Paul Bingley
Share of the variance explained by heritability, under the classic twin design and after relaxing its equal-environments assumption Heritability falls from 34 to 9 percent for schooling, 60 to 16 for earnings, 56 to 14 for disposable income and 42 to 14 for wealth, once the degree of environmental sharing is allowed to differ between identical and fraternal twin pairs. 0 20 40 60 Schooling 9 34 Earnings 16 60 Disposable income 14 56 Wealth 14 42 Heritability, % of the variance Twin-family model Classic twin design

A finding

Testing the twin model's equal-environments assumption cuts the heritability of schooling from 34 to 9 percent.

The classic twin design reads any excess similarity between identical pairs as genetic, which holds only if identical and fraternal pairs share their environments to the same degree. Linking the Danish Twin Registry to the twins' spouses and children identifies the model without assuming it, and the assumption is rejected. Heritability falls from 34 to 9 percent of the variance in schooling and from 60 to 16 percent in earnings. Shared family environment accounts for 42 and 26 percent.

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Family backgroundEducation

About

I am a Professor at VIVE — The Danish Center for Social Science Research in Copenhagen, where I work in the Health and Later Life research department.

I study how advantages and disadvantages accumulate over a life, from the circumstances of the childhood home to how long people live. The questions are those of applied labour and public economics: schooling, pensions and retirement, labour supply, and what passes from one generation to the next. Most of the work runs on Danish administrative registers, which follow the whole population rather than a sample, and which link children to parents, workers to workplaces, and people to the care they received.

My work has appeared in outlets including the Review of Economics and Statistics, the Journal of Applied Econometrics, the Economic Journal and the Journal of Labor Economics.

Before joining VIVE, I was Professor at SFI — The Danish National Centre for Social Research, which merged into VIVE in 2017. I was previously affiliated with the Economics Department at Aarhus Business School, now part of Aarhus University’s Department of Economics and Business Economics; the Centre for Register-based Research at Aarhus University; the Epidemiology, Biostatistics and Biodemography research unit at the University of Southern Denmark; and the Economics Department at Keele University, now part of Keele Business School.

VIVE staff page

Economics of education Pensions & retirement Labour supply Intergenerational mobility Health & inequality

More Findings

Three more in brief. The Research page presents a broader selection, grouped by theme. The Projects page presents some of the questions I am working on now.

Standard trials understate the gains from tutoring The lower bound on the social multiplier is 3.2 at the observed tutoring share of 0.171, 2.0 to 3.7 across shares 0.15 to 0.25, and falls to 1 at a share of 0.40. Plausible range No gain to classmates At least 3× at the share schools tutored 1× 2× 3× 4× 5× 15% 20% 25% 30% 35% 40% Share of pupils a school would tutor True gain vs. what a standard trial sees

Tutoring a few kindergartners raised reading for the whole school.

Tutoring trials usually randomise pupils within schools, which nets out any benefit to classmates. We randomised 81 Danish schools and 2,583 kindergartners, tutored a few in each and tested all of them. Decoding rose 0.38 standard deviations in the pre-registered target group and 0.27 school-wide. Bounds needing only random assignment and the test's range put the gain to never-tutored peers at 0.19 SD or more, so evaluating tutoring within schools understates its value two- to threefold.

The line is a lower bound, built only from random assignment and the test's score range.

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Education

Effect of parental job loss on grade 9 maths by the child's age at the job loss Job loss when the child is 0 to 1 lowers grade 9 maths by 0.041 SD (95% interval -0.071 to -0.010). Effects at later ages are smaller and their intervals include zero. Ages 17 to 22, after school, are the reference group. After school −0.04 SD +0.02 0 −0.02 −0.04 −0.06 0–1 Infancy 2–5 6–11 12–16 17–22 Child's age when parent lost job Effect on grade 9 maths (SD)

Parental job loss hurts children most when it hits in infancy.

Earlier work shows that losing a job harms the children of the worker, without saying whether the child's age matters. We use Danish plant closures, match exposed children to similar peers, and difference out the selection that does not vary with the child's age by using parents displaced after school has ended. A job loss in a child's first two years lowers ninth-grade maths by 0.04 SD, and the families who cannot borrow their way through the shock drive the result. Job losses later in childhood do much less harm.

Dots are effects by the child's age when the parent lost their job, with 95% intervals. The grey dot is the after-school group everything is compared against.

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Family backgroundEducation

Gap in life expectancy at 40 between lowest and highest socioeconomic status, Danish men and women born 1942 to 1944 Education: men 78 to 87, women 83 to 92; IQ at the draft board: men 76 to 85; Income: men 68 to 85, women 80 to 88; Wealth: men 69 to 86, women 80 to 92; Occupation: men 67 to 86, women 83 to 92; All combined: men 65 to 89, women 74 to 97. Education 9 / 9 yrs IQ at the draft board 9 yrs / n.a. (men only) Income 17 / 8 yrs Wealth 17 / 12 yrs Occupation 19 / 9 yrs All combined 24 / 23 yrs 65 89 74 97 60 70 80 90 100 Expected age at death, lowest to highest status Men Women

The socioeconomic gap in lifespan is far bigger than education or income alone suggest.

Studies of inequality in lifespan usually rank people by one measure, such as schooling or income, missing anyone high on one and low on another. We follow every Dane born in 1942 to 1944 from age 40 to 78 and use machine learning to combine education, income, wealth, occupation and IQ into one ranking. The highest-status men can expect to live 24 years longer than the lowest, and women 23 years, compared with only 9 years for either sex when ranked by education alone. Wealth is the most informative measure.

Each bar runs from the life expectancy at 40 of the lowest-ranked group to that of the highest, for each measure alone and for all combined. Right-hand numbers give the gap for men, then women.

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Health & longevity

Other findings by research theme

Short Biography

Paul Bingley is Professor at VIVE, The Danish Center for Social Science Research, in Copenhagen, where he works in the Health and Later Life department. He works in applied labour and public economics, on the economics of education, pensions and retirement, labour supply, and the intergenerational transmission of economic outcomes, using Danish administrative registers that cover the whole population. His research has appeared in the Review of Economics and Statistics, the Journal of Applied Econometrics, the Economic Journal and the Journal of Labor Economics. Before joining VIVE he was Professor at SFI, The Danish National Centre for Social Research.