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Do American mothers use self-employment as a flexible work alternative?

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Abstract

This paper provides evidence that self-employment is a quantitatively important work alternative that American mothers use to gain workplace flexibility. First, I use panel data from the Survey of Income and Program Participation (SIPP) to show that self-employment rates are higher when women have young children at home in a pattern that has remained largely unchanged over the previous three decades. I estimate that women whose youngest child is two years old have 14% higher predicted self-employment rates due to the birth of that child. Second, I show that self-employed women appear to have more flexibility in their work location, hours, and schedule than wage and salary employed women using data from the American Time Use Survey. I find that mothers with young children use self-employment to spend an additional two hours per day with their children. My results suggest that mothers use self-employment to gain more control over their work environment allowing them to better manage their household responsibilities while working. These findings contribute to the ongoing discussion on the importance of family friendly work policies and the rise of alternative work arrangements.

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Notes

  1. These papers study highly educated, high earning individuals. Bertrand et al. (2010) focuses on MBAs, Goldin (2014) studies the 40 highest earnings occupations, and Guvenen et al. (2014) study the top 1% of earners. For these women their prime childbearing ages are between 30 and 35.

  2. Self-employment rates are usually defined as the percent of the labor force who are self-employed. The figures reported in this section use that definition. In my empirical analysis, I do not condition on employment and instead focus on the fraction of the population who are self-employed.

  3. These are average differences between male and female self-employment. As Fairlie and Robb (2009) point out, after controlling for many differences between male and female owned businesses, they do not find that female owned businesses are less successful.

  4. The SIPP adds individuals to the survey if they move into a surveyed household.

  5. See Karoly and Zissimopoulos (2004) for evidence on self-employment as partial retirement.

  6. Further detail on the relevant SIPP questions can be found in Appendix B.

  7. This means that “mothers” in my sample only include women whose children live with them.

  8. Technically, these are not the correct weights to use because they overweight individuals who are similar to those who leave the sample. Other authors have used the monthly weights from the first period of observation, but these would overweight individuals who have similar characteristics to those who remain in the sample. See Lavelle and Smock (2012) for an example of a paper using the baseline monthly weights and Kim (2017) and Byker (2016) for examples that use the final monthly weights.

  9. Further information about the ATUS questionnaire can be found in Appendix B.

  10. Generally childcare is a subset of supervision, however, there are categories of childcare including waiting to pick up children, attending school conferences, and organizing and planning for children that would not be included in supervision time. Additionally, childcare activities for children over the age of 13 would not be included in supervision time.

  11. Leisure does not include religious activities, volunteering, or any type of shopping.

  12. The model predicted self-employment rate for individual i, in month j, in year t uses the estimated coefficients including the individual’s fixed effect to estimate a propensity for self-employment for each observation. Then I use the average predicted rate among observations of women with no children under 18.

  13. The counterfactual self-employment rate is predicted for observations whose youngest child is two years of age according to the estimated model using the age of the woman’s next youngest child and is adjusted for having one fewer child.

  14. Married women without children under 18 may differ in age, education and other observed characteristics that could contribute to their predicted self-employment rate, which I use as the base in the first measure.

  15. This definition is not the same as labor force participation because I exclude unemployed women looking for work during the previous month from my working definition.

  16. Appendix Table 9 reports the regression results.

  17. The same figure predicting wage and salary employment looks very similar to the overall working figure, with big declines among women with young children.

  18. These results are available from the author upon request.

  19. For example, Broussard et al. (2015) argue that the self-employed have more children to have an heir for the family business, which could drive a positive relationship between fertility and self-employment.

  20. A recent article from The Council of Economic Advisors (2014) reports that 55% of women with a bachelor’s degree or higher have access to some schedule flexibility compared to 38% of women with less than a high school education.

  21. A little over 15% were self-employed at some during the prior six months, but a majority of them were wage and salary employed in their main job between self-employment spells.

  22. A little over 16% were self-employed at some during the next six months, but a majority of them were wage and salary employed in their main job between self-employment spells.

  23. There are around 2000 transitions into and out of self-employment over the panel time-frame.

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Acknowledgements

This work was started as part of my dissertation at the University of Michigan. I would like to thank Jeff Smith, Kevin Stange, Martha Bailey, and Brian McCall for their mentorship and advice. I am grateful to Austin Davis, Gaurav Khanna, Gretchen Lay, and Katherine Michelmore who have provided countless helpful comments. Any errors are my own.

Funding

This project was started when the author was a graduate student at the University of Michigan with support from the University for tuition and stipend.

Author information

Authors and Affiliations

  1. Office of Tax Analysis, U.S. Department of the Treasury, 1500 Pennsylvania Ave NW, Washington, DC, 20220, USA

    Katherine Lim

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  1. Katherine Lim
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Correspondence to Katherine Lim.

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Appendices

A Appendix

Tables 8–11, Figs. 5–13

Table 8 Top occupations among self-employed women over time
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Table 9 Employment propensity
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Table 10 Multinomial model of non-employment, self-employment, and wage and salary employment
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Table 11 Differences in time use associated with self-employment excluding childcare workers
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Fig. 5
figure 5

Female self-employment rates and the age of the youngest child; alternative weights; pooled panels. Notes: The three lines plot the coefficients on the age of the youngest child from regressions of the pooled surveys using no weights, the longitudinal panel weights and the final month of observation weights. The regressions predict self-employment status controlling for age, marital status, number of children, and fixed effects with standard errors clustered at the individual level. The markers denote statistical significance at the 5% level. The estimation sample includes women ages 18–55 who are present in the first wave of each SIPP panel

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Fig. 6
figure 6

Female self-employment rates and the age of the youngest child; final panel weights. Notes: The three lines plot the coefficients on the age of the youngest child from regressions using different SIPP panels. The regressions predict self-employment status controlling for age, marital status, number of children, and fixed effects with standard errors clustered at the individual level. The markers denote statistical significance at the 5% level. The estimation sample includes women ages 18–55 who are present in the first wave of each SIPP panel who are observed during every month of the survey. Observations are weighted using the final panel weight for the individual

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Fig. 7
figure 7

Female self-employment rates and the age of the youngest child; unweighted. Notes: The three lines plot the coefficients on the age of the youngest child from regressions using different SIPP panels. The regressions predict self-employment status controlling for age, marital status, number of children, and fixed effects with standard errors clustered at the individual level. The markers denote statistical significance at the 5% level. The estimation sample includes women ages 18–55 who are present in the first wave of each SIPP panel. Observations are unweighted

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Fig. 8
figure 8

Female self-employment rates and the age of the youngest child; by education level. Notes: The two lines plot the coefficients on the age of the youngest child from regressions on the sample of women with at least a bachelor’s degree and women without a bachelor’s degree. The regressions predict self-employment status controlling for age, marital status, number of children, and fixed effects with standard errors clustered at the individual level. The markers denote statistical significance at the 5% level. The estimation sample pools SIPP panels together and includes women ages 18–55 who are present in the first wave of a SIPP panel. Observations are weighted using the monthly weight from the individual’s final month of the survey

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Fig. 9
figure 9

Female self-employment rates and the age of the youngest child; by marital status. Notes: The two lines plot the coefficients on the age of the youngest child from regressions on the sample of women who are married throughout the entire survey and women who are single throughout the entire survey. The regressions predict self-employment status controlling for age, marital status, number of children, and fixed effects with standard errors clustered at the individual level. The markers denote statistical significance at the 5% level. The estimation sample pools SIPP panels together and includes women ages 18–55 who are present in the first wave of a SIPP panel. Observations are weighted using the monthly weight from the individual’s final month of the survey

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Fig. 10
figure 10

Broad occupation transitions; all mothers transitioning to self-employment. Notes: Occupations on the left are from the most recent wage and salary employment in the previous six months. Occupations on the right are the most common 2 digit self-employment occupations. The sample includes women ages 18–55 present in the first wave of the 2008 SIPP panel who become self-employed while they have a child under 18

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Fig. 11
figure 11

Broad occupation transitions; all mothers transitioning from self-employment. Notes: Occupations on the left are the most common pre-transition 2 digit self-employment occupations. Occupations on the right come from the first wage and salary employment in the following six months. The sample includes women ages 18–55 present in the first wave of the 2008 SIPP panel who become self-employed while they have a child under 18

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Fig. 12
figure 12

Joint distribution of hours worked and hours spent supervising children; wage and salary employed women. Notes: The sample includes wage and salary employed mothers of children under 13 years of age who are 18–55 years in age from the ATUS 2003–2016. The sample is limited to mothers who spent positive minutes supervising children and working

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Fig. 13
figure 13

Joint distribution of hours worked and hours spent supervising children; self-employed women. Notes: The sample includes self-employed mothers of children under 13 years of age who are 18–55 years in age from the ATUS 2003–2016. The sample is limited to mothers who spent positive minutes supervising children and working

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B Appendix

B.1 SIPP questionnaire text

Respondents who state that they have a self-employed job are then asked questions about their business. The self-employment definition in this paper depends on an individual having a self-employed job and working more hours at that job than any wage and salary position.

1984–1986

  1. 1.

    You said … worked during the 4-month period. Was … working for an employer or was… self-employed? (Include unpaid worker in family business or farm as working for an employer.)

    1. (1)

      Worked for employer only

    2. (2)

      Self-employed only

    3. (3)

      Both worked for employer and self-employed

  2. 2.

    How many hours per week did … usually work at this business

    1. (1)

      Hours

    2. (2)

      None

    3. (3)

      DK

1996

  1. 1.

    Was that for an employer or was [FIRST NAME] [LAST NAME] self-employed or did he/she have some other arrangement? (INTERVIEWER NOTE: Other arrangements include odd jobs, on-call work, day labor, one-time jobs, and informal arrangements like babysitting, lawn mowing, or leaf raking for neighbors.)

    1. (1)

      Employer

    2. (2)

      Self-employed

    3. (3)

      Both employer and self-employed

    4. (4)

      Some other arrangement

    5. (5)

      Not sure or don’t know

During the weeks [FIRST NAME] [LAST NAME] worked between [MONTH1] 1st and the end of [MONTH4], how many hours per week did [FIRST NAME] [LAST NAME] usually work AT ALL ACTIVITIES for [BUSINESS NAME]?

2008

  1. 1.

    Was that for an employer or [fill WASWERE] [fill TEMPNAME] self-employed or did [fill HESHE] have some other arrangement? OTHER ARRANGEMENTS INCLUDE ODD JOBS, ON-CALL WORK, DAY LABOR, ONE-TIME JOBS, AND INFORMAL ARRANGEMENTS LIKE BABYSITTING, LAWN MOWING, OR LEAF RAKING FOR NEIGHBORS.

    1. (1)

      Employer

    2. (2)

      Self-employed

    3. (3)

      Both employer and self-employed

    4. (4)

      Some other arrangement

  2. 2.

    How many hours per week did [fill HESHE] usually work AT ALL ACTIVITIES for [fill ALLBUS]?

    1. (1)

      ENTER (V) IF HOURS VARY

B.2 ATUS questionnaire text

Self-employment in this analysis is based on the individual’s main job (job that they work the most hours at). I also use information in the survey about usual hours worked at the job and actual minutes worked based on time diaries.

  1. 1.

    Are you employed by government, by a private company, a non-profit organization or are you self-employed [or working in a family business]?

    1. (1)

      Government

    2. (2)

      Private for-profit company

    3. (3)

      Non-profit organization

    4. (4)

      Self-employed

    5. (5)

      Working in family business

    6. (6)

      Don’t know, refused

  2. 2.

    How many hours per week do you USUALLY work at your [main] job?

    *By main job we mean the one at which you usually work the most hours.

    *Please enter Hours or Enter V if Hours Vary

    1. (1)

      0–99 h

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Lim, K. Do American mothers use self-employment as a flexible work alternative?. Rev Econ Household 17, 805–842 (2019). https://doi.org/10.1007/s11150-018-9426-0

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