions, data, etc. (6 Points) In addition, provide comments to two other students via the discussion board. Comments may be made up to a week after the due date of the assignment. (4 Points)