A Study on the Census of the U.S. Labor Market and Income Distribution Based on Big Data

The US labor market has always been plagued by wage inequality due to differences in workers' gender, race, and educational background. This paper uses the 1994 US Census dataset (32,561 people) to analyze the impact of US workers' demographic factors on their income and working hours using Pearson correlation analysis and T-test. The statistical results show that higher education levels are significantly correlated with higher incomes (r=0.45), white people occupy high-paying jobs in the United States, and minorities do not account for a high proportion of high-level positions; men work an average of 42.4 hours per week, while women work 36.4 hours (p<0.01). These gaps reflect differences and unfairness in income caused by racial discrimination, unequal educational opportunities, and excessive family care responsibilities for women. Comparative analysis of policies in various countries shows that intervention measures such as childcare subsidies and vocational skills training programs in the European system can help reduce inequality in the US labor market. The results revealed the inequality in the US labor market and point out the need for the United States to promote citizens' fair participation in the labor market through targeted policy measures.