The Effect of Gender, Internet Access, and Ethnicity on Earnings: An Empirical Assessment for Texas in 2018

This research uses Becker’s human capital theory to empirically assess the effect of gender, digital divide, and ethnicity on earnings using 2018 Public Use Micro Statistical data for the State of Texas. The paper suggests the application of different empirical techniques to estimate the effects of ethnicity on the gender gap, digital divide, and earning disparities. Education, experience, age, and other earning drivers are considered in this research. The empirical techniques applied in this research are OLS, WLS, LASSO, Ridge, and White’s Robust error regression. Holding the rest of the earnings determinants constant, results suggest that there is enough evidence to support that the wages of females are significantly lower than those of males by 0.2%. In addition, individuals with internet access are statistically higher than those individuals without internet access by 1.5%. Results suggest that a Hispanic individual without internet access makes 0.3% less than non-Hispanic individuals without internet access. Education and experience are statistically significant factors affecting the earnings of the representative individual positively by 0.28 and 0.10%. Digital divide and disparities in earnings based on gender and ethnicity prevent digital innovation and business sustainability. Results in this paper could be used to seek collaboration between policymakers, business leaders, and higher education institutions to highlight the relevance of implementing effective measures to close the gender gap, digital divide, and difference in earnings in non-majority groups of the population. The paper contributes to applying empirical measures to support the UN’s SDGs 4 and 5 as it refers to promoting inclusive and equitable quality education and gender equality.