In this study, we seek to understand how macroeconomic factors such as GDP, inflation, Unemployment Insurance, and S&P 500 index; as well as microeconomic factors such as health, race, and educational attainment impacted the unemployment rate for about 20 years in the United States. Our research question is to identify which factor(s) contributed the most to the unemployment rate surge using linear regression. Results from our studies showed that GDP (negative), inflation (positive), Unemployment Insurance (contrary to popular opinion; negative), and S&P 500 index (negative) were all significant factors, with inflation being the most important one. As for health issue factors, our model produced resultant correlation scores for occurrences of Cardiovascular Disease, Neurological Disease, and Interpersonal Violence with unemployment. Race as a factor showed a huge discrepancies in the unemployment rate between Black Americans compared to their counterparts. Asians had the lowest unemployment rate throughout the years. As for education attainment, results showed that having a higher education attainment significantly reduced one chance of unemployment. People with higher degrees had the lowest unemployment rate. Results of this study will be beneficial for policymakers and researchers in understanding the unemployment rate during the pandemic.

翻译：本研究旨在探究宏观经济因素（如GDP、通货膨胀、失业保险和标普500指数）以及微观经济因素（如健康状况、种族和教育程度）如何影响美国近20年来的失业率。我们的研究问题是通过线性回归识别对失业率飙升贡献最大的因素。研究结果表明，GDP（负向）、通货膨胀（正向）、失业保险（与普遍观点相反；负向）和标普500指数（负向）均为显著影响因素，其中通货膨胀最为重要。在健康问题因素方面，我们的模型得出了心血管疾病、神经系统疾病和人际暴力事件与失业率的相关性得分。种族因素显示，美国黑人与其他种族群体之间的失业率存在巨大差异，而亚裔群体的失业率多年来始终最低。在教育程度方面，结果表明更高的教育水平能显著降低失业概率，拥有更高学历者的失业率最低。本研究结果将有助于政策制定者和研究人员理解疫情期间的失业率动态。