CoChat
Sign Up
Cited by 89Crime Patterns and InterventionsSchool Choice and PerformanceCriminal Justice and Corrections Analysis

School starting age and the crime-age profile

Open access
Landersø, Rasmus, Nielsen, Helena Skyt, Simonsen, Marianne·2017·The Economic Journal
DOI 10.1111/ecoj.12325
Open this paper in CoChat — free accountOpen PDF

Abstract

This paper uses register-based data to investigate the effects of school starting age on crime. Through this, we provide insights into the determinants of crime-age profiles. We exploit that Danish children typically start first grade in the calendar year they turn seven, which gives rise to a discontinuity in school starting age for children born around New Year. Our analysis speaks against a simple invariant crime-age profile as is popular in criminology: we find that higher school starting age lowers the propensity to commit crime at young ages. We also find effects on the number of crimes committed for boys.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1111/ecoj.12325

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Age is invariably negatively correlated with criminal activities.

    “This effect could be partly mechanical: an extensive literature shows how age is invariably negatively correlated with criminal activities (see, e.g., Landersø et al. (2017)).”

    From Prison Rehabilitation Programs: Efficiency and Targeting (2021) · cites this paper as Landersø et al. (2017)

    The introduction (p. 4) describes an almost universally observed crime-age profile in which crime rates rise until about age 18–20 and decline thereafter. That contradicts the claim that age is invariably negatively correlated with criminal activity. (LLM, conf=0.90)

    Checked by a reasoning model — may be wrong.

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 23

  1. Abadie, A. (2003). 'Semiparametric instrumental variable estimation of treatment response models', Journal of Econometrics , vol. 113(2), pp. 231-263 .
  2. Aliprantis, D. (2012). 'Redshirting, compulsory schooling laws, and educational attainment', Journal of Educational and Behavioral Statistics, vol. 37(2), pp. 316-338.
  3. Anderson, M. (2014). 'In school and out of trouble? The minimum dropout age and juvenile crime', Review of Economics and Statistics , vol. 96(2), pp. 318-331.
  4. Bedard, K. and Dhuey, E. (2006). 'The persistence of early childhood maturity: international evidence of long-run age effects', Quarterly Journal of Economics , vol. 121 (4), pp. 1437-1472.
  5. Black, S.E., Devereux, P.J. and Salvanes, K.G. (2011). 'Too young to leave the nest? The effects of school starting age', Review of Economics and Statistics , vol. 93(2), pp. 455-467.
  6. Black, S.E., Devereux, P.J. and Salvanes, K.G. (2013). 'Under pressure? The effect of peers on outcomes of young adults', Journal of Labor Economics , vol. 31(1), pp. 119-153.
  7. Cook, P.J. and Kang, S. (forthcoming). 'Birthdays, schooling, and crime: regression-discontinuity analysis of school performance, delinquency, dropout, and crime initiation', American Economic Journal: Applied Economics .
  8. Cunha, F. and Heckman, J.J. (2008). 'Formulating, identifying and estimating the technology of cognitive and noncognitive skill formation', Journal of Human Resources , vol. 43(4), pp. 738-782
  9. Elder, T.E. and Lubotsky, D. (2009). 'Kindergarten entrance age and children's achievement: impacts of state policies, family background, and peers', Journal of Human Resources , vol. 44(3), pp. 641-683.
  10. Elder, T.E. (2010). 'The importance of relative standards in ADHD diagnoses: evidence based on exact birth dates', Journal of Health Economics , vol. 29(5), pp. 641-656.
  11. Evans, W.N., Morrill, M.S. and Parente, S.T. (2010). 'Measuring excess medical diagnosis and treatment in survey data: the case of ADHD among school-age children', Journal of Health Economics , vol. 29(5), pp. 657-673.
  12. Fredriksson, P. and Öckert, B. (2013). 'Life-cycle effects of age at school start', Economic Journal , vol. 124(579), pp. 977-1004.
  13. Gaviria, A. and Raphael, S. (2001). 'School-based peer effects and juvenile behavior', Review of Economics and Statistics , vol. 83(2), pp. 257-268.
  14. Gottfredson, M.R. and Hirschi, T. (1990). A General Theory of Crime , Stanford, CA: Stanford University Press.
  15. Grogger, J. (1998). 'Market wages and youth crime', Journal of Labor Economics , vol. 16(4), pp. 756-791.
  16. Jacob, B. and Lefgren, L. (2003). 'Are idle hands the devil's workshop? Incapacitation, concentration, and juvenile crime', American Economic Review , vol. 93 (5), pp. 1560-1577.
  17. Lochner, L. (2011). 'Non-production benefits of education: crime, health, and good citizenship,' in (Hanushek, E. A., S. Machin and L. Woessman, eds.), Handbook of Economics of Education , vol. 4., pp. 183-282, Elsevier.
  18. Luallen, J. (2006). 'School's out... Forever: a study of juvenile crime, at-risk youths and teacher strikes', Journal of Urban Economics , vol. 59(1), pp. 75-103.
  19. McAdams, J.M. (forthcoming). 'The effect of school starting age policy on crime: evidence from U.S. microdata', Economics of Education Review .
  20. Nevo, A. and Rosen, A.M. (2012). 'Identification with imperfect instruments', Review of Economics and Statistics , vol. 94(3), pp. 659-671.
  21. Sacerdote, B. (2001). 'Peer effects with random assignment: results from dartmouth roommates', Quarterly Journal of Economics , vol. 116(2), pp. 681-704.
  22. Sampson, R. J. and Laub, J.H. (1995). Crime in the Making: Pathways and Turning Points through Life , Harvard University Press.
  23. Uggen, C. (2000). 'Work as a turning point in the life course of criminals: a duration model of age, employment, and recidivism', American Sociological Review , vol. 65(4), pp. 529-46.

Cited by

Sorted by citations

Authors
Landersø, R., Nielsen, H. S., & Simonsen, M.
Affiliations
  • Rockwool Foundation (DK)
  • Aarhus University (DK)
ORCID
Venue
The Economic Journal
Publisher
Oxford University Press (OUP)
Published
2016-08-08
Volume
127
Issue
602
Pages
1096-1118
ISSN
  • 0013-0133 (ISSN-L)
  • 1468-0297
DOI
10.1111/ecoj.12325
OpenAlex
W2300032353
Cited by
89
References
1
Citations by year
2026: 4 · 2025: 7 · 2024: 10 · 2023: 8 · 2022: 10 · 2021: 13 · 2020: 10 · 2019: 10 · 2018: 7 · 2017: 6 · 2016: 4
FWCI
18.80
Type
journal article
Language
en
Open access
Licence
Locations
  • The Economic Journal (publishedVersion)
  • SSRN Electronic Journal (acceptedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
Funders
  • Strategiske Forskningsråd (09-070295)
  • CIRRAU
Topics
  • Social Sciences › Sociology and Political Science › Crime Patterns and Interventions
  • Social Sciences › Education › School Choice and Performance
  • Social Sciences › Sociology and Political Science › Criminal Justice and Corrections Analysis
Keywords
school entry age, juvenile delinquency, birth cohort effects, sex differences in crime, criminology

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review