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Community-Wide Job Loss and Teenage Fertility: Evidence From North Carolina

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Demography

Abstract

Using North Carolina data for the period 1990–2010, we estimate the effects of economic downturns on the birthrates of 15- to 19-year-olds, using county-level business closings and layoffs as a plausibly exogenous source of variation in the strength of the local economy. We find little effect of job losses on the white teen birthrate. For black teens, however, job losses to 1 % of the working-age population decrease the birthrate by around 2 %. Birth declines start five months after the job loss and then last for more than one year. Linking the timing of job losses and conceptions suggests that black teen births decline because of increased terminations and perhaps also because of changes in prepregnancy behaviors. National data on risk behaviors also provide evidence that black teens reduce sexual activity and increase contraception use in response to job losses. Job losses seven to nine months after conception do not affect teen birthrates, indicating that teens do not anticipate job losses and lending confidence that job losses are “shocks” that can be viewed as quasi-experimental variation. We also find evidence that relatively advantaged black teens disproportionately abort after job losses, implying that the average child born to a black teen in the wake of job loss is relatively more disadvantaged.

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Notes

  1. In the early years of the sample, the Latino population in North Carolina was too small to provide stable county-level measures of teen birthrates. Throughout the article, the terms “white” and “black” are used to refer to non-Hispanic members of those racial groups.

  2. In July 2010, North Carolina instituted a new birth certificate form, with changes in the type and measurement of outcomes, and post-June data are not comparable to pre-June data.

  3. We considered three sources of time-varying measures of county population: decennial census data with linear interpolation used for intercensus years (estimates from the North Carolina Governor’s Office, and Surveillance Epidemiology and End Results estimates from the National Cancer Institute). Each source provided data that correlated above .99 with each other source, and estimates were robust to using any source.

  4. When separate measures for job losses in each of a series of three-month intervals preceding the conception are included in a model, effects for one to three, four to six, and seven to nine months are significant and of similar magnitude, while effects more than nine months prior to conception are small and insignificant; results are presented in Table 8 in the Appendix. For efficiency, we combine job losses for one to nine months into a single measure and do not include job losses for earlier periods in our main specification.

  5. Attempts were made to analyze micro-level North Carolina abortion data; however, these data were missing important demographic indicators in such a high percentage of cases as to render the data unusable. Nationally, both black and white teens have significant abortion rates (Jones et al. 2010).

  6. Authors’ calculations, using data obtained from the U.S. Bureau of Labor Statistics (retrieved from http://data.bls.gov).

  7. In other specifications, we considered whether job loss was nonlinearly related to teen fertility by squaring job loss, by logging job loss, and by dividing our continuous measure of job loss into dichotomous categories (e.g., no job loss, .01 to 1 % job loss). We also considered specifications in which the effect of job loss varied by the level of preexisting unemployment. We found little evidence supporting a nonlinear model of the relationship between job losses and teen fertility, or that the effect of job loss varied by levels of preexisting unemployment.

  8. These analyses can be conducted only with Surveillance, Epidemiology and End Results (SEER) data, because SEER measures vary nonlinearly within decade, population group, and county. Monthly population counts of teenagers are not available. In other work (Ananat et al. 2011), we estimated the effect of job losses last year on this year’s county public school enrollment for various grades and found no relationship; because those data represent actual counts rather than population estimates, they provide a stronger additional falsification test and lend confidence that endogenous migration is not occurring.

  9. Other measures of disadvantage, such as whether the mother used Medicaid to pay for the birth, are not available until December 2010.

  10. “Mass” is defined as 50 or more workers. BLS does not collect data on layoffs or closings affecting fewer than 50 workers.

  11. We are unable to measure outcomes as logged population shares as in Eq. (2) because of the YRBS’s complex survey design. Therefore, we estimate Eq. (3) as a linear probability model.

  12. The technique used to combine the two measures of job loss available at the state level, separations and total initial claimants (see Table 1), are described in Ananat et al. (2013).

  13. State-level estimates of effects of job losses on black and white teen fertility are consistent with our North Carolina estimates. However, because job loss data for other states are provided only quarterly, it is not possible to estimate our models using state-level data.

  14. The miscarriage rate for women is estimated to range from 11 to 12 miscarriages per 1,000 pregnancies (Knudsen et al. 1991; Regan et al. 1989; Warburton and Fraser 1964). Assuming a miscarriage rate of 12 %, then the implied pregnancy rate is 84.2 (based on a birthrate of 74.1 births per 1,000 women and pregnancy rate of 74.1 / (100 – .12), or 84.2 %). A miscarriage rate of 12 % would thus translate into 10.1 losses per 1,000 black teens (82.6 – 74.1); for miscarriage rate of 11 %, 9.2 losses would be found. The observed decrease of more than two births for this group, if caused by increased miscarriage, implies more than a 20 % increase in the miscarriage rate due to job loss.

  15. Immediate changes in funding for community services, however, are unlikely to be responsible for the decrease in teen fertility because effects occur too quickly after job losses to be driven by government or nonprofit funding cycles.

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Acknowledgments

The authors thank Eric Bannister, Dania Francis, Matthew Panhans, and Megan Reynolds for their outstanding research assistance. They gratefully acknowledge the support of the Smith Richardson Foundation; Ananat and Gibson-Davis gratefully acknowledge the support of the William T. Grant Foundation; and Gassman-Pines gratefully acknowledges the support of Foundation for Child Development. Helpful feedback on this article was provided by seminar participants at the University of California–Davis Economics Department; meeting participants at the Population Association of America; and members of the Beyond Test Scores research team at Duke University, especially Charlie Clotfelter, Phil Cook, Ken Dodge, Helen Ladd, and Jake Vigdor.

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  1. Sanford School of Public Policy, Duke University, Box 90312, Durham, NC, 27708, USA

    Elizabeth Oltmans Ananat, Anna Gassman-Pines & Christina Gibson-Davis

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  1. Elizabeth Oltmans Ananat
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  2. Anna Gassman-Pines
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Correspondence to Elizabeth Oltmans Ananat.

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Appendix

Appendix

Table 8 Regressions of birthrates on job loss, women aged 15–19, by race: 1991–2010
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Ananat, E.O., Gassman-Pines, A. & Gibson-Davis, C. Community-Wide Job Loss and Teenage Fertility: Evidence From North Carolina. Demography 50, 2151–2171 (2013). https://doi.org/10.1007/s13524-013-0231-3

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