Can A $239 Million Prison Transformation Pay for Itself? 

A data-driven model explores how San Quentin’s transformation could reshape releases, recidivism, employment, and long-term public costs.

California’s $239 million investment in the San Quentin Rehabilitation Center has become one of the most debated criminal justice expenditures in the country. When announcing the transformation, Governor Gavin Newsom framed the project in practical terms: ninety-five percent of people in prison will return to communities, and the question is what kind of neighbors they will become. 

The redesign of San Quentin expands education, workforce training, and structured reentry planning inside the facility. Critics see the renovation as an expensive gamble. Supporters view it as overdue modernization. What has largely been missing from the debate is a structural analysis of what happens financially if rehabilitation outcomes change.

To address that gap, The Last Mile worked with researchers to build a multi-year structural model tracking how releases, recidivism, employment, and wages evolve under the California Model. The model compares a status quo trajectory with a rehabilitation-driven trajectory and calculates how those differences affect incarceration costs, lost tax revenue, productivity, and cumulative savings. Instead of evaluating a single cohort, the model follows annual release groups from 2026 through 2035, allowing changes to compound. The central question becomes whether sustained improvements across a decade can offset the initial investment.

A Structural Shift: Why More People Will Be Released Through San Quentin

The model begins with a structural assumption that more people will be released through San Quentin over time. 

Rather than operating as a traditional prison, the function of the redesigned facility will shift into a pre-release hub where individuals spend their final years preparing for reentry. Under this assumption, annual releases increase from just over 250 individuals in 2026 to roughly 900 by 2035. 

This change does not assume more people are released statewide. It assumes individuals nearing release are routed through San Quentin so they receive education, employment preparation, and reentry planning before returning home. As more people move through the facility, more individuals are exposed to programming designed to reduce recidivism and increase employment.

Recidivism Declines as Programming Expands

Recidivism is the central cost driver of incarceration. When people return to prison, costs repeat. When fewer people return, those costs decline. In California today, recidivism for the relevant population sits around 22 percent. That means roughly one in five people released will return to prison within the measured period.

The second structural assumption in this model is that recidivism will decline gradually over the same ten-year period. With expanded education, workforce training, and reentry planning, recidivism is projected to fall steadily, tapering toward approximately 8 percent by 2035. That figure aligns with the current rate observed among returning citizen alumni of The Last Mile.

The change does not happen immediately. Instead, it phases in over time as more individuals pass through San Quentin’s rehabilitation-focused environment.

This gradual decline interacts directly with the first structural assumption: more people will be released through San Quentin each year. As the facility transitions into a pre-release hub, annual releases rise significantly. Even as recidivism rates fall, the larger number of people returning to the community means the absolute number of individuals returning to prison increases in the early years of the model. 

That dynamic produces an important fiscal implication. During the early years of the transition, the total cost of reincarceration increases before it begins to fall. The system is temporarily absorbing more releases while outcomes are still improving. Over time, the declining recidivism rate overtakes the expanding release volume. Once that crossover occurs, the number of people returning to prison begins to drop, and incarceration costs decline alongside it.

Employment Rates Drive the Economic Engine of the Model

Employment is the strongest predictor of successful reentry. Individuals who secure stable work are far less likely to return to prison. They also generate wages, tax revenue, and long-term economic productivity. 

In the status quo system, employment rates for returning citizens remain low. Approximately 25 percent secure stable employment. That means three out of four people leaving prison return to their communities without consistent income, limited access to career pathways, and few opportunities to build long-term stability. 

Unemployment increases the likelihood of housing instability, financial stress, and reengagement with the conditions that often led to incarceration in the first place. When employment remains low, the system absorbs repeated costs: higher recidivism, greater reliance on public services, and lost wages that never circulate through local economies.

The model assumes that expanded education, job training, and employer partnerships increase employment gradually. As more individuals pass through San Quentin’s programming, employment rises toward levels already observed in structured reentry programs, an estimated 75% by 2025. This trajectory mirrors outcomes observed in structured reentry programs, including in the returned citizen population of The Last Mile. 

In this model, wage quality is projected using two trajectories. A conservative scenario assumes wages rising toward roughly $55,000 annually. An optimistic scenario assumes wages approaching $75,000. These figures represent averages across a population that includes both entry-level roles and skilled careers. 

The model treats wages as stable once employment begins. A person earning $35,000 in 2026 is assumed to continue earning that amount in later years. This assumption keeps the model conservative, as real wages typically increase over time in real-world work environments. 

The True Cost of Recidivism Extends Beyond Prison Budgets

Recidivism carries costs beyond incarceration alone. The model includes multiple components to capture the full impact, including pretrial detention, prosecution and courts, public defense, victim services, parole supervision and more.

Each return to prison removes a worker from the economy and triggers a new list of public expenditures. Under the status quo system, these costs repeat consistently. Under the new rehabilitation model, fewer people return over time, reducing both direct and indirect costs.

The model calculates a comprehensive cost of recidivism. Direct incarceration costs are estimated using average annual cost multiplied by an assumed 1.3-year return length. The model also includes broader social costs (like those listed above), and lost tax revenue is calculated using projected wages and effective tax rates. Productivity losses account for income that individuals would have earned if they remained in the workforce. Together, these components create a full cost of recidivism that extends far beyond prison budgets.

These costs are calculated for both the status quo and California Model scenarios across each year. As recidivism declines and employment rises, total costs fall while productivity increases. The model therefore captures both reduced spending and increased economic activity.

Cumulative Productivity Creates Accelerating Savings

The most important feature of the model is cumulative productivity. Individuals who return home and remain employed generate wages every year they stay in the workforce. Each new cohort adds to that total.

In this model, someone released in 2026 contributes to the economy through 2035 if they remain employed. As employment rates rise and wages increase, cumulative productivity accelerates. By the later years of the model, productivity from earlier cohorts combines with new releases, producing a steep upward curve in total economic output.

This cumulative effect becomes the largest contributor to overall savings. The model shows productivity gains exceeding $130 million annually in later years under optimistic assumptions. The later years dominate the break-even calculation because multiple cohorts contribute simultaneously.

Break-Even Timeline: When the Investment Pays for Itself

The final step in the model compares cumulative savings against the initial $239 million investment in the San Quentin Rehabilitation Center. 

Rather than focusing on a single year, the model tracks how improvements in recidivism, employment, and wages build over time. Each of these changes produces measurable financial effects; Fewer people returning to prison reduces incarceration costs, more people working increases tax revenue, higher wages expand economic productivity. Together, these factors create annual savings that compound year after year.

The trajectory unfolds in phases. In the early years, costs rise slightly as more people are released through San Quentin while recidivism is still declining. This transition reflects the structural shift in how the facility is used. More individuals are being prepared for release, which temporarily increases the number of returns even as outcomes improve. During the middle years of the model, recidivism continues to fall and employment rises, stabilizing costs. By the later years, multiple cohorts are working simultaneously, and cumulative productivity accelerates. At that point, savings begin to grow rapidly.

Under conservative wage assumptions, cumulative savings approach the initial investment around 2034. Under more optimistic employment outcomes, the break-even point arrives slightly earlier, near the end of 2033. After that point, projected savings continue to expand, meaning the transformation begins generating net positive fiscal impact.

The model suggests that the transformation of San Quentin does not produce immediate savings. Instead, it gradually reshapes outcomes. As releases increase, recidivism declines, employment expands, and productivity compounds across cohorts. Over time, those shifts offset the initial investment and convert prison transformation into a long-term economic benefit.

A Conservative Model With Expansive Implications

The model outlined here does not assume dramatic overnight transformation. It does not assume perfect implementation, universal success, or immediate fiscal return. 

Instead, it follows a deliberately conservative path, grounded in gradual improvements and restrained projections. Recidivism declines slowly over a decade rather than dropping immediately. Employment increases steadily rather than jumping to peak outcomes. Wages are held constant once individuals enter the workforce, even though real-world earnings typically rise with experience. 

The model also accounts for a transitional period in which costs increase before they fall, reflecting the reality that more people will be released through San Quentin while the new approach takes hold. Each of these assumptions tempers the projection and narrows the margin for optimism.

Even within those constraints, the structural shift remains clear. As more individuals pass through a rehabilitation-focused pre-release environment, the number of people returning to prison begins to decline. At the same time, employment rises and wages generate measurable economic activity. 

Those outcomes build across cohorts, creating cumulative productivity that grows year after year. The model therefore captures not only the direct fiscal impact of reduced reincarceration, but also the broader economic contribution of individuals who return home prepared to work and remain in their communities.

The break-even timeline emerges from that compounding effect. Under conservative wage assumptions, cumulative savings approach the original investment around 2034. Under more optimistic but still plausible employment outcomes, the break-even could occur even sooner. 

This model does not rely on aspirational claims about rehabilitation. It follows measurable inputs: releases, recidivism, employment, and wages. It accounts for both costs and benefits, including those often overlooked in discussions of incarceration. It assumes incremental progress and allows time for outcomes to mature. Within those parameters, the analysis suggests that transforming San Quentin into a rehabilitation-centered facility has the potential to shift incarceration from a recurring public expenditure into a long-term economic contributor.

If those assumptions hold, the implications extend beyond a single facility. A prison designed to prepare individuals for reentry changes the flow of people returning to communities. Fewer returns to prison reduce public costs. More individuals entering the workforce expand economic activity. Over time, those changes reinforce one another, creating a cycle defined not by repeated incarceration, but by sustained opportunity.

---

By Robert Roche, VP of Marketing, and Sam Bufe, Sr. Manager of Research and Analytics at The Last Mile.

Want articles like this one in your inbox? Subscribe to The Last Mile Marker. This is a biweekly newsletter offering in-depth insights, critical updates, and inspiring stories on criminal justice reform and second chances.