PUAD 5003: RESEARCH AND ANALYTICAL METHODS | DR. SERENA KIM | UNIVERSITY OF COLORADO DENVER | DECEMBER 2020 I N T R O DUC T I O N Women play a crucial role in the workforce by adding diversity, empathy, and creativity that is otherwise lacking. Strides have been made in last couple of decades to increase the number of females participating in the U.S. workforce. However, current trends are showing working women professionals are leaving the workforce for a variety of reasons. This project reviews areas such as workplace flexibility, demands to work extra hours, lack of adequate and affordable childcare, sexual discrimination, income gaps, and perceptions about female participation in the workplace to determine why women choose to participate or not in the workplace. The impact of COVID 19 can be seen in Bureau of Labor Statistics showing a decline in female participation in the U.S. workforce since March of 2020 ( Carrazana , 2020). According to recent literature published by McKinsey & Company and Lean In new demands on women as a result of COVID 19 like fear of layoffs, lack of adequate childcare, and being in work mode for too many hours is having an impact on female participation in the workforce (Thomas, et. al., 2020). The cost of recruiting new hires is typically more than the cost of implementing programs that support female employees (Williams, 2020). On a larger scale, decreases in the female workforce are shown to negatively affect the economy (Maurer & Qureshi, 2019). This information should be used by the private and public sectors to establish programs to support and thus retain female workers. DATA & M E T H O DS Data form the U.S. Bureau of Labor Statistics was used to determine unemployment rates for males and females in December 2019 and October 2020. Data from the 2018 GSS was used to determine work experiences of males and females, see table 1. The data was analyzed through the linear regression model using STATA. A review of six data sets occurred to determine if women experience work differently than men. These data sets included responses to survey questions on work arrangements at the respondents main job, if the respondent is required to work extra hours, days per month the respondent worked extra hours, how often the respondent found work stressful, if the respondent feels discrimination because of gender, and if the respondent feels it is better for a man to work and a woman tend home . REFERENCES 1. Carrazana The 19 th . https://19thnews.org/2020/08/americas first female recession/ 2. Maurer , C. & Qureshi, I. (2019). Not just good for her: a temporal analysis of the dynamic relationship between representation of women and collective employee turnover. Organization Studies, 1 23. https://journals sagepub com.aurarialibrary.idm.oclc.org/doi/10.1177/0170840619875480 3. The General Social Survey. (2018). GSS Data Explorer. https://gss.norc.org/Get The Data 4. Thomas , R., Cooper, M., Cardazone , G., Urban, K., Bohrer , A., Long, M., Yee, L., Krivkovich , A., Huang, J., Prince, S., Kumar, A., & Coury , S. (2020). Women in the McKinsey & Company and Lean In . https://wiw report.s3.amazonaws.com/Women_in_the_Workplace_2020.pdf 5. U.S . Bureau of Labor Statistics. (2020, October ). Employment Situation Summary. https://www.bls.gov/news.release/pdf/empsit.pdf 6. U.S . Bureau of Labor Statistics. (2019, December ). Employment Situation Summary. https://www.bls.gov/news.release/archives/empsit_01102020.pdf 7. Williams making sure they can stay in the workforce. Public Management , 102(9). https:// go gale com.aurarialibrary.idm.oclc.org/ps/i.do?p=ITOF&u=auraria_main&id=GALE|A63 7863590&v=2.1&it=r&sid=summon ANALYZING FEMALE PARTICIPATION IN THE U.S. WORKFORCE THE IMPACT OF OUTSIDE FACTORS ON GENDER PARTICIPATION IN THE WORKFORCE Katie Gloystein PROBLEM/RESEARCH QUESTION Female participation in the U.S. workforce steadily rose 2019. This participation has declined through 2020. What factors impact female participation in the U.S. workforce? Is there a difference between female participation and male participation in the U.S. workforce ? HYPOTHESES Null: there is no difference in how males and females participate in the workforce. H 1 : there is a statistically significant difference in the factors that influence participation rates of males and females in the U.S. workforce. H 2 : females are more likely to not participate in the workforce for a variety of factors . CONTACT Katie Gloystein Master of Public Administration Candidate University of Colorado Denver School of Public Affairs Katie.Gloystein@ucdenver.edu BUREAU OF LABOR STATISTICS DATA December 2019, 74,584,000 women over 20 were employed compared to 84,008,000 men over 20 December 2019, the unemployment rate for women over 20 was 3.2 percent and was 3.5 percent for men over 20 October 2020, 72,330,000 women over 20 were employed compared to 82,562,000 men over 20 October 2020, the unemployment rate for women over 20 was 6.5 percent and was 6.7 percent for men over 20 CONCLUSION It is concluded that there is limited statistical differences between factors that impact different gendered employees desire to participate in the U.S. workforce. While some factors seem to impact females at a statistically different level than males, many of the factors reviewed had no statistically significant difference between the two genders. The data used for this analysis was from the 2018 GSS survey. Recent literature indicates that the factors analyzed may have more of an impact on females during the COVID 19 pandemic. Further research should be conducted to determine if this is an accurate hypothesis. The linear regression analysis indicated that the genders are impacted in statistically significant ways by gender discrimination and perceptions up research in this area could assist with better understanding the impact of gender discrimination and perceptions about working mothers. The analysis could provide insight into the sources of discrimination and gender participation in the workforce. ANALYSIS The linear regression analysis results are displayed in Table 2. These results indicate a negative correlation between gender and work schedules and gender and being overworked. A positive correlation is shown between gender and assistance for childcare, gender discrimination, income differentials, and perceptions that a mother working hurts children . ANALYSIS (Continued) The results demonstrate that factors that impact the genders in statistically significant ways are gender discrimination and The correlations between gender and work schedule, overworking, assistance for childcare, and income differentials are not statistically significant . Figure 1 highlights the differences in male response rates versus female response rates on the fechld variable. This is the most statistically significant variable demonstrating a perceived difference is workplace participation between the two genders. The results from the linear regression analysis provide mixed support for rejecting the null hypothesis. H 1 is partially supported showing a statistically significant difference in some but not all of the variables. Data from the Bureau of Labor Statistics contradicts H 2. Rates of participation in the workforce are consistent over time for females and males.