
The Influence of Gender Disparities on the Unemployment Rate in the United States amid the Covid-19 Pandemic
- 1 Shandong University
* Author to whom correspondence should be addressed.
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.
Keywords
Covid-19, gender, unemployment, ARIMA model
[1]. Gallant, J., Kroft, K., Lange, F., & Notowidigdo, M. J. (2020). Temporary Unemployment and Labor Market Dynamics during the COVID-19 Recession. Brookings Papers on Economic Activity, 2020(3), 167-226.
[2]. Couch, K. A., Fairlie, R. W., & Xu, H. (2022). The evolving impacts of the COVID-19 pandemic on gender inequality in the US labor market: The COVID motherhood penalty. Economic Inquiry, 60, 485-507.
[3]. Ozili, P. K., & Thankom, A. (2020). Spillover of COVID-19: Impact on the Global Economy. Retrieved from SSRN website: https://ssrn.com/abstract=3562570
[4]. Gezici, A., & Ozay, O. (2020). How race and gender shape COVID-19 unemployment probability. Retrieved from SSRN website: https://ssrn.com/abstract=3675022
[5]. Gezici, A., & Ozay, O. (2020). An Intersectional Analysis of COVID-19 Unemployment. Journal of Economics and Race Policy, 3, 270-281. https://doi.org/10.1007/s41996-020-00075-w
[6]. Alon, T. M., Doepke, M., Olmstead-Rumsey, J., & Tertilt, M. (2020). The impact of COVID-19 on gender equality. National Bureau of Economic Research. No. w26947
[7]. Albanesi, S., & Kim, J. (2021). The gendered impact of the COVID-19 recession on the US labor market. National Bureau of Economic Research, No. w28505.
[8]. Benvenuto, D., Giovanetti, M., Vassallo, L., Angeletti, S., & Ciccozzi, M. (2020). Application of the ARIMA model on the COVID-2019 epidemic dataset. Data in brief, 29, 105340.
[9]. Parolin, Z. (2020). Unemployment and child health during COVID-19 in the USA. The Lancet Public Health, 5(10), e521-e522.
[10]. Russell, L., & Sun, C. (2020). The effect of mandatory child care center closures on women’s labor market outcomes during the COVID-19 pandemic. Covid Economics, 62(18), 124-154.
[11]. Mooi-Reci, I., & Risman, B. J. (2021). The gendered impacts of COVID-19: Lessons and reflections. Gender & Society, 35(2), 161-167.
[12]. Milliken, F. J., Kneeland, M. K., & Flynn, E. (2020). Implications of the COVID‐19 pandemic for gender equity issues at work. Journal of Management Studies, 57(8), 1767–1772.
Cite this article
Ning,K. (2024). The Influence of Gender Disparities on the Unemployment Rate in the United States amid the Covid-19 Pandemic. Advances in Economics, Management and Political Sciences,57,268-275.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
Disclaimer/Publisher's Note
The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of EWA Publishing and/or the editor(s). EWA Publishing and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
About volume
Volume title: Proceedings of the 2nd International Conference on Financial Technology and Business Analysis
© 2024 by the author(s). Licensee EWA Publishing, Oxford, UK. This article is an open access article distributed under the terms and
conditions of the Creative Commons Attribution (CC BY) license. Authors who
publish this series agree to the following terms:
1. Authors retain copyright and grant the series right of first publication with the work simultaneously licensed under a Creative Commons
Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this
series.
2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the series's published
version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial
publication in this series.
3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and
during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See
Open access policy for details).