Abstract
Using a multinomial logit model with data from the Survey of Income and Program Participation, this paper tests whether the implementation of the Family and Medical Leave Act (FMLA) is associated with an increase in return to work at part-time status among first-time mothers working full-time during their pregnancy. I find a statistically significant trend of increasingly higher odds of returning to work at part-time status relative to return at full-time status, beginning in 1993 (the year in which the FMLA is implemented). Furthermore, an additional week of either state or federal leave is significantly associated with a higher odds of return at part-time status. This article provides evidence that job protection and leave legislation may help facilitate higher levels of labor force participation among women with small children, through more flexible work arrangements.
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In contrast, 15% would ideally work full-time, and 21% would prefer not to work at all. Note that no distinction is made between full- and part-time status for the response “working for pay from home.” (Erickson and Aird 2005).
For example, in 1992, 20% of employees at small firms (less than 100 employees) were covered by leave policy, while 63% of employees at medium to large firms (100 employees or more) were covered in 1993 (Waldfogel 1999).
Studies have shown high reliability of maternal recall of events such as infant birth weight and obstetric conditions, particularly around the first birth (Soua et al. 2006; Catov et al. 2006; Buka et al. 2004). However, there is a lack of research specific to the reliability of maternal recall of age of child at return to work. Research on the reliability of recall data on migration suggests that recall is more accurate when linked to life events such as the birth of a child (Smith and Thomas 2003).
Although the 1996 panel also includes births between 1990 and 1996, I exclude these from the analysis in order to (i) minimize sampling bias introduced by the use of several samples and (ii) not erroneously give more weight to births occurring during this period. I limit the births in the 2004 sample to those occurring through 2002 in order to allow enough time for women giving birth in 2002 to report return to work within one full year. The 2001 panel fertility history module also asks questions about employment surrounding first birth, but only for births going back to 1990; thus it provides no additional information beyond that gleamed from the 2004 panel, which includes more recent births as well.
The first 3 years of each decade are analyzed here merely to illustrate trends over time.
Henceforth, the term “pregnancy” in this paper refers to the pregnancy leading to the first birth.
Income is not observed in the year of first birth, but rather, at the time of the survey. Therefore, this variable is interpreted as a measure of labor market attachment in general, rather than the association between income itself and return to work. In separate analysis, this variable was excluded to see whether it was introducing bias to the other variables. The results for the FMLA were robust.
While potential experience is known to be an imperfect estimate of experience for women, it may be more accurate for women who have had no births, since they may arguably have had fewer spells out of the labor force.
Other household income is not observed in the year of first birth but rather, at the time of the survey. Therefore, this variable is only an approximation of other household income. However, results were robust to a model excluding this variable.
In order to determine eligibility, we would need information on firm size and number of hours worked at the firm in the year prior to the birth, data that are not collected in the SIPP survey instrument.
Calculated as e β, where β is the coefficient on the FMLA dummy from model 1(a).
Calculated as e β, where β is the coefficient on the dummy indicating state leave legislation in effect at the time of the birth, models 1(a)–(c).
It is interesting that the association of state leave is robust to the inclusion and exclusion of the FMLA dummy, as well to the exclusion of births occurring in the years prior to FMLA implementation, according to additional analysis not shown here. In addition, an interaction between the FMLA and the state law dummies was not significant, suggesting that the two do operate separately. This evidence would support the hypothesis that the effect of state leave law on part-time return has been similar to that of the FMLA. However, they do appear to act independently, so that having a state leave law encourages part-time return, and then the introduction of the FMLA further encourages part-time return.
State laws are coded as in effect in the year in which they take effect. States coded as having laws mandating leave include California (all sample years), Connecticut (from 1991), the District of Columbia (from 1991), Maine (from 1990, since Maine was not separately coded as a state in data for 1988 and 1989), Massachusetts (all sample years), Minnesota (from 1988), New Jersey (from 1990), Oregon (from 1988), Rhode Island (from 1988), Tennessee (from 1988), Vermont (from 1993), Washington (from 1990), and Wisconsin (from 1988). Covered firm size varies from 5 or more employees to 100 or more employees. States in which leave legislation was only mandated to state employees, including Alaska (enacted in 1993), Georgia (enacted in 1993), Hawaii (enacted in 1992), North Carolina (enacted in 1988), North Dakota (enacted in 1990), Oklahoma (enacted in 1989), are not coded as having state legislated leave for this analysis. In the 1996 panel, Vermont and Maine, which had differing state laws, were not uniquely coded. These cases were coded as zero in 1988 and 1989, in order to draw more conservative conclusions regarding the importance of state laws. Source for state leave legislation dates: Han and Waldfogel (2003).
That the coefficient loses significance in model 1(b) may suggest that the simple linear time trend is picking up some trend in the economy.
In analysis not shown, t 3 was also included, but its coefficient was not significant.
I employ the seqlogit command in Stata, written by Maarten Buis, Vrije Universiteit Amsterdamn (Buis 2007).
In the Netherlands, the labor force participation rate of women with a child under the age of 6 was 71% in 2002, of whom 79% were working part-time; in Sweden, 61% of these women were in the labor force, of whom 74% were working part-time (Organisation for Economic Co-operation and Development social indicators, series SS4.1 and SS4.2)
For women whose potential experience is 10 years or greater, the employment-to-population ratio lagged 10 years is coded; for women whose experience is negative or zero, the ratio in the year in which they gave birth is coded.
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Appendix
Appendix
There may be some concern that since I limit the sample to women who are working full-time during their pregnancy, I introduce sample selection bias to the estimates. To generalize about the potential impact of the FMLA on the entire population, it would be wise to take into account the ways in which women working full-time during their pregnancy may be a selected group of individuals. While statistical methods exist to control for such bias when the first stage regression includes a binomial or multinomial dependent variable and the second stage is a continuous dependent variable (Heckman 1979; Lee 1983), I know of no straightforward extension of such an approach to a multinomial dependent variable in the second stage.
As a second-best approach, I calculate the inverse Mills ratio using predicted probabilities from a first stage probit of labor force participation during pregnancy, and include this variable in the second stage multinomial logit regression. While the inverse Mills ratio will not have the same statistical characteristics in this equation, it may instead serve as a proxy for the extent to which selection may be an issue, and reveal the way in which our independent variables of interest may change. In this approach, the first stage equation is separately identified from the second stage equation by (i) the male employment-to-population lagged by the number of years of potential experience, Footnote 20 and (ii) a variable for being disabled prior to pregnancy (for first stage regression results, see Table 7) I use two specifications for the first stage regression: working at all during pregnancy versus not working, and working full-time during pregnancy versus not working. The specification for the second stage regression is identical to that in model 1(c), Table 4.
When selection is a concern, one would expect the coefficient on the inverse Mills ratio to be significant, and for the estimates of the independent variable of interest to be biased. In this case, the coefficient on the inverse Mills ratio is indeed significant, but the coefficient on the FMLA variable only increases slightly in magnitude. These results suggest that any sample selection bias may actually lead us to underestimate the importance of the FMLA (Table 7). Therefore, the estimates in the body of the paper are likely to constitute a conservative estimate of the true FMLA relationship with return to work.
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Schott, W. Going Back Part-time: Family Leave Legislation and Women’s Return to Work. Popul Res Policy Rev 31, 1–30 (2012). https://doi.org/10.1007/s11113-011-9221-6
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DOI: https://doi.org/10.1007/s11113-011-9221-6