The study, authored by Emtiaz Hossain Hritan of the University of California, Irvine, takes advantage of one of the most useful natural experiments in modern urban economics: the staggered rollout of ridesharing platforms across United States cities beginning in 2010. Because Uber, Lyft, and similar services did not arrive everywhere at once, different cities were exposed to the technology at different times. That variation allows researchers to compare crime trends in cities that adopted ridesharing early against those that adopted it later, while statistically accounting for the possibility that the cities themselves were changing for other reasons.

The headline findings are striking in their consistency. According to the research, the introduction of ridesharing services was associated with a 4.6 percent reduction in the rate of violent crimes, a 5.6 percent reduction in the rate of property crimes, and a 10.5 percent reduction in the rate of burglaries. In a policy field where even single-digit percentage changes are considered meaningful, a double-digit drop in burglaries tied to a commercial app is the kind of result that demands attention from criminologists, economists, and city officials alike.

Just as informative is what the study did not find. The analysis detected no significant effects on larceny, motor vehicle theft, or arson. That pattern of results is not random noise, the research suggests, but a fingerprint of a specific mechanism. Burglary, unlike motor vehicle theft or arson, is often understood in criminological research as an income-generating crime, one committed in part to obtain money or goods that can be converted into cash. If ridesharing reduces burglary more than it reduces other property offenses, that points toward an economic explanation rather than a purely situational one.

That explanation, the study argues, lies in employment. Ridesharing platforms lowered the barriers to earning income in the formal economy by allowing people with a car and a smartphone to drive on flexible schedules. For individuals who might otherwise have faced limited job prospects, particularly in cities with weak local labor markets, gig driving offered a legitimate alternative source of income. Improved employment opportunities generated by the platforms, the research concludes, may have played an important role in the observed crime reductions. In economic terms, the opportunity cost of committing crime rose when a legal, low-barrier income option became available.

This mechanism connects the findings to a long tradition in economics that treats crime as a choice influenced by incentives. From this perspective, people respond to the relative payoffs of legal and illegal activity, and policies that expand legitimate earning opportunities can reduce offending even without adding a single police officer. Ridesharing, in this framing, is not a crime-fighting technology in any deliberate sense. It is a labor market innovation whose side effects happen to include a public-safety dividend.

The author argues that the implications extend beyond the ridesharing industry itself. “My findings suggest that digital platforms may generate public-safety benefits beyond their primary commercial purpose,” Hritan said. “Ridesharing services may complement traditional crime-reduction strategies by improving mobility and expanding employment opportunities.” The statement frames platforms such as Uber and Lyft not as replacements for policing or social programs, but as complements to them, working through channels that conventional crime policy rarely touches.

The mobility channel deserves attention alongside the employment channel. By making transportation cheaper, faster, and more reliably available, ridesharing changed how people move through cities, particularly at night and in neighborhoods poorly served by taxis or public transit. Improved mobility can affect crime in several plausible ways, from changing patterns of guardianship and routine activity to altering how quickly people can leave risky situations. While the study’s strongest evidence points to employment as the key driver, the broader point is that transportation infrastructure, including app-based transportation, is intertwined with the social conditions that shape offending.

The research also adds to a growing body of work examining the unintended consequences of the platform economy. Digital marketplaces were designed to match supply with demand for rides, deliveries, and short-term lodging, not to reshape labor markets or public safety. Yet because these platforms operate at city scale and enter markets at identifiable points in time, they create quasi-experimental conditions that economists can exploit. The staggered rollout design used in this study is a methodological strength, helping to separate the effect of ridesharing itself from broader economic trends, demographic shifts, or policing changes that might otherwise confound the results.

For city governments, the findings arrive at a moment when many are rethinking how they regulate gig economy services. If ridesharing generates measurable public-safety benefits, then the calculus of regulation, licensing fees, and minimum-pay rules becomes more complicated, because policies that constrain the platforms may also constrain whatever crime-reducing effects they produce. At the same time, the results should not be oversold. The study identifies associations tied to the introduction of the services and points to employment as a plausible mechanism; it does not claim that ridesharing is a substitute for addressing the deeper structural causes of crime, and the absence of effects on several offense categories is a reminder that the benefits are specific rather than universal.

What makes the research genuinely provocative is the possibility it raises for the future. If a ride-hailing app can nudge citywide burglary rates down by roughly ten percent simply by changing who can earn money and how easily people can move around, then other digital platforms, from delivery networks to remote work marketplaces, may carry their own unmeasured social externalities, both positive and negative. Economists have spent decades cataloging the costs that new technologies impose on cities, from congestion to labor displacement. This study is a reminder that the ledger has another side, and that sometimes the most consequential effects of a technology are the ones nobody designed it to have.

Subject of Research: The effect of ridesharing services on crime rates in US cities

Article Title: Do ridesharing services affect crime rates?

Article References: Do ridesharing services affect crime rates?. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: ridesharing, Uber, Lyft, crime rates, burglary, violent crime, property crime, employment, gig economy, Economic Inquiry, urban economics, public safety

The research team assembled an original panel dataset covering 31 FATF member countries and regions, including Australia, China, Germany, India, Japan, the United Kingdom, and the United States, during the third round of FATF mutual evaluations from 2003 to 2015. Crime figures were drawn from the United Nations Office on Drugs and Crime database, Eurostat’s Crime and Justice Database, and official national statistical yearbooks, spanning seven core categories such as murder, assault, rape, robbery, theft, burglary, and motor vehicle theft, plus eight additional predicate crimes including drug offenses, corruption, fraud, forgery, extortion, kidnapping, trafficking in stolen goods, and environmental crimes. Compliance levels were quantified through a novel MER-AML index, built by converting the ratings that FATF assessors assigned to each recommendation, compliant, largely compliant, partially compliant, or non-compliant, into numerical scores and averaging them across all applicable recommendations for each jurisdiction and year.

Methodologically, the study is careful about causality. The authors employed a two-way fixed effects model that absorbs both country-specific characteristics, such as culture, geography, and legal tradition, and year-specific shocks, such as waves of economic globalization, while controlling for economic development, unemployment, urbanization, income inequality, education, gender ratios, population density, age structure, and population mobility. To address endogeneity, they turned to a two-stage least squares strategy built on three instrumental variables: the number of years since a country enacted its first anti-money laundering law, regime durability measured from the POLITY 5 database, and membership in the Egmont Group of financial intelligence units. Statistical tests rejected the possibility of weak instruments, and Hansen’s J test confirmed the validity of the over-identifying restrictions, lending credibility to the causal interpretation of the estimates.

The headline finding is striking: stronger compliance with international anti-money laundering standards significantly reduces the total crime rate. According to the fixed effects estimates, a 1 percent increase, equivalent to a 0.01 score improvement on the MER-AML index, corresponds to roughly a 0.2 percent decrease in the total crime rate, measured as offenses per 100,000 people. This result survived a battery of robustness checks, including rerunning the models with raw crime counts instead of rates and applying the instrumental variable estimation. The economics-of-crime logic behind this effect, rooted in Gary Becker’s classic deterrence framework, is straightforward: many crimes are financially motivated, and if the proceeds cannot be converted into clean assets, the expected payoff of offending falls.

However, when the researchers disaggregated crime into violent and property categories, the deterrent effect vanished. Neither murder, assault, and rape, nor robbery, theft, burglary, and motor vehicle theft showed any statistically significant response to AML compliance. The authors explain this pattern through the lens of the Walker Model, the pioneering framework developed by John Walker to estimate laundering volumes by multiplying offenses in each crime category by the average amount laundered per offense. In Walker’s original Australian estimates, an assault generated a mere 2.23 dollars in launderable proceeds and a homicide about 225 dollars, while a burglary yielded 600 dollars and a robbery 1,400 dollars. Violent and opportunistic property crimes simply do not produce the large financial flows that the AML system, which targets banks and designated non-financial businesses and professions, is designed to intercept.

The most provocative results emerged when the team examined the eight serious predicate crimes that feed money laundering. Kidnapping rates declined significantly where AML compliance was stronger, a pattern the authors attribute to the difficulty of laundering large, high-profile ransoms under intensified scrutiny. Drug crimes, forgery, trafficking in stolen goods, and environmental crimes showed no significant change. But corruption, fraud, and extortion moved in the opposite direction: higher AML compliance was positively and significantly associated with higher rates of these high-yield offenses, a result that directly contradicts the study’s initial hypotheses and echoes earlier skepticism about the regime’s effectiveness.

The authors liken this paradox to the so-called cobra effect, a term for policies that backfire by creating perverse incentives, and draw an analogy with American Prohibition, which inadvertently industrialized bootlegging. By restricting opportunities for criminals to launder their own proceeds, AML measures may stimulate demand for specialized, large-scale laundering services. Professional money launderers, whom the FATF itself has flagged as a growing threat, operate sophisticated schemes involving shell companies, false invoicing, and increasingly cryptocurrencies, spanning multiple jurisdictions. By lowering the operational risks and costs of laundering for their clients, these networks may inadvertently reduce the barriers to committing corruption, fraud, and extortion, the very crimes that generate the largest illicit proceeds.

The study also identifies institutional dynamics that may amplify these unintended consequences. Compliance fatigue can set in as regulatory burdens expand, pushing institutions toward box-ticking exercises that prioritize formal adherence over substantive enforcement. Enforcement fragmentation, meaning poor coordination between financial intelligence units, police, and courts, creates blind spots that professional laundering networks exploit. And symbolic compliance, the strategic performance of regulatory rituals without addressing structural risks, has been documented by scholars such as Riccardo Pol, Michael Levi, and Eleni Tsingou, who argue that a compliance industry has grown more focused on process than on impact. Scandals like the Panama Papers and Paradise Papers have reinforced concerns that financial secrecy persists despite the global regime.

Importantly, the authors do not conclude that the FATF framework has failed. The regime has built a shared normative foundation for financial integrity, raised the economic and reputational costs of illicit finance, and created an unprecedented platform for intergovernmental cooperation, with participation now approaching universal. Uneven implementation across jurisdictions, driven by differences in legal infrastructure, institutional capacity, and political will, remains a key constraint, but the absence of deterrent effects on some predicate crimes reflects the fact that crime is motivated by many factors beyond the need to launder money.

The policy implications are pointed. The authors argue that the FATF Recommendations should be recalibrated to target high-yield predicate crimes such as corruption, fraud, and organized crime more directly, that specialized operations against professional money laundering networks must be prioritized, and that future mutual evaluations should incorporate standardized, disaggregated indicators of crime trends and enforcement outcomes rather than relying on procedural metrics. They also call for integrating AML enforcement with anti-corruption initiatives, tax justice efforts, and organized crime suppression. The study’s limitations, including a sample restricted to FATF members and the absence of harmonized data on police density, judicial independence, and drug market size, point toward a natural next step: retesting these relationships once the fourth round of global mutual evaluations is complete. For now, the message is clear: the world’s financial defenses are working in aggregate, but the smartest criminals have found ways to turn those defenses into a business opportunity.

Subject of Research: The effect of FATF international anti-money laundering standards on national crime rates and predicate crimes

Article Title: Do the international anti-money laundering standards reduce crimes? Evidence from FATF members

Article References: Zhang, G., Gao, Z., & Wang, D. (2025). Do the international anti-money laundering standards reduce crimes? Evidence from FATF members. Global Public Policy and Governance, 5(3), 229-250. https://doi.org/10.1007/s43508-025-00120-0

Image Credits: AI Generated

DOI: 10.1007/s43508-025-00120-0

Keywords: anti-money laundering, FATF, financial crime, predicate crimes, corruption, fraud, money laundering, global governance, crime rates, policy effectiveness, professional money launderers, mutual evaluations