Due Nov 1
- Which problem will you be addressing? (Copy and paste your chosen prompt description)
- Why is it an important problem to solve? What is the impact? What’s the big picture?
- How will you be answering the question? Will you use regression analysis?
- If you’re planning on using regression analysis, you must answer the following questions:
- Does anybody in your group have experience using Stata? Stata is a program commonly used in economic consulting that is somewhat similar to Excel, but much more powerful. Who? (If not, it’s fine, but it makes the regression analysis a lot easier)
- What will your dependent variable be? How is it quantified? Please be specific. For instance, rather than saying “home value,” say “home value, as measured by price at last sale” or “home value, as measured by Zillow’s Zestimate.”
- Where is data for your dependent variable available?
- What independent variables do you plan to explore?
- Where is the data for your independent variables available?
- Why do you think these independent variables are relevant? (For instance, if you’re doing topic 3, you might say “I think crime rates are relevant to house prices because people are probably willing to pay more money for a house in a safe neighborhood since they value their security.” I think home size is relevant because…)
- Define multicollinearity. You can copy and paste a definition.
- If you are NOT planning on using regression analysis, you must answer the following question:
- Describe your general approach. Will it be rooted in examination of relevant literature? Relevant studies? Will you be interviewing people? Who?
- Please compare and contrast your methodology with regression analysis. What are 3 ways you think it’s better? 3 ways it might be worse?
- Please list the titles and authors of 5 scholarly articles or studies that are relevant to your topic.
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