In this case study, a framework to research economic development is presented. The framework was developed to better understand economic development in large U.S. cities. Because regional economies operate under a single macroeconomic climate, the research techniques applied in international comparisons of economic development can be modified to better evaluate the nuances of the economies being studied. The framework outlined in this case study can be used to guide data selection and the aggregation of said data into an economic development index. Correlation coefficients are discussed because of their merit in guiding the choice of which data to include. In addition, systematically excluding data series within an index is shown to allow the researcher to determine if the index is robust to the data it is comprised of. The advantages and disadvantages of using the arithmetic mean in aggregating data are also discussed. After reading this case study, you will be able to apply the framework outlined for your own research purposes.