A Bounding Approach to Age–Period–Cohort Analysis: A Demonstration Using Public Crime Concerns in Germany

Abstract Objectives In this paper, we present an application of a bounding approach to age–period–cohort (APC) analysis, recently developed by Fosse and Winship (2019), offering a transparent and assumption-aware alternative to commonly used identification strategies. Specifically, we apply the method to evaluate long-term trends in public concern about crime in Germany, addressing whether observed changes reflect genuine period effects. Methods For the demonstration, we use data from the German Socio-Economic Panel (SOEP) covering 1994–2020 focusing on the item measuring the concerns about crime in Germany. Results Using an intuitive and theoretically warranted assumption that crime concerns are unlikely to decrease from late adolescence into adulthood, we identify a declining period trend. However, additional constraints might be needed to narrow the solution space for age and cohort effects. Conclusions A bounding approach to APC analysis is easy to implement. The method allows extracting meaningful conclusions under transparent and testable assumptions, offering a promising alternative to models relying on hidden or arbitrary constraints.

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Publication Details

Journal
Journal of Quantitative Criminology
Published
2025-10-15
DOI
https://doi.org/10.1007/s10940-025-09633-7
Primary Topic
Health disparities and outcomes
Type
article
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article

A Bounding Approach to Age–Period–Cohort Analysis: A Demonstration Using Public Crime Concerns in Germany

Gordey Yastrebov, Alexander Trinidad, Thomas Léopold
Journal of Quantitative Criminology
Health disparities and outcomes
article

A Bounding Approach to Age–Period–Cohort Analysis: A Demonstration Using Public Crime Concerns in Germany

Gordey Yastrebov, Alexander Trinidad, Thomas Léopold
article en

Abstract

Abstract Objectives In this paper, we present an application of a bounding approach to age–period–cohort (APC) analysis, recently developed by Fosse and Winship (2019), offering a transparent and assumption-aware alternative to commonly used identification strategies. Specifically, we apply the method to evaluate long-term trends in public concern about crime in Germany, addressing whether observed changes reflect genuine period effects. Methods For the demonstration, we use data from the German Socio-Economic Panel (SOEP) covering 1994–2020 focusing on the item measuring the concerns about crime in Germany. Results Using an intuitive and theoretically warranted assumption that crime concerns are unlikely to decrease from late adolescence into adulthood, we identify a declining period trend. However, additional constraints might be needed to narrow the solution space for age and cohort effects. Conclusions A bounding approach to APC analysis is easy to implement. The method allows extracting meaningful conclusions under transparent and testable assumptions, offering a promising alternative to models relying on hidden or arbitrary constraints.

Journal of Quantitative Criminology
Albertus-Magnus-Institut (DE)
Openalex Percentile: Top 63%
Health disparities and outcomes
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