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Research ArticleArticles
Open Access

Early Labor Market Prospects and Family Formation

View ORCID ProfileMattias Engdahl, Mathilde Godard and Oskar Nordström Skans
Journal of Human Resources, September 2024, 59 (5) 1564-1598; DOI: https://doi.org/10.3368/jhr.1220-11387R1
Mattias Engdahl
Mattias Engdahl is a researcher at the Institute for Evaluation of Labour Market and Education Policy (IFAU) in Uppsala, Sweden
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  • ORCID record for Mattias Engdahl
  • For correspondence: mattias.engdahl{at}ifau.uu.se
Mathilde Godard
Mathilde Godard is a CNRS researcher at Université Paris-Dauphine-PSL, LEDa in Paris, France
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Oskar Nordström Skans
Oskar Nordström Skans is a professor of economics at Uppsala University, Sweden
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  • Unemployment Rate (15–64), Sweden 1987–2013, OECD Notes: The shaded area shows the graduation years of the enrollment cohorts studied. The first enrollment cohort graduated in 1989 or 1990, depending on length of the vocational program, and the last cohort graduated in 1993 or 1994.
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    Figure 1

    Unemployment Rate (15–64), Sweden 1987–2013, OECD

    Notes: The shaded area shows the graduation years of the enrollment cohorts studied. The first enrollment cohort graduated in 1989 or 1990, depending on length of the vocational program, and the last cohort graduated in 1993 or 1994.

  • Effect of Unemployment Rate at Graduation on Labor Market Outcomes and Welfare Receipt for Each Year since (Predicted) Graduation—IV Specification
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    Figure 2

    Effect of Unemployment Rate at Graduation on Labor Market Outcomes and Welfare Receipt for Each Year since (Predicted) Graduation—IV Specification

  • Full‐Time Path of the Effect of Unemployment Rate at Graduation on Family Related Events—IV Specification, Bottom Quintile Notes: The estimates are unconditional; that is, females are included regardless of whether they ever formed a partnership, had a child, or dissolved a partnership.
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    Figure 3

    Full‐Time Path of the Effect of Unemployment Rate at Graduation on Family Related Events—IV Specification, Bottom Quintile

    Notes: The estimates are unconditional; that is, females are included regardless of whether they ever formed a partnership, had a child, or dissolved a partnership.

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    Table 1

    Summary Statistics for the Sample of Female Vocational Students

    AllLow GPAaHigh GPAa
    MeanSDMeanSDMeanSD
    Education
    Age enrolled in upp. sec.16.22(0.28)16.21(0.28)16.25(0.28)
    Age at predicted graduation from upp. sec.18.14(0.47)18.07(0.42)18.26(0.52)
    Age at observed graduation from upp. sec.18.22(0.60)18.20(0.66)18.30(0.58)
    Share dropouts0.12(0.32)0.27(0.44)0.05(0.22)
    Share late graduates0.05(0.22)0.08(0.26)0.03(0.18)
    Percentile ranked GPA 9th grade50.07(28.80)8.62(4.96)88.78(6.46)
    Graduated from a three‐year track0.17(0.38)0.11(0.31)0.25(0.43)
    Accumulated years of schooling by age 3812.62(2.02)11.62(1.57)13.69(2.13)
    Labor Market Outcomes at Graduationb
    Employment0.77(0.42)0.70(0.46)0.82(0.38)
    Annual earnings0.52(0.40)0.48(0.43)0.55(0.39)
    Family Formation and Fertility by Age 38
    Ever in a stable partnership0.85(0.36)0.83(0.38)0.87(0.34)
    Age at first stable partnership (if ever in one)26.69(4.67)25.62(4.91)27.23(4.40)
    Ever had a child0.87(0.34)0.85(0.35)0.88(0.32)
    Number of children at age 38 (if ever had a child)2.17(0.86)2.26(1.00)2.17(0.77)
    Age at birth of first child (if ever had a child)26.66(4.84)25.12(4.97)27.67(4.46)
    Partner’s Characteristics (At Age 27)c
    Partners with low GPAd0.48(0.50)0.62(0.49)0.36(0.48)
    Age difference−3.32(3.58)−3.38(3.86)−3.34(3.42)
    Share in same cohort0.13(0.33)0.13(0.33)0.13(0.33)
    Family dissolution by age 380.33(0.47)0.49(0.50)0.23(0.42)
    Ever Ended First Partnership (If Ever in One)
    Ever ended first partnership (if partner was low GPA)0.37(0.48)0.48(0.50)0.29(0.45)
    Ever ended first partnership (if partner was high GPA)0.27(0.44)0.39(0.49)0.20(0.40)
    Welfare receipt at age 380.03(0.16)0.07(0.25)0.01(0.08)
    Individuals78,59515,93016,079
    • Notes: The sample includes female vocational students observed in the year of (predicted) graduation, including dropouts.

    • ↵a Low (high) GPA students refer to students in the bottom (top) quintile of the GPA distribution in ninth grade.

    • ↵b We assume than an individual is employed (or to some extent active on the labor market) if her earnings in the current year are higher than the monthly full‐time minimum wage. Annual earnings are scaled as months of full‐time minimum wage (see Online Appendix B.1 for details).

    • ↵c “Partner” refers to a partner (husband or partner living with common child) whose characteristics are measured when the woman is 27 years old (which is the average age when women form their first stable partnership).

    • ↵d Partners with low GPA refer to partners whose grades in ninth grade are below the median of the GPA distribution.

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    Table 2

    Effect of Predicted Unemployment Rate at Graduation (ϕcj) and Pilot Intensity (Pcj) on High School Progression?

    Dependent Variable
    p(Enrolls in Upp. Sec. School)p(Enrolls in Voc. Track)p(Delays Enrollment in Voc. Track)p(Drops Out from Voc. Track)GPA Rank for Dropouts
    (1)(2)(3)(4)(5)
    Predicted unemployment rate at grad. (ϕcj)0.000−0.000−0.000−0.0010.257
    (0.002)(0.002)(0.001)(0.002)(0.600)
    Pilot intensity (Pcj)0.0010.0110.0050.014−7.326*
    (0.013)(0.016)(0.005)(0.017)(3.972)
    GPA rank in 9th grade0.004***−0.010***−0.000***−0.003***
    (0.000)(0.000)(0.000)(0.000)
    Born in Nordic country0.017***0.073***−0.132***−0.0023.307**
    (0.005)(0.005)(0.009)(0.007)(1.407)
    Cohort FE✓✓✓✓✓
    Municipality FE✓✓✓✓✓
    Mean of dep. variable0.860.380.020.1231.12
    Individuals255,471200,50278,64177,1928,946
    • Notes: Marginal effects are presented. Standard errors (in parentheses) are clustered at the municipality * cohort (j × c) level. Model 1 is estimated using the sample of students observed three years after graduation from compulsory school, including dropouts. Since not all students in compulsory school enrolled in upper secondary school, Pcj and ϕcj are measured at the municipality * cohort (j × c) level, where j stands for municipality of residence at age 16 (as information on the municipality of residence during the last year of compulsory schooling is only available from the upper secondary application register) and c stands for the year the individual finishes compulsory school. Models 2–5 are estimated using the sample of students observed in the year of (predicted) graduation, including dropouts. We estimate Model 2 conditional on enrolling in upper secondary school at age 16, Model 3 conditional on enrolling in vocational studies, Model 4 conditional on enrolling in vocational studies at age 16, and Model 5 conditional on enrolling in vocational studies at age 16 and dropping out. Unconditional estimations of Models 2–4 yield very similar results (not shown). Significance: *p < 0.10, **p < 0.05, ***p < 0.01.

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    Table 3

    Placebo Tests: The Impact of Predicted Unemployment Rate at Graduation Embedded Image on Pre‐Treatment Characteristics—Full Sample

    GPA in 9th GradeBorn in a Nordic CountryMother’s Years of SchoolingFather’s Years of SchoolingUnemp. at EnrollmentUnemp. at Enrollment +3 Years
    Predicted unemployment rate at graduation (ϕcj)0.0690.0010.0170.008−0.0110.000
    (0.197)(0.001)(0.014)(0.015)(0.012)(0.000)
    Individuals69,13069,13069,13069,13069,13069,130
    GPA in 9th grade✓✓✓✓✓
    Born in Nordic country✓✓✓✓✓
    Pilot intensity (Pcj)✓✓✓✓✓✓
    Cohort FE✓✓✓✓✓✓
    Municipality FE✓✓✓✓✓✓
    • Notes: Marginal effects are presented. Standard errors (in parentheses) are clustered at the municipality * cohort (j × c) level. Each model is estimated for vocational students observed in the year of (predicted) graduation. Significance: *p < 0.10, **p < 0.05, ***p < 0.01.

    • View popup
    Table 4

    Impact of Track Length (Two‐ versus Three‐Year Track), for High‐ and Low‐Unemployment‐Rate Municipalities Separately

    Dependent Variable: Employment
    High‐Unemployment‐Rate MunicipalitiesLow‐Unemployment‐Rate MunicipalitiesDiff.
    Years Since (Predicted) GraduationCoeff.Obs.Coeff.Obs.Coeff.Obs.
    (1)(2)(3)
    00.218***34,5920.332***33,6490.07668,241
    (0.099)(0.055)(0.086)
    5−0.01134,2060.06733,2690.04967,475
    (0.068)(0.044)(0.069)
    100.05333,8530.01732,991−0.09164,844
    (0.077)(0.044)(0.077)
    Track FE✓✓✓
    Cohort FE✓✓✓
    Municipality FE✓✓✓
    Individual characteristics✓✓✓
    • Notes: We define high‐ (low‐)‐unemployment‐rate municipalities as municipalities in which unemployment in 1994 (when the crisis was reaching its peak) was above (below) the median unemployment rate that year. Marginal effects are presented. In Model 3, we test for the equality of regression coefficients using the fully interacted form of the model. Standard errors (in parentheses) are clustered at the municipality * cohort (j × c) level. Significance: *p < 0.10, **p < 0.05, ***p < 0.01.

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    Table 5

    First‐Stage Regressions

    Dependent Variable
    Three‐Year Track Dummy (1)Unemployment Rate at Graduation (2)
    Predicted unemployment rate at graduation (ϕcj)0.0100.510***
    (0.007)(0.045)
    Pilot intensity in municipality of residence (Pcj)0.451***0.081
    (0.042)(0.145)
    Cohort FE✓✓
    Municipality FE✓✓
    Individual characteristics✓✓
    Individuals68,24168,241
    R20.200.89
    Kleibergen–Paap Wald rk F‐statistic67.8567.85
    • Notes: As we have two endogenous regressors and two IVs, we cannot simply look at the first‐stage F‐statistics to test for weak instruments. We look instead at the Kleibergen–Paap Wald rk F‐statistic (which is cluster‐robust). Here, the eigenvalue (for 10 percent maximal IV size) is equal to 7.03. We show first‐stage estimates for the sample of individuals in the year of (predicted) graduation (68,241 individuals). Marginal effects are presented. Standard errors (in parentheses) are clustered at the municipality * cohort (j × c) level. Significance: *p < 0.10, **p < 0.05, ***p < 0.01.

    • View popup
    Table 6

    Impact of Unemployment Rate at Graduation on Labor Market Outcomes in the Year of (Predicted) Graduation—IV Specification

    Dependent VariableFull Sample(1)Bottom Quintile(2)Median Quintile(3)Top Quintile(4)
    Employmenta
    Effect of unemployment rate at graduation−0.022**−0.053***−0.009−0.017
    (0.007)(0.015)(0.014)(0.013)
    Track‐length dummy0.279***0.450***0.236**0.213**
    (0.052)(0.097)(0.090)(0.087)
    Individuals68,24113,12713,23912,844
    Mean of dependent variable0.7760.6860.8180.827
    Annual Earningsb
    Effect of unemployment rate at graduation−0.026***−0.035***−0.010−0.032**
    (0.006)(0.010)(0.011)(0.010)
    Track‐length dummy0.353***0.364***0.285***0.345***
    (0.044)(0.086)(0.081)(0.069)
    Individuals68,24113,12713,23912,844
    Mean of dependent variable0.5010.4150.5460.552
    Track FE (instrumented)✓✓✓✓
    Cohort FE✓✓✓✓
    Municipality FE✓✓✓✓
    Individual characteristics✓✓✓✓
    • Notes: Marginal effects are presented. Standard errors (in parentheses) are clustered at the municipality * cohort (j × c) level. Each model is estimated using the sample of students present in the year of (predicted) graduation. Significance: *p < 0.10, **p < 0.05, ***p < 0.01.

    • ↵a We assume than an individual is employed (or to some extent active on the labor market) if her earnings in the current year exceed one month full‐time at the minimum wage (see Section III for details).

    • ↵b Annual earnings are scaled as months of full‐time minimum wage (see Section III for details).

    • View popup
    Table 7

    Impact of Unemployment Rate at Graduation on Educational Attainment—IV Specification

    Dependent VariableFull Sample (1)Bottom Quintile (2)Median Quintile (3)Top Quintile (4)
    Late Graduation from Upp. Sec. School
    Effect of unemployment rate at graduation0.0030.003−0.0030.004
    (0.003)(0.009)(0.007)(0.006)
    Individuals68,24113,12713,23912,844
    Mean of dependent variable0.0570.0990.0470.037
    Accumulated Years of Schooling by Age 38
    Effect of unemployment rate at graduation−0.030−0.077**−0.033−0.081
    (0.023)(0.038)(0.062)(0.056)
    Individuals66,29312,79712,83312,433
    Mean of dependent variable12.81112.02212.74113.817
    Track FE (instrumented)✓✓✓✓
    Cohort FE✓✓✓✓
    Municipality FE✓✓✓✓
    Individual characteristics✓✓✓✓
    • Notes: Marginal effects are presented. Standard errors (in parentheses) are clustered at the municipality * cohort (j × c) level. Each model is estimated using the sample of students present in the year of (predicted) graduation. Significance: *p < 0.10, **p < 0.05, ***p < 0.01.

    • View popup
    Table 8

    Impact of Unemployment Rate at Graduation on Family Formation—IV Specification

    Dependent VariableFull Sample (1)Bottom Quintile (2)Median Quintile (3)Top Quintile (4)
    Panel A: Conditions at Graduation
    Still living at parents’ home at age 19
     Effect of unemployment rate at graduation0.000−0.030*0.030*−0.016
    (0.007)(0.017)(0.016)(0.013)
     Individuals68,24113,12713,23912,844
     Mean of dependent variable0.6310.5780.6310.659
    Age at first partnershipa
     Effect of unemployment rate at graduation−0.074−0.390**0.0810.050
    (0.068)(0.172)(0.135)(0.112)
     Individuals57,74010,77711,20511,154
     Mean of dependent variable26.82526.04026.97327.163
    Age at first birth
     Effect of unemployment rate at graduation−0.090−0.395**0.055−0.004
    (0.064)(0.178)(0.140)(0.117)
     Individuals57,10310,75711,06010,926
     Mean of dependent variable26.98725.79427.09527.730
    Panel B: Completion of Family Formationb
    Ever in a partnership
     Effect of unemployment rate at graduation0.000−0.0060.0000.010
    (0.004)(0.012)(0.011)(0.008)
     Individuals66,33612,80012,85412,433
     Mean of dependent variable0.8700.8420.8720.897
    Ever had a child
     Effect of unemployment rate at graduation−0.002−0.001−0.0010.000
    (0.005)(0.012)(0.011)(0.009)
     Individuals66,33612,80012,85412,433
     Mean of dependent variable0.8610.8410.8610.880
    Total number of children (if ever had a child)
     Effect of unemployment rate at graduation0.022*0.0330.024−0.015
    (0.012)(0.035)(0.027)(0.023)
     Individuals57,03310,74611,04310,916
     Mean of dependent variable2.1492.1912.1162.173
    Track FE (instrumented)✓✓✓✓
    Cohort FE✓✓✓✓
    Municipality FE✓✓✓✓
    Individual characteristics✓✓✓✓
    • Notes: Marginal effects are presented. Standard errors (in parentheses) are clustered at the municipality * cohort (j × c) level. Each model (except the first model in Panel A) is estimated using the sample of women observed at age 38. Significance: *p < 0.10, **p < 0.05, ***p < 0.01.

    • ↵a A partnership is defined as either being married or cohabitation with a partner and common child.

    • ↵b Completed family formation refers to family outcomes at age 38.

    • View popup
    Table 9

    Impact of Unemployment Rate at Graduation on Partnership Quality and Dissolution—IV Specification

    Dependent VariableFull Sample (1)Bottom Quintile (2)Median Quintile (3)Top Quintile (4)
    Panel A: Partner’s Characteristicsa
    Partner’s GPAb
     Effect of (own) unemployment rate at graduation−0.005−0.050−0.020−0.013
    (0.013)(0.045)(0.032)(0.034)
     Individuals17,5213,1793,2393,561
     Mean of dependent variable2.9092.7252.9263.082
    Partner’s annual earnings
     Effect of (own) unemployment rate at graduation−0.025**−0.045*−0.022−0.042
    (0.011)(0.024)(0.027)(0.027)
     Individuals28,9315,4825,5765,656
     Mean of dependent variable1.1991.1331.2121.242
    Partner’s age
     Effect of (own) unemployment rate at graduation−0.0160.267−0.341*−0.005
    (0.076)(0.194)(0.188)(0.185)
     Individuals28,9315,4825,5765,656
     Mean of dependent variable30.26230.26830.24530.329
    Panel B: Partnership Dissolutionc
    Ended the first partnership (if ever in one)
     Effect of unemployment rate at graduation−0.0030.046**−0.006−0.001
    (0.006)(0.020)(0.015)(0.013)
     Individuals57,74010,77711,20511,154
     Mean of dependent variable0.3080.4320.2930.221
    Single mother
     Effect of unemployment rate−0.0000.037**0.004−0.008
      at graduation(0.006)(0.019)(0.012)(0.012)
     Individuals66,33612,80012,85412,433
     Mean of dependent var.0.2310.3220.2170.164
    Number of fathers (if ever had a child)
     Effect of unemployment rate   at graduation0.0100.047**0.030**0.010
    (0.006)(0.019)(0.013)(0.009)
     Individuals56,64510,63210,98310,863
     Mean of dependent variable1.1311.2231.1181.074
    Track FE (instrumented)✓✓✓✓
    Cohort FE✓✓✓✓
    Municipality FE✓✓✓✓
    Individual characteristics✓✓✓✓
    • Notes: Marginal effects are presented. Standard errors (in parentheses) are clustered at the municipality * cohort (j × c) level. Significance: *p < 0.10, **p < 0.05, ***p < 0.01.

    • ↵a We measure partners’ characteristics (if in partnership) when females are 27.

    • ↵b Partners’ GPA refer to grades in ninth grade. Sample is reduced since we do not have GPA for all partners.

    • ↵c Partnership dissolution is measured by the age of 38. Each model in Panel B is estimated using the sample of women observed at age 38.

    • View popup
    Table 10

    Impact of Unemployment Rate at Graduation on Welfare Receipt and Related Joint Events, Bottom Quintile—IV Specification

    Dependent Variable (Measured at Age 38)Bottom Quintile
    Welfare receipt
     Effect of unemployment rate at graduation0.019**
    (0.007)
     Mean of dependent variable0.043
     Individuals12,800
    Welfare receipt * No child
     Effect of unemployment rate at graduation0.000
    (0.005)
     Mean of dependent variable0.008
     Individuals12,800
    Welfare receipt * In partnership with child
     Effect of unemployment rate at graduation0.003
    (0.003)
     Mean of dependent variable0.009
     Individuals12,800
     Welfare receipt * Single mother
     Effect of unemployment rate at graduation0.017**
    (0.006)
     Mean of dependent variable0.026
     Individuals12,800
    Welfare receipt * First partner had high GPAa
     Effect of unemployment rate at graduation−0.003
    (0.002)
     Mean of dependent variable0.004
     Individuals9,500
    Welfare receipt * First partner had low GPAa
     Effect of unemployment rate at graduation0.011**
    (0.005)
     Mean of dependent variable0.0148
     Individuals9,500
    Welfare receipt * First partner had high earningsa
     Effect of unemployment rate at graduation0.001
    (0.002)
     Mean of dependent variable0.004
     Individuals12,800
    Welfare receipt * First partner had low earningsa
     Effect of unemployment rate at graduation0.015***
    (0.006)
     Mean of dependent variable0.028
     Individuals12,800
    Track FE (instrumented)✓
    Cohort FE✓
    Municipality FE✓
    Individual characteristics✓
    • Notes: Marginal effects are presented. Standard errors (in parentheses) are clustered at the municipality * cohort (j × c) level. Each model is estimated using the sample of women observed at age 38. Significance: *p < 0.10, **p < 0.05, ***p < 0.01.

    • ↵a First partners with low/high GPA refer to first partners whose grades in ninth grade were below/above the median GPA. First partners with low/high earnings refer to partners whose earnings were below/above median earnings (measured when their female partner was 27).

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Journal of Human Resources: 59 (5)
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Early Labor Market Prospects and Family Formation
Mattias Engdahl, Mathilde Godard, Oskar Nordström Skans
Journal of Human Resources Sep 2024, 59 (5) 1564-1598; DOI: 10.3368/jhr.1220-11387R1

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Early Labor Market Prospects and Family Formation
Mattias Engdahl, Mathilde Godard, Oskar Nordström Skans
Journal of Human Resources Sep 2024, 59 (5) 1564-1598; DOI: 10.3368/jhr.1220-11387R1
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  • Article
    • Abstract
    • I. Introduction
    • II. Economic Environment and Institutions
    • III. Data
    • IV. Empirical Strategy
    • V. Results
    • VI. Discussion
    • VII. Conclusion
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