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Financial penalties for impaired driving

Adult Criminal Justice
Benefit-cost methods last updated December 2024.  Literature review updated July 2025.
Financial penalties are a common component of impaired driving arrests and convictions. In Washington, the level of financial penalties imposed is based on the severity of the offense and the person’s driving history. The minimum mandatory fine for a person with no prior offenses is $990, with a maximum of $5,000. Individuals with two or more offenses within the past seven years face fines between $2,095 and $5,000. Financial penalties are mandatory except for limited exceptions for indigent defendants. This evidence review only includes direct financial penalties associated with impaired driving adjudications.
 
ALL
BENEFIT-COST
META-ANALYSIS
CITATIONS
For an overview of WSIPP's Benefit-Cost Model, please see this guide. The estimates shown are present value, life cycle benefits and costs. All dollars are expressed in the base year chosen for this analysis (2023).  The chance the benefits exceed the costs are derived from a Monte Carlo risk analysis. The details on this, as well as the economic discount rates and other relevant parameters are described in our Technical Documentation.
Benefit-Cost Summary Statistics Per Participant
Benefits to:
Taxpayers $6 Benefits minus costs ($96)
Participants ($80) Benefit to cost ratio n/a
Others ($12) Chance the program will produce
Indirect ($10) benefits greater than the costs 37%
Total benefits ($96)
Net program cost $0
Benefits minus cost ($96)

^^WSIPP does not include this outcome when conducting benefit-cost analysis for this program.

Meta-analysis is a statistical method to combine the results from separate studies on a program, policy, or topic to estimate its effect on an outcome. WSIPP systematically evaluates all credible evaluations we can locate on each topic. The outcomes measured are the program impacts measured in the research literature (for example, impacts on crime or educational attainment). Treatment N represents the total number of individuals or units in the treatment group across the included studies.

An effect size (ES) is a standard metric that summarizes the degree to which a program or policy affects a measured outcome. If the effect size is positive, the outcome increases. If the effect size is negative, the outcome decreases. See Estimating Program Effects Using Effect Sizes for additional information on how we estimate effect sizes.

The effect size may be adjusted from the unadjusted effect size estimated in the meta-analysis. Historically, WSIPP adjusted effect sizes to some programs based on the methodological characteristics of the study. For programs reviewed in 2024 or later, we do not make additional adjustments, and we use the unadjusted effect size whenever we run a benefit-cost analysis.

Research shows the magnitude of effects may change over time. For those effect sizes, we estimate outcome-based adjustments, which we apply between the first time ES is estimated and the second time ES is estimated. More details about these adjustments can be found in our Technical Documentation.

Meta-Analysis of Program Effects
Outcomes measured Treatment age No. of effect sizes Treatment N Effect sizes (ES) and standard errors (SE) used in the benefit-cost analysis Unadjusted effect size (random effects model)
First time ES is estimated Second time ES is estimated
ES SE Age ES SE Age ES p-value
Crime
Involvement in the criminal justice system (e.g., arrests, charges, convictions, incarceration) measured through administrative records (e.g. court records, arrests) or self-report.
 32 4 9494 -0.061 0.077 33 -0.061 0.077 41 -0.061 0.431
Any crash^^
Reported crashes at all injury and damage levels. Includes fatal, injury, and property damage crashes.
32 2 1081 0.044 0.043 33 0.044 0.043 42 0.044 0.299
Fatal crash
Reported crashes with at least one fatality.
32 2 275 0.015 0.111 33 0.015 0.111 42 0.015 0.889
Injury and fatal crash (alcohol related)^^
Reported crashes involving alcohol that result in a fatality, serious injury, or minor injury, measured through driver BAC or a commonly accepted proxy (e.g., single-vehicle nighttime crashes).
32 1 83 -0.594 0.232 33 -0.594 0.232 42 -0.594 0.010
Any non-fatal injury crash
Reported crashes at all injury levels except fatal. Includes all injury levels (serious injury, minor injury, possible injury).
32 1 59 0.147 0.171 33 0.147 0.171 42 0.147 0.390
Fatal crash (alcohol related)^^
Reported crashes with at least one fatality involving alcohol, measured through driver BAC or a commonly accepted proxy (e.g., single-vehicle nighttime crashes).
32 1 216 0.112 0.236 33 0.112 0.236 42 0.112 0.636
Any crash (alcohol related)^^
Reported crashes at all levels (fatal, injury, and property damage) involving alcohol, measured through driver BAC or a commonly accepted proxy (e.g., single-vehicle nighttime crashes).
32 1 1022 0.072 0.044 33 0.072 0.044 42 0.072 0.103
1In addition to the outcomes measured in the meta-analysis table, WSIPP measures benefits and costs estimated from other outcomes associated with those reported in the evaluation literature. For example, empirical research demonstrates that high school graduation leads to reduced crime. These associated measures provide a more complete picture of the detailed costs and benefits of the program.

2“Others” includes benefits to people other than taxpayers and participants. Depending on the program, it could include reductions in crime victimization, the economic benefits from a more educated workforce, and the benefits from employer-paid health insurance.

3“Indirect benefits” includes estimates of the net changes in the value of a statistical life and net changes in the deadweight costs of taxation.
Detailed Monetary Benefit Estimates Per Participant
Affected outcome: Resulting benefits:1 Benefits accrue to:
Taxpayers Participants Others2 Indirect3 Total
Crime Criminal justice system $9 $0 $7 $4 $20
Fatal crash Total costs of fatal crash $0 ($5) ($2) ($14) ($21)
Any non-fatal injury crash Total costs of nonfatal injury crash ($2) ($76) ($17) $0 ($94)
Totals $6 ($80) ($12) ($10) ($96)
Click here to see populations selected
Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $0 2023 Present value of net program costs (in 2023 dollars) $0
Comparison costs $0 2023 Cost range (+ or -) 30%
Research has found that the value of recovered fines exceeds the cost of managing and collecting the fines. For this reason, we assume a per-person cost of $0 for this program.
The figures shown are estimates of the costs to implement programs in Washington. The comparison group costs reflect either no treatment or treatment as usual, depending on how effect sizes were calculated in the meta-analysis. The cost range reported above reflects potential variation or uncertainty in the cost estimate; more detail can be found in our Technical Documentation.
Benefits Minus Costs
Benefits by Perspective
Taxpayer Benefits by Source of Value
Benefits Minus Costs Over Time (Cumulative Discounted Dollars)
The graph above illustrates the estimated cumulative net benefits per-participant for the first fifty years beyond the initial investment in the program. We present these cash flows in discounted dollars. If the dollars are negative (bars below $0 line), the cumulative benefits do not outweigh the cost of the program up to that point in time. The program breaks even when the dollars reach $0. At this point, the total benefits to participants, taxpayers, and others, are equal to the cost of the program. If the dollars are above $0, the benefits of the program exceed the initial investment.

Citations Used in the Meta-Analysis

Chan, Y.-S., Chen, C.-S., Huang, L., & Peng, Y.-I. (2017). Sanction changes and drunk-driving injuries/deaths in Taiwan. Accident Analysis and Prevention, 107, 102–109.

Kim, K.S., Myeong, M.H., & Kweon, Y.J. (2006). Evaluating the effects of safety policy measures on traffic fatalities in Korea. Transport Reviews, 26(3), 293–304.

Mann, R.E., Vingilis, E.R., Gavin, D., Adlaf, E., & Anglin, L. (1991). Sentence severity and the drinking driver: Relationships with traffic safety outcome. Accident Analysis and Prevention, 23(6), 483–491.

Martin, S.E., Annan, S., & Forst, B. (1993). The special deterrent effects of a jail sanction on first-time drunk drivers: A quasi-experimental study. Accident Analysis and Prevention, 25(5), 561–568.

Weatherburn, D., & Moffatt, S. (2011). The specific deterrent effect of higher fines on drink-driving offenders. British Journal of Criminology, 51(5), 789–803.

Young, D.J., & Likens, T.W. (2000). Alcohol regulation and auto fatalities. International Review of Law and Economics, 20(1), 107–126.

Yu, J. (1994). Punishment celerity and severity: Testing a specific deterrence model on drunk driving recidivism. Journal of Criminal Justice, 22(4), 355–366.