The Influence of Gender Disparities on the Unemployment Rate in the United States amid the Covid-19 Pandemic

Abstract

The COVID-19 pandemic, which emerged in late 2019 and quickly spread globally in 2020, hit economic activity tough in most countries. In the United States, the socially enforced shutdown and economic stagnation caused by the pandemic led to a rapid rise in unemployment from the first quarter of 2020 onwards. Although the rise in unemployment rates in the US during the pandemic involves individuals of every gender, the COVID-19 pandemic's effects on the rise in unemployment rates were different for men and women, according to examination of statistics on unemployment for both genders from 2010 to 2023, with women experiencing a greater increase in their unemployment rate compared to men during the pandemic. Moreover, by constructing an ARIMA model based on the unemployment rates of different genders from 2010 to 2019, this paper predicts the unemployment rate of the United States from 2020 to 2023 under the assumption of no pandemic effects. It can be observed that the pace of decline in female unemployment rates during the pandemic was larger than that for male unemployment rates by comparing the gap between the prediction model and the actual data, and by January 2023, whether overall unemployment rates or unemployment rates across different genders were significantly higher than those predicted by the ARIMA model. The data compilation and analysis presented within this paper are useful in understanding the impact of public health events on employment status based on gender differences, and in providing a reference for post-COVID-19 mitigation policies.