Life-Cycle Bias Adjustment and Intergenerational Association in Crime

Bibliographic Data

ID19419219
AuthorsYu‐wei Luke Chu (0000-0002-8537-3468, Victoria University of Wellington, corresponding author), Lorena Di Bono (Victoria University of Wellington)
Year2026
Pages1-23
Publication date2026-04-06
Open AccessNo
TypeARTICLE
VenueJournal of Business and Economic Statistics (JOURNAL)
Journal identifiersISSN: 0735-0015 • E-ISSN: 1537-2707
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/07350015.2026.2654892
OpenAlexW7151032532
LanguageEN
References cited26

Using age-specific measures as proxies for lifetime outcomes can introduce bias into estimates of intergenerational associations. We extend the generalized errors-in-variables (GEiV) model to the estimation of intergenerational crime associations and implement a data-driven method to correct for life-cycle bias. The GEiV adjustment accounts for both the extensive and intensive margins and introduces an elasticity estimator that accommodates zeros. Our results show that intergenerational associations are underestimated by 30–50%, even when criminal behaviors are measured during the teenage years, a period least affected by life-cycle bias. The GEiV-adjusted intergenerational elasticity between fathers and sons in New Zealand is approximately 0.7 for the likelihood of committing any crime and 0.5 for the number of crimes committed. Mother–child elasticities are smaller than father–child elasticities. The GEiV-adjusted estimates remain stable across ages, birth cohorts, number of aggregated years, and crime types and severity

Data collection · Crime Patterns and Interventions · Family Dynamics and Relationships · Financial Literacy, Pension, Retirement Analysis

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Open DOIOpen Access