Week 9- Improving My Final Product

This week was mainly spent improving the first draft of my final product that I submitted last week. Rather than focusing on the limitations of each regression based on the variables I used in each one, like last week, I focused more on identifying limitations of the approach as a whole this time, such as the April 2025 Liberation Day tariff increase, which could have influenced the pre-shutdown trend that I was comparing the post-shutdown trend to. Additionally, I added all my sources, from which I obtained my datasets, to my bibliography, as they are also important references.

I also realized I didn’t properly explain the variables I created to support the regression analysis, including t, D, D_t, and t_centered. To fix this, I created a section of my paper to define each variable and made a chart explaining what the characteristics of these variables contribute to my final interpretation. For coefficients, this usually meant explaining how they show a positive correlation when they are positive and significant, and for p-values, this meant detailing how they are considered significant when less than 0.05. I also explained the process of how I created my graphs and what they signified, as I realized that could be confusing for someone not as familiar with regression analysis.

To provide more context for my analysis, I also provided the basic universal simple regression equation and showed how adding other variables, through my multivariate regressions, affects that equation. I also added how the coefficient and p-value of shutdown-intensity variables should be interpreted in the table with the other independent variables.