Policy 2: Reclassify Crimes

Description

One way states have dealt with prison overcrowding is by reclassifying some crimes so that they are no longer punishable by incarceration. The crimes most likely to be reclassified tend to be those that are lowest cost (e.g. small amounts of drug possession or low value larcenies, etc.) One way to conceptualize a reclassification of some crimes is as a 100% decrease in sentence length, which could be seen as an application of the equations from the first policy change. When using that approach, however, it is important to note that the cost of the crimes committed by individuals now free due to non-incarceration is likely to be on the low end of the crime cost distribution (i.e., we must replace the mean cost \(\overline{c}\) in the equations above with a new quantity, \(c_r\), which represents the mean cost of only the low-end crimes).

To be concrete, I consider the impact of reclassifying the least serious \(r\)% of crimes that were previously subject to incarceration, so that they may now not result in incarceration. I assume that individuals know exactly which sentence they are subject to and thus the policy change only impacts the individuals who commit the reclassified crimes.

Unlike policy change #1, incarceration is assumed to decrease for this policy change, so now crime changes will result in increased costs (since now sentences are lower and more potential criminals are on the streets). The cost due to general deterrence is: \[\mathit{Cost}_{GD} = c_r*\eta_{GD}*crime_r \] where \(c_r\) indicates the mean cost of crime for the lowest \(r\) percent and \(crime_r\) is the amount of crime attributable to the lowest \(r\) percent.

The specific deterrence effect will be: \[\mathit{Cost}_{SD}=c_r*s_r*\frac{drecid}{ds}*\lambda*\mathit{prison}_r\] where \(s_r\) is the mean sentence of the bottom \(r\) percent of sentences and \(\mathit{prison}_r\) is the number of prisoners impacted by the crime reclassification. This times the derivative of recidivism yields the change in recidivism rate. Multiplying this by \(\lambda*\mathit{prison}_r\) gives the total number of increased crimes expected, and taking the product with \(c_r\) gives the total cost.

The cost from reduced incapacitation is easiest to quantify: \[\mathit{Cost}_{Inc}=c_r\lambda*\mathit{sentshare}_r*\mathit{prison}\] where \(\mathit{sentshare}_r\) is the share of overall sentence length of the lowest \(r\) percent.

The benefit of this policy change will come from reduced costs of imprisonment (including value of freedom): \[Benefit=(CP+VoF)*sentshare_r\]

Parameters

Select a set of values from the dropdowns below to pre-fill the parameters or use custom values. For more about the papers this calculator refers to, please consult the references section.

Results

Benefit: Not Calculated
Total Cost: Not Calculated
General Deterrence: Not Calculated
Specific Deterrence: Not Calculated
Incapacitation: Not Calculated
Net Benefit: Not Calculated
Net Benefit/Prisoner: Not Calculated