Statistical discrimination offers a compelling story to understand gender wage gaps, at least during the early stages of the career. Employers believe that women will get pregnant with a positive probability, which leads to potential losses, eg. costs associated with finding substitutes, potential losses in customers, etc. Employers then have an incentive to offer women lower wages, in order to discount for future losses. If that is the case, lower and delayed fertility should imply lower discount in wages, and consequently reductions in the gender pay gap among entrants. In order to test for this hypothesis, we collect individual level data from European countries dating back to the early 1990. Having compiled these data, we compute the adjusted gender wage gap for workers at the early stages of their career, that is for those aged 25 to 29. These adjuste differences are obtained using the non-parametric approach pioneered by Nopo. We then regress these measures on macro data on fertility changes. If the statistical discrimination hypothesis is correct, we should expect that the secular decline in fertility observed in Europe over the last 30 years is correlated with lower estimates of the gender wage gap. Our estimates suggest that this is indeed the case. Using the age at first birth as a proxy for fertility, we find that postponing childbirth by an additional year leads to a reduction of .18 in the adjusted gap. One caveat with this result is that fertility can be endogeneous to wages. If women were to receive higher wages, they might choose to postpone childbirths. To address this issue, we instrument our measure of fertility with the number of years since the introduction of the pill in the country. This measures varies across countries and over time, while at the same time it is fairly exogeneous, as the introduction of the pill occurred several generations back, normally in the mid-60 and 70s. First stage regressions reveal that the instrument correlates well with mean age at first birth. Second stage estimates are still significant, though they are smaller in magnitude. We conclude that recent changes in fertility helped to reduce the gender wage gap among women entering to the labor market.

1. Can I have my kids now?
Can I have my kids now?
Fertility and gender wage gaps
Nuria Rodriguez-Planas [CUNY & IZA]
Joanna Tyrowicz [FAME|GRAPE, IAAEU, IZA & University of Warsaw]
Lucas van der Velde [FAME|GRAPE & Warsaw School of Economics]
Prague Workshop on Gender and Family in the Labor Market
May 2019

2. Can I have my kids now?
Introduction
Motivation – textbook case for statistical discrimination
Fertility (-related absences) as premise for gender inequality
fertility plans → hiring decisions
(Becker et al., 2019)
child bearing → wage loss among mothers (not fathers)
(Landais & Kleven, 2019; Cukrowska-Torzewska & Matysiak, 2017; Pertold-Gebicka, 2014)

3. Can I have my kids now?
Introduction
Motivation – textbook case for statistical discrimination
Fertility (-related absences) as premise for gender inequality
fertility plans → hiring decisions
(Becker et al., 2019)
child bearing → wage loss among mothers (not fathers)
(Landais & Kleven, 2019; Cukrowska-Torzewska & Matysiak, 2017; Pertold-Gebicka, 2014)
Demographic trends: ↑ age at first birth and ↓ # of births
⇒ less reasons for statistical discrimination

4. Can I have my kids now?
Introduction
Motivation – textbook case for statistical discrimination
Fertility (-related absences) as premise for gender inequality
fertility plans → hiring decisions
(Becker et al., 2019)
child bearing → wage loss among mothers (not fathers)
(Landais & Kleven, 2019; Cukrowska-Torzewska & Matysiak, 2017; Pertold-Gebicka, 2014)
Demographic trends: ↑ age at first birth and ↓ # of births
⇒ less reasons for statistical discrimination
Why look at entrants?
most of the “action”
entry wage as benchmark for raises → future earnings
(Blau and Ferber, 2011; Reuben et al., 2013)

5. Can I have my kids now?
Introduction
Our contribution
Test the link from fertility to (adjusted) gender wage gaps

6. Can I have my kids now?
Introduction
Our contribution
Test the link from fertility to (adjusted) gender wage gaps
Causal evidence
New IV: international variation in “pill” admission
(in the US: Goldin & Katz, 2002; Bailey, 2006; Oltmans-Ananat & Hungerman, 2012)
Link between “pill” and fertility is causal
(Bailey, 2009)

7. Can I have my kids now?
Introduction
Our contribution
Test the link from fertility to (adjusted) gender wage gaps
Causal evidence
New IV: international variation in “pill” admission
(in the US: Goldin & Katz, 2002; Bailey, 2006; Oltmans-Ananat & Hungerman, 2012)
Link between “pill” and fertility is causal
(Bailey, 2009)
Earlier studies: directly affected cohorts ↔ this study: current cohort

8. Can I have my kids now?
Introduction
Our contribution
Test the link from fertility to (adjusted) gender wage gaps
Causal evidence
New IV: international variation in “pill” admission
(in the US: Goldin & Katz, 2002; Bailey, 2006; Oltmans-Ananat & Hungerman, 2012)
Link between “pill” and fertility is causal
(Bailey, 2009)
Earlier studies: directly affected cohorts ↔ this study: current cohort
Comparable measures of AGWG (across c & t) for entrants
Study time trends in GWG and AGWG across countries
Document substantial heterogeneity in trends

9. Can I have my kids now?
Introduction
Table of contents
1 Introduction
2 Toy model
3 Method and data
4 Results
5 Summary
6 Appendix

10. Can I have my kids now?
Toy model
A toy model of statistical discrimination
Variation of the ideas presented by Phelps (1972)
Set up
Two types of workers: parents (π ) and non-parents (1 − π)
Same productivity h , but there are costs (c) associated with
parenthood
c is borne mostly by women.
Employer cannot know whether a worker is (will be) a parent
Wages reflect the expected productivity
W = E(h) = h ∗ (1 − π) + (h − c) ∗ (π)

11. Can I have my kids now?
Toy model
A toy model of statistical discrimination (II)
The Adjusted GWG is then:
E(Wm|h) − E(Ww |h)) = h − (h ∗ (1 − π) + (h − c) ∗ (π) = c · π
In this very stylized partial equilibrium framework, adjusted GWG
Increases with the additional costs of childbearing (c)
Increases with the probability of being a parent (π)
If employers are rational: ↓ π ⇒↓ gender wage gap

12. Can I have my kids now?
Method and data
Implementation
We would like to estimate the following regression
AGWGi,t = βi + β × Fertilityi,t + γXi,t + i,t

13. Can I have my kids now?
Method and data
Implementation
We would like to estimate the following regression
AGWGi,t = βi + β × Fertilityi,t + γXi,t + i,t
But
Fertility as in TFR is noisy → we want the “risk” by employers
No directly observable inequality → adjust raw GWG
Fertility decisions endogenous to AGWG

14. Can I have my kids now?
Method and data
Instrument: admission of contraceptive pill
A little bit of history
Pill was admitted in US in 1960
Heterogeneity in Europe: admission timing & forms
Many European countries admitted immediately
Some (e.g. Portugal and Spain) lagged behind (late 60’s and 70’s)
Some delayed admission (e.g. Norway)

15. Can I have my kids now?
Method and data
Instrument: admission of contraceptive pill
A little bit of history
Pill was admitted in US in 1960
Heterogeneity in Europe: admission timing & forms
Many European countries admitted immediately
Some (e.g. Portugal and Spain) lagged behind (late 60’s and 70’s)
Some delayed admission (e.g. Norway)
Admission = availability (→ timing)
E.g. former socialist countries: admitted but unavailable
Prescriptions vs otc
...

16. Can I have my kids now?
Method and data
Our instruments
We use variation in pill admission
1 Time since admission of the pill: year - year when admitted
Variation across countries and over time.
2 Additionally: differences in national legislation
Where can pills be bought? Any shop vs. drugstores/ pharmacies
Is prescription required to buy pills?
In our sample, variation only across countries.

17. Can I have my kids now?
Method and data
A note on the estimation procedure
We use 2SLS for panel data as in Baltagi and coauthors (1981, 1992, 2000)
It is a random effects model (FGLS)
but... instrumentation in first stage is different
within component ˜xi,j = xi,j − ˆθ ¯xi
between component ¯xi
Additional instruments are redundant in White sense
→ More precise than RE
Standard errors are adjusted to unbalanced panels

18. Can I have my kids now?
Method and data
Measuring the adjusted gender wage gap
Nopo decomposition
A Flexible non-parametric approach based on perfect matching
Reliable even when even when small set of covariates
(perfect matching)
Reliable even when cannot correct for selection bias
(GWG within common support)
Adjusting for: age (5-year categories) ; education (3 levels) ; marital
status (2 levels) ; urban setting (2 levels)
Not adjusting for household composition (kids)

19. Can I have my kids now?
Method and data
Data
Estimation of the gender wage gap:
1 ECHP: EU 15 (1994 - 2001)
2 EU-SES: Enlarged EU, every four years between 2002 and 2014
3 Labor Force Survey when available (UK, France, Poland) from early
1990’s till 2014
4 Panel data: SOEP (Germany 1991-2014), BHPS (UK, 1991-2008).
The pill data: Finlay, Canning and Po (2012)
Country level data:
Fertility related variables: Eurostat
Other variables: World Bank

20. Can I have my kids now?
Results
Evolution of the RAW gender wage gap−.20.2.4
Gap
1990 1995 2000 2005 2010 2015
Year
ECHP EUSES Others
Evolution of the raw gender wage gap
Notes:Adjusted gender wage gap obtain using Nopo (2008) decomposition. Average equals 0.05. Line
represents fitted values from a regression that also includes source FE

21. Can I have my kids now?
Results
Evolution of the ADJUSTED gender wage gap−.20.2.4
Gap
1990 1995 2000 2005 2010 2015
Year
ECHP EUSES Others
Evolution of the adjusted gender wage gap
Notes:Adjusted gender wage gap obtain using Nopo (2008) decomposition. Average (all sample) is
.09., in 2014 ∼ 0.12. Line represents fitted values from a regression that also includes source FE

22. Can I have my kids now?
Results
Fertility and gender wage gap−.20.2.4
Gap
24 26 28 30 32
Mean age at first birth
Raw GWG
−.20.2.4
Gap
24 26 28 30 32
Mean age at first birth
Adjusted GWG
Notes: Raw and adjusted gender wage gap obtain using Nopo (2008) decomposition. Linear relation
and 95% CI from a simple regression with no additional controls.
Alternative measure of fertility

23. Can I have my kids now?
Results
IV results
Adjusted GWGi,t = β + β1 × Mean age at first child birthi,t + γXi,t + i,t
Model 1 Model 2 Model 3 Model 4 Model 5
Mean age at birth -0.0175 -0.0398 -0.0360 -0.0279 -0.023
p-value (0.05) (0.02) (0.02) (0.10) (0.13)
N 244 244 244 230 230
Year Y Y Y Y
Education Y Y
Log(GDP pc) Y Y
R2
overall 0.313 0.337 0.373 0.334 0.366
R2
between 0.361 0.386 0.425 0.385 0.418
R2
within 0.010 0.005 0.015 0.008 0.018
Notes: All regressions estimated using Baltagi’s RE estimator. All regressions include source FE.
Estimates of the adjusted gender wage gap at the mean obtained using Nopo decomposition. Robust
standard errors used to compute p-values against a two-sided alternative.
Raw GWG

24. Can I have my kids now?
Results
First stage results: Are our instruments good predictors?
Model 1 Model 2 Model 3 Model 4 Model 5
Time since (w) 0.125 0.253 0.153 0.282 0.315
(0.00) (0.00) (0.04) (0.00) (0.00)
Time since (b) -0.026 -0.032 -0.035 -0.037 -0.040
(0.04) (0.02) (0.03) (0.01) (0.01)
Availability (b) 0.636 0.692 0.762 0.496 0.523
(0.02) (0.02) (0.02) (0.13) (0.22)
No prescription (b) -0.732 -0.695 -0.798 -0.167 -0.183
(0.00) (0.00) (0.00) (0.44) (0.51)
Year Y Y Y Y
Education Y Y
Log(GDP pc) Y Y
Notes: Table presents first stage of Baltagi’s RE estimator. Robust standard errors used to compute
p-values against a two-sided alternative. All estimations include source FE

25. Can I have my kids now?
Results
Alternative specifications
HT GWG+ Time FE
Model 1 Model 2 Model 1 Model 2
Mean age at birth -0.020 -0.027 -0.023 -0.020 -0.018
P-value (0.068) (0.021) (0.228) (0.042) (0.201)
Log(GDP pc) Y Y Y
Notes:
HT include prescription and shop availabiity as time invariant exog. covariates together with
country FE P-value Hausman test: 0.42 → RE is prefered
GWG Added controls for industry, firm size and occupation in GWG estimation. We kept only obs.
with +50% of men and women in common support. N dropped to ∼ 1/2 of previous.
REV FE for year. Control for time trends in the data.

26. Can I have my kids now?
Summary
Summary
Do employers discriminate statistically?
If so, lower fertility among youth →↓ GWG
Results are consistent with a model of statistical discrimination
IV estimates ∼ −0.02
Adjusted GWG = .12 (on average)
Delaying 1st
birth by a year cuts Adjusted GWG by almost 20%
Estimates were stable and robust across model specifications
Possible extensions
Can we extend results to developing countries?
Does lower fertility reduce Adjusted GWG over the life-cycle?

27. Can I have my kids now?
Summary
Questions or suggestions?
Thank you!
w: grape.org.pl
t: grape org
f: grape.org
e: l.vandervelde@uw.edu.pl

28. Can I have my kids now?
Appendix
Demographic trends2224262830
Meanageatfirstbirth
1990 1995 2000 2005 2010 2015
Year
Mean age at first birth
11.522.5
Fertilityrate
1990 1995 2000 2005 2010 2015
Year
Fertility rate
Source: EUROSTAT. Lines indicate the fitted values and a 95% CI of a regression of the fertility
measure on time.
Back

29. Can I have my kids now?
Appendix
Is c mostly bourne by women?
Contribution to household production by gender
Households were both partners work 35+ hours with kids < 6 y.o.
Data cover 20 EU countries (EST, LUX, MLT, ROM missing)
0.2.4.6.8
Laundry Repairs Caring Shopping Cleaning Cooking
Mostly women About equal Mostly men

30. Can I have my kids now?
Appendix
Is c mostly bourne by women?
Contribution to household production by gender
Households were both partners work 35+ hours with kids < 6 y.o.
Data cover 20 EU countries (EST, LUX, MLT, ROM missing)
0.2.4.6.8
Laundry Repairs Caring Shopping Cleaning Cooking
Mostly women About equal Mostly men
Surprisingly, 54% of men in sample declare to perform a fair share of tasks
Back

31. Can I have my kids now?
Appendix
Fertility rate and gender wage gap−.20.2.4
Gap
1.2 1.4 1.6 1.8 2
Fertility rate
Raw GWG
−.20.2.4
Gap
1.2 1.4 1.6 1.8 2
Fertility rate
Adjusted GWG
Back

32. Can I have my kids now?
Appendix
IV results: Raw gender wage gap
Model 1 Model 2 Model 3 Model 4 Model 5
Mean age at birth -0.0241 -0.0337 -0.0315 -0.0299 -0.0222
p-value (0.00) (0.07) (0.05) (0.11) (0.14)
Year Y Y Y Y
Education Y Y
GDP pc Y Y
R2
overall 0.277 0.258 0.298 0.299 0.354
R2
between 0.215 0.196 0.231 0.254 0.324
R2
within 0.054 0.044 0.053 0.063 0.063
Notes: All regressions estimated using Baltagi’s RE estimator. All regressions include source FE.
Estimates of the adjusted gender wage gap at the mean obtained using Nopo decomposition. Robust
standard errors used to compute p-values against a two-sided alternative.
Back