Misaligned Incentives and the Scale of Incarceration in the United States
By: Branden DuPont
A REVIEW OF AURÉLIE OUSS'S 2020 ARTICLE
Local Decisions, State Budgets
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Mass incarceration is a state and local problem
- 90% of the 2 million people in prisons and jails today
- Local justice system actors determine who is in custody: prosecutors, judges, probation officers
- Paid by the state; costs are not fully internalized
MISALIGNED INCENTIVE
The most delicious of all
privileges — spending
other people's money.
-John Randolph of Roanoke
MISALIGNED INCENTIVE
Vera Institute of Justice's Incarceration Trends
How Much Of US's Incarceration Can Be Attributed to These Misaligned Incentives ?
- Incarceration is largely subsidized by the state, leading to what Zimring and Hawkins (1992) have referred to as a “correctional free lunch.”
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Other domains health care, unemployment show inefficiencies
- Econ speak: "If demand for incarceration is price-elastic, the cost division of incarceration is expected to impact sentencing."
MISALIGNED INCENTIVE
California Juvenile Justice Realignment
Creates A Natural Experiment
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Juvenile facilities are run at the county level by the California Youth Authority (CYA), but are funded by the State of California
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SB 618: 1996 Juvenile Realignment changed financing structure of juvenile justice.
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"the law discontinuously changed the price that counties would have to pay to incarcerate juveniles"
Research Design
SB 618: Nuts and Bolts
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Goal:
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reduce the over-reliance by counties for less serious juvenile offenders
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to encourage counties to create local programs
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Not meant to reduce incarceration
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Level 1-4
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5% per capita cost for serious offenses (murder, robbery)
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Level 5-7 sliding scale
- 50% per capita cost moderate offenses (burglary, assault)
- 75% per capita cost second degree burglary and car theft
- 100% per capita cost for technical rule violations
Research Design
If decision-makers respond to cost, ... we expect a drop
in CYA admissions when their financial burden increases.
Hypothesis
Commitments to California Youth Authority facilities
Results
Commitments to California Youth Authority facilities
Results
CYA monthly averages for intakes
Commitments to California Youth Authority facilities
Results
CYA monthly averages for intakes
Fit local-polynomial regression lines. 95% confidence
Commitments to California Youth Authority facilities
Results
CYA monthly averages for intakes
Fit local-polynomial regression lines. 95% confidence
Discontinuity: clear, immediate break in mean
XKCD
Methods
Regression Discontinuity Design in Time (RDiT) is used to calculate the drop in juvenile incarceration
Methods
The Effect by Nick C. Huntington-Klein
Assistant Professor of Economics, Seattle University
Methods
The Effect by Nick C. Huntington-Klein
Assistant Professor of Economics, Seattle University
RDiT skips this
Results
Decrease in Juvenile Justice Admission
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fit three RDiT models
- linear
- quadratic (polynomial^2)
- rdrobust, Calonico 2014
- found change in cost resulted in 38– 63% drop in youth incarceration
- probability of being incarcerated in a CYA facility instead of an adult facility for youth under the age of 25 upon entry 42% decrease
- Used DiD to compare <18 in adult with a control group of young adults 19 years old. Found no drop in young adult incarceration.
- Avoided overall increasing adult trends because of 3 strike law's influence
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Other subsidized options
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slight increase in adult admissions, but much smaller than use of
- gradual trend
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slight increase in adult admissions, but much smaller than use of
No Change or Substitution in Adult Incarceration
Threat to Validity
- Main change: cases being dismissed or diverted by probation officers
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Case types with the largest cost-burden shift, saw the largest decrease
- Level 5-7: $1300 – $2600 per month for parole violations, misdemeanors, burglary
- Level 1-4: $150 instead of $25 per month
- "price changes and offense severity are correlated, we cannot disentangle both explanations"
Orange County and Santa Clara
Mechanism
Less prison, more crime?
Spillover Effects?
Spillover Effects?
Study Limitations?
Let's Ask Econ Twitter
Study Limitations?
Could Be Better Modeled As An Interrupted Time Series (ITS)
- "tests for sorting or bunching near the threshold are irrelevant"
- Long time period: unobserved changes & lead to smaller uncertainty estimates than if forecasting
- Model may not account for time series properties (e.g. auto-correlated and non-constant variance)
- may not have affected this paper, but could affect reproducibility
- ITS, especially to test crime/arrest over time
Discussion
"It’s not drug crime that drives mass incarceration, it’s violence. And that’s a much harder problem to solve."
John Pfaff
Question: if this policy was directed at serious violent juvenile crimes or adult crimes, would it have the same impact?
Discussion
Question: Probation officers are low-level bureaucrats with a rehabilitative focus.
Will this realignment affect an elected prosecutor in the same way?
Discussion
Question: Are There Better Ways to Realign Incentives?
- Tell prosecutors about cost of incarceration
- Larry Krasner: Mandate Less Punitive Sentences
Dinosaur
