Do Health Shocks Like Cancer Diagnoses Increase the Likelihood of Committing Crime?

This study investigates whether severe health shocks, such as cancer diagnoses, increase individuals’ likelihood of committing crime. Using rich administrative data from Denmark linking health, income, and criminal records, the authors exploit the plausibly exogenous timing of cancer diagnoses to estimate causal effects. They find that cancer diagnoses lead to a 14% increase in the probability of committing a crime, with effects persisting for over a decade. The increase is evident for both first-time offenses and re-offenses. Mechanisms include reduced income, lower expected punishment due to diminished survival probabilities, and psychological distress. Welfare generosity mitigates the observed increase in crime.

Full Citation and Link to Article

Peijnenburg, K., Andersen, S., Parise, G., & Colmsjö, E. (Accepted/In press, January 2025). Breaking Bad: How Health Shocks Prompt Crime. American Economic Journal: Applied Economics. https://doi.org/10.2139/ssrn.4973245

Extended Summary

Central Research Question

The central question of “Breaking Bad: How Health Shocks Prompt Crime” is whether severe health shocks—specifically cancer diagnoses—cause individuals to become more likely to commit crime. Motivated by rational theories of crime that emphasize cost-benefit calculations involving legal versus illegal earnings and expected punishments, the authors examine how a sudden health crisis might shift these calculations. They seek to determine not only whether criminal behavior increases following a health shock but also which mechanisms—economic hardship, decreased survival probability, or psychological stress—might explain the observed changes. The study uses a robust empirical design to identify causal effects and explores how social welfare policy moderates these impacts.

Previous Literature

This study contributes to multiple strands of research. Within the economics of crime, it adds to a relatively limited body of work examining how life shocks influence criminal behavior. Classic economic models by Becker (1968) and Ehrlich (1973) predict that criminal activity responds to changes in expected income and punishment. Previous empirical work has shown that events like job loss, family formation, and incarceration affect crime rates. For instance, Dustmann and Landersø (2021) and Massenkoff and Rose (2024) demonstrate that childbirth and marriage reduce criminal behavior, while job loss and removal from welfare increase it. However, the role of health shocks as a potential trigger for crime remains largely unexplored in prior studies, with the exception of some correlational evidence. The paper fills this gap by providing causal estimates using high-quality administrative data.

This research also complements literature on turning points in criminal behavior, often used in sociology, where events like military service or marriage shift life trajectories. Cancer diagnoses may act as “negative turning points,” pushing people toward crime rather than away from it. Finally, the study contributes to health economics by highlighting that the consequences of health shocks extend beyond the individual to broader societal outcomes like increased crime, which in turn carries public costs.

Data

The authors use a unique dataset linking multiple administrative registers in Denmark from 1980 to 2018. The core sample includes all individuals diagnosed with cancer during this period, focusing on those aged 18 to 62 (pre-retirement age) and covering the ten years before and after each individual’s diagnosis. This design yields over 5 million person-year observations on 368,317 distinct individuals. The data includes detailed health records (e.g., diagnosis timing and type from national patient registries), income and employment data from tax records, and comprehensive criminal records including convictions, charges, and types of crimes committed.

Demographic variables (gender, education, marital status) and information on household wealth (e.g., homeownership) are included. The Danish context—with universal health insurance and robust welfare records—allows for an analysis relatively free from confounding factors like out-of-pocket medical spending.

Methods

To estimate the causal effect of cancer diagnoses on crime, the authors exploit plausibly exogenous variation in the timing of diagnosis among individuals who eventually develop cancer. The identification strategy compares individuals who are diagnosed at different times but are otherwise similar in age and personal characteristics. The main empirical approach is a staggered adoption design with individual fixed effects and year-by-age fixed effects to control for unobserved time-invariant characteristics and age-related trends.

The authors use a dynamic difference-in-differences (DiD) framework, allowing them to estimate time-varying effects (leads and lags) around the cancer diagnosis. The model captures both immediate and long-term changes in crime rates following diagnosis and checks for parallel trends before treatment. To assess mechanisms, the study interacts the treatment with variables capturing income, survival probabilities, psychological distress, and welfare generosity. Robustness checks include balanced samples, placebo tests, attrition analysis, and alternative control groups (never-treated individuals).

Findings/Size Effects

The authors find that cancer diagnoses significantly increase criminal behavior, with several notable effects:

1. Overall Crime Increase: Cancer increases the probability of committing a crime by 0.10 percentage points, or 14%, from a baseline of 0.69%. The effect is not immediate but emerges in the years following diagnosis and persists for more than a decade.

2. First-Time and Repeat Offenses: Among those without a criminal record, cancer increases the likelihood of committing a first offense by 0.04 percentage points (14%). For those with prior offenses, re-offending increases by 0.06 percentage points (also 14%).

3. Types of Crimes: Both economically motivated crimes (e.g., theft) and non-economic crimes (e.g., assault) increase. Economic crimes rise by 14% and non-economic crimes by 38%, suggesting that motives beyond financial hardship—such as psychological distress—play a role.

4. Economic Mechanism: Cancer leads to significant reductions in income and employment. Total income falls by 1.5%, employment drops by 1.0%, and hours worked decline substantially in the year of diagnosis. Individuals who lack financial buffers—such as singles, renters, or the low-educated—are more likely to turn to crime.

5. Survival Probabilities Mechanism: Individuals facing larger declines in predicted 5-year survival probabilities exhibit greater increases in criminal behavior, consistent with models in which shorter time horizons reduce the perceived cost of punishment.

6. Psychological Distress Mechanism: Cancer patients who seek psychological help after diagnosis are 2.5 times more likely to increase criminal behavior compared to those who do not, indicating a role for emotional or mental health factors.

7. Welfare Moderation: The study uses a 2007 Danish municipal reform as a natural experiment to assess whether welfare generosity mitigates crime. Municipalities that reduced income replacement for cancer patients saw significantly larger increases in crime. A decrease in generosity of 2% raised the crime effect by an additional 0.08 percentage points.

8. Robustness Checks: There is no evidence of pre-trends in criminal behavior prior to cancer diagnosis. Placebo tests using randomly assigned “diagnoses” to never-cancer individuals show no effect. Attrition due to mortality appears to bias estimates downward, suggesting the true effect may be larger.

Conclusion

This study provides compelling evidence that health shocks like cancer diagnoses can lead to increased criminal behavior, even in a high-income welfare state with universal health coverage. The findings underscore that personal health events have public externalities and that these effects persist over the long term. The increase in crime is driven by both economic need and non-economic factors such as reduced survival expectations and psychological distress.

From a policy standpoint, the study suggests that maintaining generous welfare programs and offering mental health support may help mitigate the social costs of health shocks. These results contribute to our understanding of how adversity can shift life trajectories and reinforce the importance of social safety nets in reducing crime and its associated public burdens.

The research also raises important normative questions about justice and rehabilitation, especially for individuals whose criminal behavior may be driven by severe life disruptions outside their control. Ultimately, this study bridges gaps between health economics, criminology, and social policy, offering new insights into how vulnerabilities cascade across domains of life.