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The Effect of Education on Martial Status and Partner Characteristics: Evidence from the UK Dan Anderberg (Royal Holloway, IFS, CEPR and CESifo) and Yu.

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Presentation on theme: "The Effect of Education on Martial Status and Partner Characteristics: Evidence from the UK Dan Anderberg (Royal Holloway, IFS, CEPR and CESifo) and Yu."— Presentation transcript:

1 The Effect of Education on Martial Status and Partner Characteristics: Evidence from the UK Dan Anderberg (Royal Holloway, IFS, CEPR and CESifo) and Yu Zhu (Kent) Kent, 3 rd November 2009

2 Overview Exploits a discontinuity in education attainment induced by a particular school exit rule for 16-year olds operating in England & Wales until 1997 Children born between February and August (the ‘summer-born’) were forced to stay on for an extra term Summer-born are nearly 4 percentage points more likely to hold some academic qualifications Month of birth (MoB) no direct effect on incidence of marriage But summer-born women more likely to marry males who hold some academic qualification and who are more economically active 2

3 Structure 1)Introduction 2)Conceptual Issues: Eq. Education & Marriage 3)Related Literature 4)Institutional Context 5)Data and Sample 6)Results 7)Conclusions 3

4 Introduction Two well-known stylized facts: – Strong positive assortative mating in education – More educated people marry later in life Suggestions that part of the economic return to education obtains through the increased prob. of marrying a higher-educated(earning) spouse: – Benham (1974), Goldin (1992) – Surprisingly little empirical support of a causal relationship – Observed correlation could be due to selection (on social background, geographical location, etc) Graduates density: Richmond park 64%, Hodge Hill (B’ham) 10% 4

5 Theoretical Model 5 Possible channels through which education may have a causal effect on marital outcomes: i.Impact on number of potential partners one meets ii.Impact on type of potential partners one meets iii.Impact on probability of any match leading to marriage Very few theoretical models of marriage market with pre-marital investment in education. Chiappori (2008) assumes frictionless market (thus ruling out the possibility of remaining single)

6 Model Setup 6 Consider an economy populated by (equal-sized) continuums of men & women Cost of education for individual (type) i: ω i =c(α i, z i ) where α i represents individual characteristics (ability, social background) and the binary variable z is a (policy) ‘instrument’, e.g. compulsory schooling rules Z i is assumed to satisfy – Monotonicity, i.e. c(α i, 1) < c(α i, 0) for all I – Exogeneity, i.e. α i independent of (α i, α -i, z -i ) where α -i, z -i denote individual characteristics and instrument of the potential partner

7 Identification Following Imbens and Angrist (1994), the average effect of education on the marriage probability for compliers can be identified if we observe marital status m i ϵ (0,1), education attainment x i ϵ (0,1), and the value of instrument z i ϵ (0,1). 7

8 Related Literature Only a small literature on the causal effect of education on marital outcomes Timing and Frequency of marriage: – Breierova & Duflo (2004) exploit variation over time and across regions in the implementation of a large school construction programme: education increases a woman’s age at 1 st marriage, but not marriage probabilities – Skirbekk et al (2004) show that increase in age at graduation delay women’s age at 1 st marriage, but not marriage probabilities by 45 using Swedish register (social group effect) 8

9 Educational Assortative Mating Behrman & Rosenzweig (2002) twins study – the correlation between spouses’ education using within-twins variation is 40% lower than that using cross-sectional variation, consistent with strong positive assortative mating on individual ‘endowments’ – But still find large (0.4) causal effect of a woman’s education on schooling of her spouse Oreopoulous & Salvanes (2009): somewhat smaller (0.23) causal effect using Norwegian administrative data McCrary & Royer (2006) using nativity data from California/Texas – Women born after the school entry cut-off have less-educated and younger partners (contamination of absolute age effects?) Lefgren & McIntyre (2006) using US census data – Find education has little impact on marital status, but strong causal impact (using MoB as IVs) on husbands’ earnings 9

10 This paper Similar to Lefgren & McIntyre (2006), but – Cleaner identification as the use of within-cohort variation in school leaving age allows us to separate absolute-age and relative-age effects – Focus directly on academic qualifications instead of years of schooling (more accurate/relevant) – Focus on spouse’s academic attainment and economic activity as outcomes (less risk of feedback from individual’s education to spouse’s behaviour) 10

11 School leaving policy in England Minimum school leaving of 16 since Sept 1973 Children not allowed to leave school on their 16 th birthday (as is the case in the US) – Children born between 1 st Sept- 31 st Jan allowed to leave at the end of Spring term (just before Easter) – Children born between 1 st Feb- 31 st Aug (the ‘summer-born’) allowed to leave on the Friday before the last Monday in May – Discontinuity lead to one term difference in length of schooling during which the O-Level/GCSE exams take place – Single point of departure since 1998 Del Bono & Galindo-Rueda (2006) exploit the same rule, but focus on wage returns to education, using post 1992 LFS data only 11

12 Data Pooled UK Labour Force Survey from 1984 to 2006 Largest regular household survey in the UK Sample of individuals in England and Wales, born between Sept 1957-Aug 1973 – All subject to the same school leaving rule – 228k men & 246k women – Observe current marital/employment status of respondent & spouse (but no history) 12

13 Results Validity of MoB as instruments for education: Impact of MoB relative to the Jan-Feb threshold on academic attainment Outcomes: Impact of MoB on marital status Impact of MoB on own economic activity Impact of MoB on spouse characteristics (academic attainment & economic activity) 13

14 Distribution of Highest Academic Qualification by MoB Marked increase in fraction holding level 1 qual. around the threshold Summer-born women also slightly more likely to have level 2 qual. No discontinuity at higher levels Small linear trend within- cohort for level 1 14

15 Fraction Holding Some Ac. Qual. by Cohort Fraction of individuals born before- and-after threshold holding some academic qual. by academic cohorts (upward trend but gap diminishing) No difference before our main sample (because SLA was 15) No difference after main sample (GCSE) 15

16 Fraction Married by Qual (ref: No Qual) (relative) fre- quency of being currently married by ac. qual. 10 percentage points difference in marriage incidence between some qual and no qual after age 30 Large strong association between attainment and marriage (after age 25) 16

17 Fraction Married by Season of Birth 3-month window Upper panel: estimated fractions currently married by age (control for cohort, survey year and diff in age in months) Lower panel focus on the est. difference Insignificant positive diff for men, and insig. negative diff for women 17

18 OLS Estimates of Summer-born on Married Sensitivity analysis 25+ only Varying window sizes (5,4,...1 months) Diff never statistically significant Point estimates virtually zero for women Point estimates larger for men 18

19 IV Estimates of Some Qual. on Married Based on the sample of 25+ Hatched lines show OLS effect No evidence of a causal effect for women Can not rule out a sizable causal effect for men (imprecisely estimated) 19

20 OLS Est. of Ac. Qual on Own Employment Large positive association between academic qualifications and own economic activity for both gender Largest effect between no qualification (reference category) and Level 1 (extensive margin important) 20

21 OLS Estimates of Summer-born on Employment Statically significant effect of the discontinuity at all window sizes except the smallest 1 percentage point for men 0.5 percentage point for women 21

22 IV Estimates of Some Qual. on Employment IV estimates statically significant at all window sizes except the smallest IV estimates larger than OLS estimates for men IV estimates smaller than OLS estimates for women 22

23 OLS Est. of Ac. Qual on Spouse Outcomes The prob of being married to a partner with some ac. qual. is increasing in own qual level Largest difference obtains between No Qual and Level 1 The prob of being married to a partner who is economically active is largely determined by whether the respondent has some qualifications 23

24 OLS Est. of Summer-born on Spouse’s Ac. Qual Women born after the threshold more likely to have husbands with some qual Effect robust wrt to window sizes No such effect for men 24

25 IV Est. of Some Qual on Spouse’s Ac. Qual Women with some qualifications are percentage points more likely to have husbands with some qual Effect robust wrt to window sizes IV < OLS suggests some selection No such effect for men 25

26 OLS Est. of Summer-born on Spouse’s Employment Women born after the threshold more likely to have husbands who are economic- ally active Effect fairly robust wrt to window sizes Effect for men statistically significant and sensitive to window sizes 26

27 IV Est. of Some Qual on Spouse’s Employment Women with some qualifications are about 12 percentage points more likely to have husbands who are economic- ally active IV estimates similar to OLS in sizes No evidence of an effect for men 27

28 Conclusions For women, having education (at low level): – has no impact on the probability of being married – Increases the probability of being married to a qualified and employed husband For men, having education (at low level): – has possible positive impact on the probability of being married – but no indication that it increases the probability of being married to a qualified wife 28


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