skip to main content
Washington State Institute for Public Policy
Back Button

Day fines

Adult Criminal Justice
  Literature review updated February 2017.
Open PDF
In the criminal justice system, fines can be used as a sanction when a person commits a crime. Typically the magnitude of these fines is determined based solely on the gravity of the offense, and not on the person’s ability to pay the fine through legitimate means. To achieve equitable punishment, day fines are a method of calibrating fines based on both the gravity of the offense as well as the individual’s ability to pay. When day fines are assessed, a judge first determines the scale of punishment that is appropriate for the offense by calculating “punishment units.” A punishment unit equals a day’s pay. Thus, if a person is sanctioned to three punishment units (3 days’ pay), the total amount paid by the individual depends on the person’s income. This type of sanction is typically used for municipal violations or non-violent felonies.

Meta-analysis is a statistical method to combine the results from separate studies on a program, policy, or topic in order to estimate its effect on an outcome. WSIPP systematically evaluates all credible evaluations we can locate on each topic. The outcomes measured are the types of program impacts that were measured in the research literature (for example, 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.

Adjusted effect sizes are used to calculate the benefits from our benefit cost model. WSIPP may adjust effect sizes based on methodological characteristics of the study. For example, we may adjust effect sizes when a study has a weak research design or when the program developer is involved in the research. The magnitude of these adjustments varies depending on the topic area.

WSIPP may also adjust the second ES measurement. Research shows the magnitude of some effect sizes decrease 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. We also report the unadjusted effect size to show the effect sizes before any adjustments have been made. More details about these adjustments can be found in our Technical Documentation.

Meta-Analysis of Program Effects
Outcomes measured No. of effect sizes Treatment N Adjusted effect size(ES) and standard error(SE) Unadjusted effect size (random effects model)
ES SE Age ES p-value
29 2 383 0.327 0.325 29 0.342 0.267
29 1 191 -0.163 0.172 31 -0.163 0.343
29 1 191 -0.556 0.182 31 -0.556 0.002

Citations Used in the Meta-Analysis

McDonald, D.C., Greene, J., Worzella, C., & Abt Associates Inc 55 Wheeler Street Cambridge MA 02138. (1992). Day fines in American courts: The Staten Island and Milwaukee experiments. United States.

Turner, S. & Greene, J. (1999). The FARE probation experiment: implementation and outcomes of day fines for felony offenders in Maricopa County. The Justice System Journal, 21(1), 1-21.