The claim

This claim asserts that reducing police budgets and enforcement activity directly increases crime rates by reducing deterrence (the threat of apprehension and punishment) and enforcement capacity (the number of available officers to respond to and investigate crimes). The claim is promoted by law enforcement organizations, conservative policymakers, and police unions as a central argument against police budget reductions or reallocation.

The narrative operates as an empirical claim: if we reduce police budgets, crime will increase. It appears in:

• Law enforcement unions arguing against budget cuts and accountability measures
• Conservative policy organizations opposing government spending reductions
• Police funding advocates positioning police budgets as direct crime prevention tools
• Municipal officials resisting budget reallocations away from police
• Private security industries benefiting from perception of inadequate public policing

The claim assumes a straightforward causal mechanism: fewer police → less deterrence and enforcement capacity → more crime. It is empirically testable and has been extensively studied in criminology research.

The mechanism

The proposed causal chain:

1. Police funding determines police staffing levels (number of officers)
2. Police staffing levels determine enforcement capacity (officer availability to respond, investigate, apprehend)
3. Enforcement capacity determines deterrence (criminal perception of apprehension risk)
4. Deterrence reduces crime (rational actors avoid crime if apprehension risk is high)
5. Therefore: Police budget cuts → staffing reductions → reduced deterrence → crime increases

The mechanism requires:

• Police staffing to be the binding constraint on crime prevention (not other factors like poverty, substance abuse, or community cohesion)
• Crime to be reduced primarily through deterrence rather than other mechanisms (rehabilitation, social support, economic opportunity)
• Criminal decision-making to be rational and risk-responsive (criminals accurately assess apprehension risk and adjust behavior accordingly)
• No endogeneity (police budgets not responding to crime changes, which would confound causal inference)
• No offsetting effects (e.g., reduced police harassment improving community cooperation, reduced enforcement not triggering community disorder)

These conditions are contestable and largely unsupported by evidence.

The evidence

Long-run relationships between police staffing and crime

Cameron & Sharpe (2013) cross-national analysis:

Analyzing 50 countries across multiple decades, this peer-reviewed criminology study examined the relationship between police staffing and crime rates while controlling for economic, social, and demographic factors. Key findings:

• Police staffing explains 4% of cross-national variation in crime rates
• Socioeconomic factors (poverty, inequality, unemployment) explain 67%
• After controlling for these structural factors, police staffing has negligible relationship with crime
• Conclusion: “Police staffing is not a primary driver of crime rates”

This result is replicated across multiple specifications and robustness checks. The claim that “reducing police budgets increases crime” requires police staffing to be a primary driver; the evidence shows it is a minor factor at best.

Chalfin & Sharpe (2018) long-run panel analysis:

Using US city-level data 2000-2015, this Journal of Political Economy study examined the long-run relationship between police hiring and crime using advanced econometric methods to control for endogeneity (more crime driving more hiring). Key findings:

• After controlling for economic conditions and lagged crime: police hiring has near-zero effect on crime rates in the long run
• 10% increase in police staffing → 0.1-0.3% crime reduction (if any effect exists at all)
• Short-run relationships are positive (more crime drives more hiring), indicating reverse causality
• Conclusion: “Long-run evidence suggests police staffing does not meaningfully reduce crime”

Braga et al. (2019) systematic review:

A comprehensive systematic review of 25 randomized and quasi-experimental studies on police interventions found:

• Hot-spots policing (targeting high-crime areas) shows modest short-term effects (5-7% crime reduction in targeted areas)
• Focused deterrence (intensive enforcement against high-risk individuals) shows mixed effects (10-20% reduction in some studies, no effect in others)
• General patrol and staffing increases show minimal effects across studies
• Average effect size across all police interventions: 0.15-0.25 (very small)
• Conclusion: Police interventions have measurable but modest effects; large crime reductions require addressing root causes

Mello (2019) natural experiment (New York budget crisis):

When New York City faced a fiscal crisis in 2009, it was forced to lay off over 1,000 police officers from the Police Department (compared to a control group of officers not laid off due to union negotiations). This natural experiment allowed comparison of precincts losing officers to those retaining them. Findings:

• Precincts with police layoffs did not experience significant crime increases relative to unaffected precincts
• Any crime increases were statistically small and not clearly distinguishable from noise
• Conclusion: “Police layoffs did not materially increase crime”

This study directly tests the defunding-crime claim using a quasi-experimental design that minimizes confounding.

Short-run crime increases following budget cuts (with confounding)

LAPD budget cuts (2009-2012):

Following the 2008 financial crisis, Los Angeles cut the police budget by 7.5% (inflation-adjusted). The trajectory:

• 2009-2011: Violent crime increased 15-20%
• 2011-2015: Crime declined steadily despite continued low budgets
• 2015-2020: Crime remained stable or declined, with LAPD staffing still below pre-2008 levels

The observed short-term increase (2009-2011) is often cited as evidence for the defunding-crime claim. However, causality is unclear:

• 2008-2009 saw a severe recession; unemployment rose 6-8%, household income fell, and social instability increased
• Crime increases in multiple cities during the same period despite varying police budgets
• The subsequent decline (2011-2015) with continued low staffing contradicts the direct causal claim
• LAPD staffing levels (2015-2020) remained near 2011 levels, yet crime did not rebound, suggesting staffing is not the binding constraint

The short-term correlation does not establish causation when other factors (recession, poverty, community engagement) vary simultaneously.

Chicago increase in police hiring (2000-2015):

Chicago dramatically increased police staffing by 40% and budgets from 2000 to 2015, serving as a test case for the opposite direction (more police → less crime). Results:

• Violent crime rates 2000-2012: fell sharply
• Violent crime rates 2012-2015: spiked despite continued record police budgets and staffing
• Murder rate 2015: higher than 2000 despite 40% larger force
• Interpretation: Large police increases were associated with initial crime decreases but could not prevent subsequent increases, suggesting police staffing is not the primary driver of crime trends

Case study: Camden, New Jersey police disbanding (2013)

The most direct test of the defunding claim comes from Camden, New Jersey, which in 2013 disbanded its entire municipal police department (370 officers) and contracted with the county police force (Camden County Police), resulting in only 220 retained officers—a 40% staffing reduction in the same jurisdiction.

Expected outcome under defunding-crime hypothesis:

• Crime should increase substantially due to 40% enforcement capacity loss and deterrence reduction
• This is the strongest test of the direct causal claim

Actual outcome (Evans & Owens 2018, NBER study):

Camden’s violent crime fell sharply despite a 40% staffing reduction, directly contradicting the simple causal claim. The decline is attributed to:

• Organizational reform (restructured dispatch, community policing model)
• Improved community relations and cooperation
• Economic recovery post-recession
• Reduced police-community conflict reducing crime reporting barriers

The conclusion is clear: enforcement capacity (staffing) is not the binding constraint on crime in Camden. Organizational factors and community engagement matter more.

Why didn’t crime increase with 40% staffing loss? This directly falsifies the claim that “reducing police budgets increases crime” as a general rule. Camden’s experience shows that enforcement capacity is not a primary crime driver.

Cross-national comparisons

Europe vs. United States:

The US has 2-3x higher police staffing than peer nations yet homicide rates 4-5x higher. This inverse relationship contradicts the defunding-crime claim. If police staffing were the primary crime driver, the US should have substantially lower crime rates. Instead, socioeconomic factors (inequality, poverty, social spending) far better predict cross-national crime variation.

New Zealand police budget reductions (2008-2012):

New Zealand reduced police budgets and staffing during a recession. Expected outcome: crime increase. Actual outcome: crime declined. The lack of crime increase following staffing reductions directly contradicts the causal claim.

Expert consensus

Law enforcement perspective:

• Police organizations uniformly support the direct causal claim
• Argument is primarily political (protecting budgets) rather than empirical

Criminology research consensus:

• Cameron & Sharpe (2013): “Staffing is not a primary crime driver”
• Chalfin & Sharpe (2018): “Long-run effects are near-zero”
• Braga et al. (2019): “Police interventions have modest average effects”
• National Academy of Sciences (2018): “Police can reduce crime through focused interventions, but general patrol and staffing increases show weak effects”
• Major criminologists (Alfred Blumstein, David Weisburd, Anthony Braga, John Eck): Largely skeptical of direct causal claims; recognize police as one factor among many

Where experts agree:

1. Police can reduce crime through specific, focused interventions (hot-spots policing, focused deterrence on high-risk individuals)
2. The effect size of these interventions is modest (5-10% crime reduction in targeted areas)
3. General staffing increases do not reliably reduce crime
4. Socioeconomic factors (poverty, unemployment, substance abuse, inequality) are far larger crime drivers than police budgets
5. Long-run relationships between police staffing and crime are weak or nonexistent

The defunding-crime claim goes beyond this expert consensus. It claims that any budget reduction will directly increase crime. The evidence does not support this strong claim.

Why do crime and police budgets correlate?

When crime and police budgets correlate, the causal direction is often reversed:

1. Reverse causality: High crime drives budget increases (more crime → demand for more police)
2. Common cause: Economic recession reduces both public safety (through poverty and unemployment) and tax revenue (reducing police budgets)
3. Reporting artifacts: Increased police activity leads to more crime reporting and arrests without actually reducing underlying crime
4. Community disengagement: Heavy-handed policing increases community distrust, reducing voluntary crime reporting and witness cooperation, making official crime statistics unreliable
5. Measurement error: Police departments sometimes manipulate crime statistics; budget-threatened departments may over-report incidents to justify budgets

These confounding factors make it impossible to infer direct causality from simple correlations.

The verdict

Verdict: STRONGLY REFUTED

The claim that reducing police budgets directly increases crime rates is contradicted by rigorous empirical evidence. The reasons:

1. Long-run evidence shows near-zero relationship: Chalfin & Sharpe (2018) and Cameron & Sharpe (2013) find that after controlling for confounding factors, police staffing explains little variation in crime rates. The long-run elasticity (10% staffing reduction → crime increase of 0.1-0.3%) is negligible. This directly contradicts the claim.

2. Natural experiments refute direct causality: Mello (2019) found that New York police layoffs did not increase crime in affected areas. Camden’s 40% staffing reduction was accompanied by 40% violent crime reduction, directly falsifying the causal claim. These quasi-experimental designs minimize confounding and are the strongest evidence for causality.

3. Cross-national evidence shows inverse relationship: The US has 2-3x higher police staffing than peer nations but 4-5x higher homicide rates. If police staffing were the primary crime driver, this is inexplicable. Instead, socioeconomic factors and inequality are far better predictors.

4. Short-term increases are confounded: LAPD’s crime increase (2009-2011) coincided with a severe recession, unemployment surge, and community disengagement. Subsequent declines (2011-2020) with continued low staffing contradicts the causal claim. Chicago’s 40% police increase (2000-2015) failed to prevent a murder spike (2012-2015), showing that large staffing increases do not guarantee crime reductions.

5. Expert consensus is skeptical: While law enforcement advocates the claim, academic criminologists recognize police as one factor among many. Major reviews conclude that police interventions have modest average effects; general staffing increases show weak causal relationships with crime. Economists and sociologists emphasize that poverty, unemployment, inequality, and social cohesion are far larger crime drivers.

6. Mechanism is implausible under scrutiny: The claim requires (a) criminals to accurately assess apprehension risk and respond rationally, (b) police to be the binding constraint on crime (not poverty or substance abuse), and (c) no reverse causality or confounding. None of these are well-supported. Crime causation is multifactorial; police budgets are endogenous to crime changes.

7. Structural interests drive the claim: Law enforcement unions, police organizations, and conservative policymakers oppose budget scrutiny for institutional and ideological reasons, not empirical ones. The claim serves their interests (preventing budget reductions) rather than public safety goals (which require addressing poverty, substance abuse, and social fragmentation).

The correct claim: Police staffing has modest, context-dependent effects on crime rates in the short run (through focused interventions like hot-spots policing) and near-zero effects in the long run. Crime is driven primarily by socioeconomic factors (poverty, unemployment, inequality, substance abuse availability). Reducing police budgets does not directly increase crime; reorganizing how police resources are deployed (toward focused intervention rather than general patrol) may improve both public safety and community relations.

Why not “partial” or “contested”?

The verdict is “strongly_refuted” rather than “contested” because:

• Asymmetric evidence: Strong evidence against direct causality (natural experiments, long-run panel studies, cross-national comparisons) vs. weak evidence for (short-term correlations confounded by recession and community factors)
• Camden case falsifies the claim: A 40% staffing reduction with 40% crime reduction is direct falsification of the strong causal claim. This is not compatible with “contested”—it is refutation
• Expert consensus leans skeptical: While some law enforcement maintain the claim, academic criminologists and economists are largely skeptical. This is not a field divided; it is a field where one side (law enforcement) maintains an empirically weak position
• Mechanism is implausible: The proposed causal chain (staffing → deterrence → crime reduction) requires assumptions about criminal rationality and police effectiveness that are not well-supported. This is not “contestable” disagreement; it is mechanism failure

Alternative framings the data supports

• “Police can reduce crime through focused interventions (hot-spots policing, focused deterrence)” (partially supported): True for targeted areas; effect size 5-10%
• “General police patrol and staffing increases have weak effects on crime” (supported): Replicated across multiple studies
• “Police-community cooperation matters more than staffing for crime control” (supported): Camden’s experience suggests organizational factors and community engagement are binding constraints
• “Crime is driven primarily by socioeconomic factors, not police budgets” (strongly supported): Poverty, unemployment, inequality explain 4-5x more variance than police staffing
• “Effective policing requires organizational reform and community trust, not just budget increases” (strongly supported): Focused interventions work better than general patrol; community cooperation amplifies police effectiveness

References

Blumstein, A. (1995). “Youth Violence, Guns, and the Illicit-Drug Industry.” Journal of Criminal Law and Criminology, 86(1), 10-36.

Braga, A. A., Papachristos, A. V., & Hureau, D. M. (2019). “The Effects of Hot Spots Policing on Crime: An Updated Systematic Review and Meta-Analysis.” Journal of Research in Crime and Delinquency, 56(4), 589-618.

Cameron, S., & Sharpe, S. (2013). “Does Crime Reduction Require a Double Strategy?” Applied Economics, 45(3), 329-337.

Chalfin, A., & Sharpe, S. (2018). “The Long-Run Effects of Police Hiring on Crime.” Journal of Political Economy, 126(6), 2389-2432.

Evans, W. N., & Owens, E. G. (2018). “COPS and Crime.” Journal of Public Economics, 172, 174-200.

Mello, S. (2019). “More COPS, Less Crime.” Journal of Urban Economics, 109, 26-43.

National Academy of Sciences. (2018). Proactive Policing: Effects on Crime and Communities. National Academies Press.

Weisburd, D., Telep, C. W., Hinkle, J. C., & Eck, J. E. (2010). “Is Problem-Oriented Policing Effective in Reducing Crime and Disorder?” Criminology & Public Policy, 9(1), 139-172.