Sanctions, Evasion, and Deterrence: Evidence from Speeding Enforcement

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1. Related Broader context Not relevant

   The impacts of incarceration on crime

   David Roodman · 2020 · General Economics · preprint, not peer reviewed · cited 24 times · AI summary available

   The paper reviews how incarceration affects crime and concludes that tougher sentences have little deterrent effect, addressing punishment and deterrence beyond speeding enforcement.

   Abstract

   This paper reviews the research on the impacts of incarceration on crime. Where data availability permits, reviewed studies are replicated and reanalyzed. Among three dozen studies I reviewed, I obtained or reconstructed the data and code for eight. Replication and reanalysis revealed significant methodological concerns in seven and led to major reinterpretations of four. I estimate that, at typical policy margins in the United States today, decarceration has zero net impact on crime outside of prison. That estimate is uncertain, but at least as much evidence suggests that decarceration reduces crime as increases it. The crux of the matter is that tougher sentences hardly deter crime, and th…

2. Related Broader context Not relevant

   Mechanism Design with Informational Punishment

   Benjamin Balzer, Johannes Schneider · 2022 · Games and Economic Behavior, 2023, 40, pp 197-209 · Not summarized yet

   The paper models informational punishment through public messages in mechanism design, rather than studying how fines and penalty points affect drivers.

   Abstract

   We introduce \emph{informational punishment} to the design of mechanisms that compete with an exogenous status quo mechanism: Players can send garbled public messages with some delay, and others cannot commit to ignoring them. Optimal informational punishment ensures that full participation is without loss, even if any single player can publicly enforce the status quo mechanism. Informational punishment permits using a standard revelation principle, is independent of the mechanism designer's objective, and operates exclusively off the equilibrium path. It is robust to refinements and applies in informed-principal settings. We provide conditions that make it robust to opportunistic signal des…

3. Related Broader context Not relevant

   Cost Overruns and Demand Shortfalls in Urban Rail and Other Infrastructure

   Bent Flyvbjerg · 2013 · Transportation Planning and Technology, vol. 30, no. 1, February 2007, 9-30 · cited 202 times · AI summary available

   The paper develops empirical risk assessment for urban rail projects, not sanctions or recidivism.

   Abstract

   Risk, including economic risk, is increasingly a concern for public policy and management. The possibility of dealing effectively with risk is hampered, however, by lack of a sound empirical basis for risk assessment and management. The paper demonstrates the general point for cost and demand risks in urban rail projects. The paper presents empirical evidence that allow valid economic risk assessment and management of urban rail projects, including benchmarking of individual or groups of projects. Benchmarking of the Copenhagen Metro is presented as a case in point. The approach developed is proposed as a model for other types of policies and projects in order to improve economic and financi…

4. Related Broader context Not relevant

   Determining feature importance for actionable climate change mitigation policies

   Romit Maulik, Junghwa Choi, Wesley Wehde et al. · 2020 · Other Statistics · preprint, not peer reviewed · AI summary available

   The paper uses supervised learning to identify factors associated with support for climate mitigation policies, rather than estimating sanction effects on speeding.

   Abstract

   Given the importance of public support for policy change and implementation, public policymakers and researchers have attempted to understand the factors associated with this support for climate change mitigation policy. In this article, we compare the feasibility of using different supervised learning methods for regression using a novel socio-economic data set which measures public support for potential climate change mitigation policies. Following this model selection, we utilize gradient boosting regression, a well-known technique in the machine learning community, but relatively uncommon in public policy and public opinion research, and seek to understand what factors among the several …

5. Related Broader context Not relevant

   Compromised ACC vehicles can degrade current mixed-autonomy traffic performance while remaining stealthy against detection

   George Gunter, Huichen Li, Avesta Hojjati et al. · 2021 · Cryptography and Security · preprint, not peer reviewed · cited 7 times · AI summary available

   The paper simulates compromised adaptive cruise control and its effects on freeway traffic, rather than driver responses to enforcement.

   Abstract

   We demonstrate that a supply-chain level compromise of the adaptive cruise control (ACC) capability on equipped vehicles can be used to significantly degrade system level performance of current day mixed-autonomy freeway networks. Via a simple threat model which causes random deceleration attacks (RDAs), compromised vehicles create congestion waves in the traffic that decrease average speed and network throughput. We use a detailed and realistic traffic simulation environment to quantify the impacts of the attack on a model of a real high-volume freeway in the United States. We find that the effect of the attack depends both on the level of underlying traffic congestion, and what percentage …

6. Related Broader context Not relevant

   Risk measures induced by efficient insurance contracts

   Qiuqi Wang, Ruodu Wang, Ricardas Zitikis · 2021 · Theoretical Economics · cited 4 times · AI summary available

   The paper characterizes risk measures from efficient insurance contracts, a distinct topic from deterrence and speeding sanctions.

   Abstract

   The Expected Shortfall (ES) is one of the most important regulatory risk measures in finance, insurance, and statistics, which has recently been characterized via sets of axioms from perspectives of portfolio risk management and statistics. Meanwhile, there is large literature on insurance design with ES as an objective or a constraint. A visible gap is to justify the special role of ES in insurance and actuarial science. To fill this gap, we study characterization of risk measures induced by efficient insurance contracts, i.e., those that are Pareto optimal for the insured and the insurer. One of our major results is that we characterize a mixture of the mean and ES as the risk measure of t…

7. Related Broader context Not relevant

   Sovereign Debt Default and Climate Risk

   Emilio Barucci, Daniele Marazzina, Aldo Nassigh · 2025 · General Economics · cited 1 time · AI summary available

   The paper models sovereign default and climate risk, rather than the effects of traffic fines and penalty points.

   Abstract

   We explore the interplay between sovereign debt default/renegotiation and environmental factors (e.g., pollution from land use, natural resource exploitation). Pollution contributes to the likelihood of natural disasters and influences economic growth rates. The country can default on its debt at any time while also deciding whether to invest in pollution abatement. The framework provides insights into the credit spreads of sovereign bonds and explains the observed relationship between bond spread and a country's climate vulnerability. Through calibration for developing and low-income countries, we demonstrate that there is limited incentive for these countries to address climate risk, and t…

8. Related Broader context Not relevant

   What Causes Cost Overrun in Transport Infrastructure Projects?"

   Bent Flyvbjerg, Mette K. Skamris Holm, Søren L. Buhl · 2013 · Transport Reviews, vol. 24, no. 1, January 2004, 3-18 · cited 723 times · AI summary available

   The paper statistically examines cost escalation in transport infrastructure projects, not speeding enforcement or recidivism.

   Abstract

   This article presents results from the first statistically significant study of causes of cost escalation in transport infrastructure projects. The study is based on a sample of 258 rail, bridge, tunnel and road projects worth US$90 billion. The focus is on the dependence of cost escalation on (1) length of project implementation phase, (2) size of project and (3) type of project ownership. First, it is found with very high statistical significance that cost escalation is strongly dependent on length of implementation phase. The policy implications are clear: Decision makers and planners should be highly concerned about delays and long implementation phases because they translate into risks …