UC Merced Undergraduate Research Journal

Innovation has increased dramatically since the advent of the 1765 steam machine. Today, we possess technology that can process millions of instructions in a matter of seconds. Endogenous growth theory has stressed the importance of technological change and education as a source of economic growth. Thanks to technological innovation and the related economic growth, many people are better off today than before. However, computers cannot mimic human capacity in creativity and the ability to envision new solutions to existing problems. The rate at which workers use these unique capabilities is industry related. Therefore, in this study I relate the proportion of workers in each industry to known industry level innovation rates to predict economic growth rates at the local level. This study is especially important, as it guides policy makers as to what incentives they might use to attract new industries to bolster their future economic well being. Specifically, this study analyzes how innovation and other factors impact growth in the United States through the years 2005-2015 at the Metropolitan Statistical Area (MSA) using a lagged first-difference quantitative statistical model. This model is well matched to the structure of the data in revealing causality between the independent variables and the dependent. Results indicate no significant relationship between innovation, as measured by localized Multifactor Productivity (MFP), and growth. However, results do indicate a strong relationship between educational attainment and economic growth. Quantitative analysis reveals that a 1% increase in average years of education within an MSA will, on average, cause an increase in localized GDP the following year by 2.33%. Future research is encouraged to better understand the matter and to determine policies that can aid educational attainment and thus, boost economic growth.