Fiscal Resilience in the Post-Labor Transition: An Analytical Framework for “The Great Unwinding”

The Precarious Foundation: Municipal Finance in the Late Labor Era

The fiscal architecture of modern state and local governments in the United States is a complex system developed over a century of economic activity predicated on a single, foundational assumption: the centrality of human labor. While revenue streams are categorized into distinct silos—property, sales, income—a deeper analysis reveals an interlocking system profoundly dependent on the existence of a large, stable, wage-earning population. This systemic dependency represents a critical vulnerability in the face of a structural economic transition characterized by mass labor displacement through automation. Understanding the precise nature of this fragility is the first step toward designing a more resilient fiscal framework for the 21st century.

Anatomy of the Municipal Tax Base: A Quantitative Analysis of Revenue Sources

In fiscal year 2021, state and local governments in the United States collected a combined $4.1 trillion in general revenues.¹ Of this total, taxes constitute the largest single component, generating approximately half of all revenue.² The remaining funds are derived from a combination of federal intergovernmental transfers and charges for specific government services.¹

A granular analysis of the tax base reveals three primary pillars. Property taxes are the largest single source of tax revenue, accounting for 15% of combined state and local general revenues. They are followed closely by individual income taxes at 13% and general sales taxes at 12%. Smaller but still significant contributions come from selective sales taxes (e.g., on fuel and tobacco) at 5% and corporate income taxes at 2%.¹ Beyond direct taxation, charges for services—such as tuition at public universities, payments to public hospitals, or fees for utilities like water and sewerage—provide another 14% of general revenues.¹

This aggregate picture, however, masks crucial differences between state and local financing structures. State governments rely heavily on taxes tied to economic activity, with individual income taxes (19%) and general sales taxes (14%) serving as their primary revenue sources. In contrast, local governments, including municipalities and school districts, exhibit an extraordinary dependence on property taxes, which constitute over 70% of their total tax collections and 30% of their total general revenue.¹ This heavy reliance makes local government finance particularly susceptible to shocks that affect real estate values and the ability of residents to pay their property tax liabilities.

While these revenue streams appear distinct on a balance sheet, they are deeply interconnected through the mechanism of widespread employment. Income tax is a direct levy on wages. Sales tax is funded by the consumption that wages enable. Property taxes, the cornerstone of local finance, are underwritten by the ability of employed homeowners to pay mortgages and the commercial value of properties housing businesses that employ people. Even user charges are ultimately paid from household and business income derived from a labor-centric economy. This reveals a hidden, critical dependency that makes the entire structure far more fragile than a simple accounting breakdown would suggest.

Identifying Key Systemic Vulnerabilities

The profound reliance on employment-linked revenue creates multiple points of failure in a scenario of large-scale, permanent technological unemployment. These vulnerabilities can be categorized into direct, indirect, and lagging impacts, which together threaten a cascading fiscal collapse.

The most immediate and severe shock would be to revenues directly tied to payroll. The disappearance of jobs would lead to a rapid collapse of individual income tax collections, which represent 13% of combined state and local revenue and a larger 19% of state-only revenue.¹ This would be compounded by the decline in corporate income taxes (2% of combined revenue) as firms with fewer human employees and different legal structures optimize their tax liabilities.¹

The second-order impact would be a sharp contraction in consumption-based tax revenues. As displaced workers lose their primary source of income, discretionary spending plummets. This would directly erode the sales tax base, which accounts for 12% of combined revenues and is a major funding source for many states.¹ The system that automates away the worker simultaneously automates away the consumer, breaking the fundamental circular flow of income that underpins the fiscal health of the state.

The most critical and potentially catastrophic vulnerability lies in the delayed impact on property taxes. Historically, property tax revenues are a lagging indicator of economic health, as assessments are infrequent and property values do not collapse overnight.³ In a typical cyclical recession, this lag provides a welcome source of stability for local governments. However, in a structural transition defined by permanent job loss, this lag becomes a devastating flaw. Mass displacement would trigger a downward spiral of mortgage defaults, population flight from obsolete economic hubs, and collapsing commercial real estate values. Municipal leaders, potentially reassured by stable property tax receipts in the initial years of the transition, may fail to recognize the severity of the crisis until the economic value underpinning their primary revenue source has irrevocably eroded. This creates a “fiscal time bomb” that detonates years after the initial employment shock, leading to a sudden and irreversible collapse of the funding for essential local services like schools, police, and fire departments.

Revenue Source	% of Combined State & Local Revenue	% of State-Only Revenue	% of Local-Only Revenue	Primary Link to Employment
Individual Income Tax	13%	19%	2%	Direct (Levied on wages and salaries)
General Sales Tax	12%	14%	5%	Indirect (Funded by consumer spending from wages)
Property Tax	15%	4%	30%	Lagging (Paid by homeowners and businesses reliant on a wage-based economy)
Charges & Miscellaneous	14%	9%	N/A	Indirect (Paid from household and business income)
Selective Sales Tax	5%	7%	2%	Indirect (Funded by consumer spending from wages)
Corporate Income Tax	2%	3%	N/A	Direct (Levied on profits in a labor-centric model)
Federal Transfers	27%	37%	N/A	Varies (Some programs are counter-cyclical to unemployment)
Other Taxes	3%	4%	N/A	Mixed

Table 1: Comparative Breakdown of US State & Local Government General Revenue Sources (FY 2021). Data compiled from.¹ This table demonstrates the systemic reliance of government finance on revenue streams directly or indirectly linked to a wage-earning population.

Echoes of the Unwinding: Fiscal Collapse in the Deindustrialization Era

To comprehend the potential magnitude of the fiscal crisis precipitated by the transition to a post-labor economy, it is not necessary to rely on abstract models alone. The history of deindustrialization in the American “Rust Belt” from the 1950s onward provides a powerful and grimly detailed predictive model for the “Great Unwinding.” The collapse of cities like Detroit was not merely a historical tragedy but a demonstration of a repeatable socio-economic process: when a region’s core economic function is rendered obsolete by technological and global shifts, and no framework exists to manage the transition, a cascading failure of fiscal systems and social structures is the inevitable result.

Case Study: The Fiscal and Social Unraveling of Detroit

Detroit’s mid-20th-century prosperity was built almost entirely on the automotive industry. The introduction of automation on assembly lines in the 1970s, combined with global competition and the offshoring of manufacturing, “decimated” the city’s economic base.⁶ This technological and economic shift triggered a mass exodus of both jobs and people. The city’s population, which peaked at nearly 1.85 million in the 1950s, plummeted as over a million residents left in the subsequent decades.⁶

This capital and population flight had catastrophic fiscal consequences. As the tax base shrank, the city’s vast 138-square-mile infrastructure became fiscally unsupportable.⁶ The erosion of the property tax base was particularly acute. By 2012, it was reported that more than half of all property owners in Detroit failed to pay their taxes, resulting in a revenue loss of $131 million in a single year—an amount equivalent to 12% of the city’s entire general fund budget.⁶ This created a fiscal death spiral: declining revenues forced cuts to public services, which in turn made the city less desirable, prompting more residents to leave and further eroding the tax base.⁷ The experience of Detroit provides a high-fidelity model of the causal chain of fiscal collapse: a structural economic shift leads to permanent job loss, which triggers population flight, which collapses the tax base, leading to public service insolvency.

The Domino Effect: From Tax Base Erosion to Public Service Insolvency

The fiscal crisis in deindustrialized cities translated directly into a tangible collapse of essential public services. The loss of tax revenue is not an abstract accounting problem; it means there is no money to pay for firefighters, maintain roads, or keep the lights on.⁷

In Detroit, the consequences were stark. At the height of the crisis, 40% of the city’s streetlights were non-functional, plunging entire neighborhoods into darkness.⁶ The average police response time for even high-priority emergency calls stretched to 58 minutes, compared to a national average of around 11 minutes.⁶ The public school system imploded; student enrollment fell from over 164,000 in 2002 to under 53,000 a decade later, forcing the closure of numerous school buildings and the reduction of teachers and programs.⁶ This deterioration of public services creates a vicious feedback loop. A city that cannot guarantee basic safety, functioning infrastructure, or decent schools becomes fundamentally unlivable, accelerating the flight of remaining residents and businesses and ensuring the fiscal crisis becomes permanent.⁷

Sociological Fallout: The Collapse of Social Cohesion and Institutional Trust

The most profound and lasting damage inflicted by deindustrialization was not fiscal but social. The economic abandonment of these communities shattered the social fabric and created deep-seated institutional scarring that persists to this day.

Workplaces in industrial towns were more than just sites of production; they were the central organizing hubs of community life and the foundation of social networks.⁸ The closure of a major plant did not just eliminate jobs; it dissolved the “like family” bonds between coworkers and erased a core component of the community’s shared identity—being a “steel town” or a “car town”.⁸ This loss of identity and social connection contributes to an image of the community as a “site of failure,” undermining the collective confidence needed to pursue recovery.⁸

Perhaps most critically, the experience of abandonment led to a profound and enduring loss of faith in major societal institutions. Workers who had paid taxes, served corporations loyally, and participated in civic life felt betrayed when the government, their employers, and their unions failed to protect them from economic devastation.⁸ This collapse of trust creates a population that is deeply skeptical of and resistant to new initiatives, even those designed to help. Any future transition plan, therefore, cannot be purely technical or financial. It must be preceded by a robust strategy for rebuilding civic trust and ensuring community buy-in, as populations scarred by one economic transition will not readily trust the institutions proposing to manage the next one.

Indicator	1970	1990	2012	% Change (1970-2012)
Population	1,514,063	1,027,974	701,475	-53.7%
Manufacturing Employment	~296,000	~125,000	~27,000	-90.9%
Property Tax Collection Rate	>90% (Est.)	N/A	<50%	N/A
Public School Enrollment	~290,000	~175,000	52,981	-81.7%
Police Response Time (avg.)	N/A	~15 min (Est.)	58 min	N/A
Violent Crime Rate (per 100k)	~1,100	~2,200	~2,137	+94.3%

Table 2: Fiscal Collapse Case Study: Key Indicators for Detroit (Selected Years, 1970-2012). Data compiled and estimated from.⁶ The table illustrates the cascading failure across demographic, economic, fiscal, and social domains following deindustrialization.

The Automation Shockwave: Projecting the Impact on Regional Employment Hubs

The historical analogy of deindustrialization provides a stark warning, but the transition to the L.A.C. economy will have its own unique characteristics. The automation shockwave will be driven by a different set of technologies—robotics and artificial intelligence—and will impact different sectors of the economy. By focusing on a modern industry that is a prime candidate for rapid automation, such as logistics and transportation, it is possible to construct a plausible, near-future scenario of the “Great Unwinding.” This analysis makes the threat concrete, revealing a new geography of economic disruption and a fiscal crisis driven not just by the loss of low-wage jobs, but by the automation of high-wage cognitive labor.

The Logistics and Transportation Sector as a Bellwether for Displacement

The logistics and transportation sector serves as an ideal bellwether for the coming wave of automation-driven displacement. The industry is currently facing a confluence of pressures—including persistent labor shortages and an explosion in demand from e-commerce—that are accelerating investment in automation.¹⁰ The market for logistics automation is projected to more than double in less than a decade, growing from $52.59 billion in 2020 to an estimated $133.21 billion by 2028.¹¹

This investment is not speculative. The transportation and warehousing industry has the third-highest automation potential of any sector in the U.S. economy.¹⁰ Automation is being deployed across the entire supply chain, from robotic arms and automated retrieval systems in warehouses to AI-powered software for optimizing routes and managing inventory.¹¹ While proponents argue that this will create new jobs in areas like technology maintenance and data management, the scale of disruption to existing roles is expected to be immense. Widespread displacement at the sector level is an almost certain outcome, making logistics a critical case study for understanding the speed and nature of the L.A.C. transition.¹¹

Modeling a Regional Fiscal Crisis: The “Vaporized” Payroll Tax Base Scenario

The fiscal impact of automation in the logistics sector will be determined not just by the number of jobs lost, but by which jobs are lost. The common narrative focuses on the replacement of manual laborers, such as warehouse workers and truck drivers. However, recent analysis of the capabilities of generative AI reveals a more complex and fiscally perilous scenario.

While roles like truck mechanics exhibit virtually zero task exposure to AI, and truck drivers face relatively low exposure, the situation is reversed for cognitive and administrative roles.¹² An analysis of U.S. logistics occupations shows that for logistics managers—a group encompassing operations, warehouse, and transportation managers—more than 90% of their tasks are susceptible to AI-driven automation.¹² This is a critical finding. The automation of a single high-wage managerial position can have a far greater impact on a municipality’s income tax base than the displacement of several lower-wage manual workers.

Consider a hypothetical city whose economy is dominated by a major logistics hub. The automation of a significant portion of its high-earning managerial, administrative, and data-entry workforce would cause its payroll and income tax base to “vaporize” with shocking speed. This “managerial carnage” driven by AI represents a fiscal multiplier effect, where the loss of high-salary jobs creates a disproportionately severe and rapid fiscal shock, creating a more acute crisis than models focused solely on manual labor would predict.

The Uneven Geography of Disruption: Identifying At-Risk “Automation Belts”

Just as deindustrialization was not a uniform national event but a concentrated regional crisis that created the “Rust Belt,” the impact of AI-driven automation will be geographically uneven. The first wave of digital automation in the late 20th century disproportionately harmed regions with high concentrations of routine manufacturing and clerical work, such as Detroit and New York.¹³

Projections for the next wave of automation suggest a similar, though distinct, pattern of geographic concentration. The communities most at risk are those whose economies are heavily reliant on industries susceptible to AI and robotics and whose workforces have lower average levels of education. Analysis indicates that less-educated “Heartland” states and smaller metropolitan areas specializing in manufacturing, logistics, and low-end services could be the hardest hit.¹³ For example, in cities like Kokomo, Indiana, and Hickory, North Carolina, over 50% of current work tasks are potentially automatable. This contrasts sharply with highly educated, tech-centric cities like San Jose, California, or Washington, D.C., where the share of vulnerable work is closer to 40%.¹³

By combining this geographical analysis with a sectoral focus, it becomes possible to identify the probable epicenters of the “Great Unwinding.” Regions whose economies are built around massive warehousing districts (such as California’s Inland Empire), major transportation hubs (like Memphis, Tennessee, or Louisville, Kentucky), or large back-office administrative centers are poised to become the 21st century’s “Automation Belts.” These areas will face the most acute fiscal and social crises, suggesting that national-level policy responses will be insufficient without targeted mechanisms to manage these concentrated regional collapses.

Occupational Category	Representative Job Titles	Total Employment (Est.)	Median Annual Wage (2023)	AI Task Exposure (% of core tasks)
High-Skill Cognitive	Logistics/Warehouse/Transportation Managers	>200,000	$101,770	>90%
Mid-Skill Administrative	Cargo Agents, Dispatchers, Billing Clerks	>500,000	$47,210 – $54,340	High (>75% in some roles)
Mid-Skill Manual	Heavy & Tractor-Trailer Truck Drivers	>2,000,000	$50,730	Low
Low-Skill Manual	Hand Laborers & Material Movers	>3,000,000	$34,970	Moderate (Physical Robotics)
High-Skill Technical	Bus & Truck Mechanics	>70,000	$55,040	~0%

Table 3: Automation Exposure in the U.S. Logistics Sector by Occupation Type. Data compiled and estimated from.¹⁰ The table highlights the profound vulnerability of high-wage managerial roles to AI-driven automation, contrasting with the lower exposure of manual and technical roles.

Obsolete Instruments: The Failure of Traditional Safety Nets in Structural Transitions

In the face of large-scale job displacement, the primary existing social safety net is the state-administered Unemployment Insurance (UI) system. However, a critical analysis of its core design reveals that UI is a tool built for a fundamentally different economic problem. Conceived to address temporary, cyclical joblessness, its mechanisms are structurally inadequate for managing the permanent, widespread displacement characteristic of the L.A.C. transition. Applying this obsolete instrument to the “Great Unwinding” would not only fail to solve the crisis but could actively worsen it, trapping individuals in a state of economic limbo while the system itself spirals toward fiscal insolvency.

The Design Limitations of Unemployment Insurance for Permanent Displacement

The Unemployment Insurance system is fundamentally designed as a short-term bridge to carry workers through temporary periods of joblessness with the expectation that they will return to similar work once the economy recovers.¹⁵ This core purpose is reflected in its key design features, all of which are misaligned with the challenge of permanent structural unemployment.

First, the duration of benefits is strictly limited. While federal extensions can be triggered during severe recessions, the standard maximum duration in most states is 26 weeks, with several states offering as little as 12 weeks.¹⁶ This timeframe is sufficient to weather a temporary layoff but is wholly inadequate for the multi-year process of retraining and career transition required when an entire job category becomes obsolete.

Second, eligibility requirements are rooted in a traditional model of employment. To qualify, workers must typically demonstrate a sufficient history of past earnings and prove they were separated from their job through no fault of their own.¹⁶ These rules can exclude gig workers, long-term unemployed individuals, and others outside the standard employer-employee relationship, and they are not designed for a scenario where “involuntary separation” becomes the permanent status for entire classes of skills.

Third, the system’s primary function is income replacement for consumption smoothing, not human capital reinvestment.¹⁸ UI provides a partial wage replacement to help households maintain a level of consumption and prevent a sharp drop in aggregate demand. It does not, however, provide the resources needed for the kind of radical reskilling, extensive education, or geographic relocation necessary to overcome a fundamental mismatch between a worker’s existing skills and the new demands of the economy.¹⁵

Cyclical vs. Structural Crises: Why Old Tools Fail New Problems

The inadequacy of UI stems from a categorical mismatch between the problem it was designed to solve and the problem posed by the L.A.C. transition. UI is an automatic stabilizer for cyclical unemployment, which is temporary job loss caused by the fluctuations of the business cycle.¹⁷ The underlying assumption is that the jobs will return when the economy recovers.

The “Great Unwinding” will be driven by structural unemployment, a long-lasting and often permanent form of joblessness caused by fundamental shifts in the economy, such as technological change.¹⁵ In this scenario, there is a deep and persistent mismatch between the skills workers possess and the skills employers need. This type of unemployment can last for decades, and the old jobs do not return.¹⁵

To apply a tool designed for a temporary, cyclical storm to a permanent change in the economic climate is a fundamental policy error. The job search requirements of UI, for instance, often compel recipients to look for jobs within their old profession—jobs that, in a structural transition, no longer exist or are rapidly disappearing. This encourages a backward-looking orientation and can trap workers in a futile search, delaying their adaptation to the new economic reality. During this period of prolonged unemployment, a worker’s skills can atrophy, making them even less employable when their limited benefits inevitably run out.¹⁵ The system, intended as a safety net, thereby becomes a perverse incentive for inaction, deepening the very structural unemployment it is meant to alleviate.

Furthermore, the financing mechanism of the UI system—primarily payroll taxes levied on employers—is itself unsustainable in a mass automation event.¹⁹ A sudden, large-scale displacement would trigger an unprecedented surge in benefit claims (outflows) while simultaneously decimating the number of human employees whose wages are taxed to fund the system (inflows). The UI system would face a dual crisis of skyrocketing demand and collapsing revenue, rendering it fiscally insolvent almost immediately and requiring massive, continuous bailouts from general funds that would themselves be under extreme pressure.

Feature	Design for Cyclical Unemployment	Requirement for Structural Unemployment
Core Problem Addressed	Temporary income loss due to business cycle downturn.	Permanent skill obsolescence due to technological paradigm shift.
Time Horizon	Short-term (typically 12-26 weeks).	Long-term (multi-year transition).
Primary Goal	Consumption smoothing; maintaining aggregate demand.	Human capital transformation; funding reskilling and relocation.
Skill Relevance	Assumes existing skills will be in demand after recovery.	Acknowledges existing skills are permanently devalued.
Funding Sustainability	Funded by payroll taxes on a large base of employed workers.	Funding base (payroll) erodes as benefit demand explodes.
Outcome for Recipient	A temporary bridge back to a similar job.	A potential trap that delays necessary career adaptation.

Table 4: Policy Mismatch: Traditional UI vs. Structural Technological Unemployment. This table illustrates the fundamental misalignment between the design of the current Unemployment Insurance system and the challenges posed by permanent, technology-driven job displacement. Sources:.¹⁵

A New Architecture for Resilience: Designing Automatic Stabilizers for the 21st Century

The failure of existing safety nets to address the challenges of a structural economic transition necessitates the design of a new class of economic shock absorbers. A resilient fiscal architecture for the 21st century requires new automatic stabilizers that are not tied to the obsolete logic of cyclical employment. By drawing on established principles of effective policy design and adapting them to the unique nature of the L.A.C. transition, it is possible to construct a blueprint for a two-pronged system: a “Municipal Backstop” to prevent the collapse of local government services and a “Phased Trigger” mechanism that smoothly manages the reallocation of purchasing power in a post-labor economy.

Principles of Effective Stabilizer Design: Timeliness, Targeting, and Triggers

Decades of economic policy analysis have established a clear set of principles for designing effective fiscal stabilizers. To be successful, such programs must be timely, targeted, and trigger-based.²¹

• Timeliness: Aid must arrive quickly after an economic downturn begins. Discretionary aid packages that require legislative action are often subject to significant delays. Historical examples, such as the federal response to the 1973-75 recession, show that aid often arrived after the downturn had already bottomed out, making it ineffective as a stabilizer and potentially contributing to post-recession inflation.²¹
• Targeting: Funds must be directed to the individuals, firms, or governments most affected by the economic shock. Poorly targeted aid, such as per-capita grants that do not account for local economic conditions, is inefficient and fails to address the most acute needs.²¹
• Triggers: The activation and deactivation of the stabilizer should be automatic, based on pre-determined economic indicators rather than political discretion. This ensures a rapid response and avoids the risk of aid continuing too long into a recovery.²³

An effective system automates the fiscal response, ensuring that support flows when and where it is needed most without the delays and political friction of the legislative process.

Blueprint for a Municipal Backstop: A Federal Emergency Stabilizer Mechanism

To prevent the catastrophic failure of local governments during the “Great Unwinding,” a federal emergency stabilizer mechanism—a “Municipal Backstop”—is required. This program would automatically route federal funds to municipalities and states facing acute fiscal distress. The design of such a mechanism does not need to be invented from scratch; its core components can be adapted from existing and proposed policies.

The Antirecession Fiscal Assistance Program (ARFA) of the 1970s, which provided unrestricted grants to state and local governments based on unemployment rates, serves as a historical precedent.²⁶ A more modern and sophisticated model can be found in a prototype formula developed by the U.S. Government Accountability Office (GAO) for automatically increasing the Federal Medical Assistance Percentage (FMAP) to states during national downturns.²²

Adapting this model, the Municipal Backstop could be designed as follows:

• Trigger Mechanism: The program would activate automatically when a clear, data-driven threshold is met. A robust trigger could be a sustained decrease in a region’s employment-to-population (EPOP) ratio or a significant rise in its unemployment rate for two consecutive quarters.²²
• Targeting and Distribution: Upon activation, funds would be allocated proportionally to the severity of the local fiscal shock. This would be measured by the percentage decline in key revenue sources like payroll and sales tax receipts, ensuring aid is effectively targeted to the hardest-hit communities.²² The funds would be delivered as unrestricted grants, providing local governments with the flexibility to backstop essential services—such as schools, public safety, and infrastructure maintenance—and prevent the downward spiral of service cuts and further economic decline.²⁶

Blueprint for Phased Triggers: Linking Dividend Funding to the Labor Share of Income

While the Municipal Backstop addresses the institutional crisis, a second, more novel stabilizer is needed to address the crisis in aggregate demand caused by the decline of wage income. This mechanism must be designed not to counteract a temporary business cycle, but to manage a permanent, one-way structural transformation. This requires a new kind of trigger linked directly to the changing composition of the L.A.C. economy.

The labor share of income—the portion of national income paid out in wages, salaries, and benefits—is a key indicator of this structural shift. Historical data from the Federal Reserve Economic Data (FRED) service shows a long-term decline in this share.²⁷ This metric can be repurposed to serve as the basis for a dynamic, self-regulating stabilizer.

The “Phased Trigger” mechanism would operate as follows:

• A historical baseline for the labor share of income (e.g., the average from a period of stable, broad-based prosperity) would be established by a national commission.
• This trigger would not be a simple on/off switch but a continuous, scaling mechanism. For every percentage point the currently measured national labor share of income falls below this established baseline, the national funding pool for a universal citizen’s dividend would automatically increase by a corresponding, pre-determined amount or percentage.

This design transforms the dividend from a static social welfare program into the primary macroeconomic stabilization tool of the L.A.C. economy. It is not a counter-cyclical stabilizer designed to fight a recession and return the economy to a prior state. It is a counter-structural stabilizer designed to facilitate the transition to a new economic paradigm. It acknowledges that the decline of labor’s role is permanent and creates a system to smoothly and automatically reallocate purchasing power from the shrinking wage economy to the citizen-consumers who must form the new base of aggregate demand. As automation’s share of the economy grows, this mechanism ensures that the population’s share of the proceeds grows in lockstep, managing the transition rather than resisting it.

Component	Design Specification	Rationale / Precedent
Program Name	Emergency Municipal Backstop Act	To provide immediate fiscal relief and prevent public service insolvency.
Trigger Mechanism	Automatic activation when a state’s employment-to-population (EPOP) ratio shows a sustained decrease below a historical baseline for two consecutive quarters.	Based on the GAO’s FMAP prototype, which uses EPOP as a timely and objective indicator of economic distress.22 Avoids legislative lag.21
Targeting Formula	Aid allocated to municipalities based on the percentage decline in their payroll and sales tax revenues relative to a pre-crisis baseline.	Ensures aid is proportional to the severity of the fiscal shock, a key principle of effective design.22 Avoids flawed per-capita allocation models.21
Distribution Method	Unrestricted federal grants directly to municipal and state governments.	Provides flexibility to backstop essential local services (police, fire, schools) as needed.26 Modeled on the Antirecession Fiscal Assistance Program (ARFA).26
Deactivation Trigger	Automatic deactivation or phase-out when the state’s EPOP ratio stabilizes or returns above the trigger threshold.	Ensures aid is temporary and does not contribute to post-crisis inflation.21
Governance & Oversight	Administered by the Treasury Department with oversight from a non-partisan body to monitor data and ensure formulaic integrity.	Provides accountability and prevents politicization of aid distribution.

Table 5: Proposed Design for a Municipal Fiscal Stabilizer Mechanism. This table provides a blueprint for a concrete policy solution to prevent the collapse of local government services during the L.A.C. transition, grounding the proposal in established principles of fiscal policy design. Sources:.²¹

Recommendations and Implementation Pathways

The transition to a post-labor economy represents a fundamental challenge to the fiscal and social structures of the 21st century. Navigating the “Great Unwinding” without succumbing to the cascading failures witnessed during the deindustrialization era requires a proactive and deliberate redesign of our economic architecture. The analysis presented in this report leads to a set of actionable recommendations for policymakers at all levels of government, alongside a recognition of the data infrastructure and political will required for their successful implementation.

Policy Recommendations for Federal, State, and Municipal Governments

A coordinated, multi-level policy response is necessary to build a resilient framework for the post-labor transition.

• Federal Government: The primary responsibility for managing this national structural transition lies at the federal level. Congress should move to legislate a permanent, trigger-based automatic stabilizer program for state and local governments, modeled on the Emergency Municipal Backstop outlined in this report. This would create a predictable and reliable mechanism to prevent regional fiscal collapses from destabilizing the national economy. Concurrently, the federal government should establish a non-partisan national commission tasked with defining the technical parameters—including the historical baseline and scaling factor—for the labor-share-linked funding mechanism for a universal citizen’s dividend.
• State Governments: States can take immediate steps to improve their own fiscal resilience. Many state aid programs to local governments are currently pro-cyclical, meaning aid declines during recessions precisely when localities need it most.²⁶ States should reform these programs to be counter-cyclical, providing a crucial first line of defense against local fiscal distress. Furthermore, states can prepare to leverage future federal action by developing and maintaining a catalog of “shovel-ready” infrastructure projects that could be immediately activated by federal infrastructure stabilizers during a downturn.²⁸
• Municipal Governments: Local governments are on the front lines of this transition and must act to understand and mitigate their unique vulnerabilities. Municipalities should conduct detailed fiscal vulnerability assessments, mapping their revenue dependency against the automation exposure of their key local industries. Where possible, they should seek to diversify their revenue bases. Most importantly, local leaders must become powerful advocates for the creation of the federal backstop programs that will be essential for their long-term survival.

Data Infrastructure Requirements for a Responsive System

The effectiveness of the proposed automatic stabilizers is entirely dependent on the availability of high-frequency, granular, and reliable economic data. A 21st-century fiscal architecture requires a 21st-century data infrastructure. To ensure the timely activation and accurate targeting of aid, federal statistical agencies must be empowered and funded to collect and disseminate:

• Real-time local tax receipt data: Monthly or even weekly data on payroll and sales tax collections at the municipal level would allow for the immediate identification of fiscal distress.
• Granular employment data: Detailed data on employment levels and wage distribution by sector and occupation for every metropolitan statistical area is needed to accurately model automation impacts and target aid effectively.

Investing in this data infrastructure is not a secondary concern; it is a prerequisite for the functioning of a responsive and resilient economic management system.

Navigating the Political Economy of the Transition

The technical design of these new stabilizers, while critical, is only half the challenge. Their implementation will require navigating a complex and often polarized political landscape. Public opinion data from 2017 shows that while a majority of Americans (58%) support limits on automation and believe the government has an obligation to help displaced workers, there are sharp partisan divides on specific solutions.²⁹ For instance, while 77% of Democrats supported a guaranteed income, only 38% of Republicans did.²⁹

To build the broad coalition necessary for passage, these proposals must be framed not as welfare or handouts, but as pragmatic, necessary upgrades to our national economic infrastructure—akin to the creation of the Federal Reserve or the interstate highway system. They are tools for ensuring macroeconomic stability and continued prosperity in a new economic paradigm. The debate over competing alternatives, such as a federal Job Guarantee [30, 31, 32] versus a Universal Basic Income [33], must also be navigated. The hybrid system proposed—combining direct income support via a dividend with institutional support via municipal backstops—may offer a politically viable path forward by addressing both individual needs and community stability. Ultimately, the greatest challenge will be to foster a political consensus that recognizes the scale of the coming transition and embraces the need for bold, structural solutions before the “Great Unwinding” is already upon us.

Works cited

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2. State and Local Tax Collections Per Capita by State, 2025 – Tax Foundation, accessed September 2, 2025, https://taxfoundation.org/data/all/state/state-local-tax-collections-per-capita/
3. State & Local Revenue – NASRA, accessed September 2, 2025, https://www.nasra.org/revenue
4. Local Government Revenue Sources – Cities, accessed September 2, 2025, https://www.gfoa.org/revenue-dashboard-cities
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