The beginnings of the research project
I chose this topic because of my background interest in finance, and specifically, city finance led me to try to find a topic that fits with these interests. The reason I picked my topic was also that tariffs were on the brain due to their being in the news cycle. While doing my preliminary research, I was unable to find any sources that discussed the middle class and how they react in times of economic stress
Previous research has helped refine my topic by allowing me to see how different populations react in times of economic stress. Low-income people tend to tighten their budgets, and the uber-wealthy tend to just spend less on hyper luxuries. The other pieces of research that helped me were the fact that, as time has gone on the periods of economic shock have had less and less effects on the economy as our economy has become more robust, which leads to my research observing the effects over a period of time that has several shocks and normal periods.,
My methodology begins with randomly selecting cities with a median income between 55,000-166000 in the western United States; the region was selected randomly. Then these cities will be split into groups with or without a large shopping center, until there are 30 cities per group. The cities will be randomly selected to be divided to avoid bias. After selecting the data, I will pull the tax records from these cities and use linear regression modeling or quantitative general-equilibrium modeling to compare the 2 groups of cities, using a % change of tax revenue gained to factor for income.
image by Data science council of America
The reason that this research is important is that the data found in this research can help cities better plan out their spending patterns during a year of economic uncertainty. Depending on whether or not a large shopping center makes a city's tax revenue more robust or not can inform how a city should re-allocate unused tax revenue from previous years to better supplement a downturn year. And this data would allow for cities to keep more stable funding even in times of economic stress, meaning they wouldn't have to cut programs.
Image by Park Meadows Mall