Week2: First Draft Prompt Assignment
Use the results from the first two assignments, what you have learned in class, and what you have learned from reading the papers and textbook for the course to answer the following questions.
- Did assigning a person to get an encouraging phone call increase their probability of voting?
AND
- Can we get an estimate of the causal effect of getting a call encouraging you to vote on your probability of voting with non-experimental data by using regression to adjust for differences between people who got a call and those that didn’t (why or why not)?
[NOTA BENE: This is a paper about whether or not a non-experimental research design can be used to generate credible causal estimates. This is done by comparing and contrasting experimental estimates and non-experimental regression adjustment estimates. The context has to do with voting, but the focus of the paper should be empirical designs, nonvoting.]
Structure of Paper
You can use the papers on the reading list as a guide for what a paper should look like. You can include your tables in the body of the paper or put them at the end of the paper. Your paper should be 10 pages long without counting tables and you will want to include the following sections:
- Title: Your paper should have an informative title.
- Abstract: One paragraphs that sums up the key elements of the paper. Write this first.
- Introduction: 1-1.5pagesthat sums the paper up with more detail than the abstract. Should tell the reader why the questions the paper answers are important and cover data, econometric methods, results,and conclusion.
- Data: Describe the data you use in the analysis and how it was generated. You may need to do some research online.
- Empirical Methods: Describe the statistical methods used. Include the equations for the regressions you will run. Describe each part of the regression and what the coefficients will reveal. Describe the assumptions under which the results will generate causal effects.
- Results: Describe and interpret your statistical findings. Be detailed. Discuss the robustness of your estimates.
- Conclusion: Interpret your findings and how they answer the motivating questions.