Population as the Primary and Predictable Driver of Local Government Forecasting

December 12, 2025.Reading time 35 minutes.

A collaboration between Lewis McLain & AI

A technical framework for staffing, facilities, and cost projection

Abstract

In local government forecasting, population is the dominant driver of service demand, staffing requirements, facility needs, and operating costs. While no municipal system can be forecast with perfect precision, population-based models—when properly structured—produce estimates that are sufficiently accurate for planning, budgeting, and capital decision-making. Crucially, population growth in cities is not a sudden or unknowable event.

Through annexation, zoning, platting, infrastructure construction, utility connections, and certificates of occupancy, population arrival is observable months or years in advance. This paper presents population not merely as a driver, but as a leading indicator, and demonstrates how cities can convert development approvals into staged population forecasts that support rational staffing, facility sizing, capital investment, and operating cost projections.

1. Introduction: Why population sits at the center

Local governments exist to provide services to people. Police protection, fire response, streets, parks, water, sanitation, administration, and regulatory oversight are all mechanisms for supporting a resident population and the activity it generates. While policy choices and service standards influence how services are delivered, the volume of demand originates with population.

Practitioners often summarize this reality informally:

“Tell me the population, and I can tell you roughly how many police officers you need.
If I know the staff, I can estimate the size of the building.
If I know the size, I can estimate the construction cost.
If I know the size, I can estimate the electricity bill.”

This paper formalizes that intuition into a defensible forecasting framework and addresses a critical objection: population is often treated as uncertain or unknowable. In practice, population growth in cities is neither sudden nor mysterious—it is permitted into existence through public processes that unfold over years.

2. Population as a base driver, not a single-variable shortcut

Population does not explain every budget line, but it explains most recurring demand when paired with a small number of modifiers.

At its core, many municipal services follow this structure:

Total Demand=α+β⋅Population

Where:

α (fixed minimum) represents baseline capacity required regardless of size (minimum staffing, governance, 24/7 coverage).
β (variable component) represents incremental demand generated by each additional resident.

This structure explains why:

Small cities appear “overstaffed” per capita (fixed minimum dominates).
Mid-sized and large cities stabilize into predictable staffing ratios.
Growth pressures emerge when population increases faster than capacity adjustments.

Population therefore functions as the load variable of local government, analogous to demand in utility planning.

3. Why population reliably predicts service demand

3.1 People generate transactions

Residents generate:

Calls for service
Utility usage
Permits and inspections
Court activity
Recreation participation
Library circulation
Administrative transactions (HR, payroll, finance, IT)

While individual events vary, aggregate demand scales with population.

3.2 Capacity, not consumption, drives budgets

Municipal budgets fund capacity, not just usage:

Staff must be available before calls occur
Facilities must exist before staff are hired
Vehicles and equipment must be in place before service delivery

Capacity decisions are inherently population-driven.

4. Population growth is observable before it arrives

A defining feature of local government forecasting—often underappreciated—is that population growth is authorized through public approvals long before residents appear in census or utility data.

Population does not “arrive”; it progresses through a pipeline.

5. The development pipeline as a population forecasting timeline

5.1 Annexation: strategic intent (years out)

Annexation establishes:

Jurisdictional responsibility
Long-term service obligations
Future land-use authority

While annexation does not create immediate population, it signals where population will eventually be allowed.

Forecast role:

Long-range horizon marker
Infrastructure and service envelope planning
Typical lead time: 3–10 years

5.2 Zoning: maximum theoretical population

Zoning converts land into entitled density.

From zoning alone, cities can estimate:

Maximum dwelling units
Maximum population at buildout
Long-run service ceilings

Zoning defines upper bounds, even if timing is uncertain.

Forecast role:

Long-range capacity planning
Useful for master plans and utility sizing
Typical lead time: 3–7 years

5.3 Preliminary plat: credible development intent

Preliminary plat approval signals:

Developer capital commitment
Defined lot counts
Identified phasing

Population estimates become quantifiable, even if delivery timing varies.

Forecast role:

Medium-high certainty population
First stage for phased population modeling
Typical lead time: 1–3 years

5.4 Final plat: scheduled population

Final plat approval:

Legally creates lots
Locks in density and configuration
Triggers infrastructure construction
Impact Fees & other costs are committed

At this point, population arrival is no longer speculative.

Forecast role:

High-confidence population forecasting
Suitable for annual budget and staffing models
Typical lead time: 6–24 months

5.5 Infrastructure construction: timing constraints

Once streets, utilities, and drainage are built, population arrival becomes physically constrained by construction schedules.

Forecast role:

Narrow timing window
Supports staffing lead-time decisions
Typical lead time: 6–18 months

5.6 Water meter connections: imminent occupancy

Water meters are one of the most reliable near-term indicators:

Each residential meter ≈ one household
Installations closely precede vertical construction

Forecast role:

Quarterly or monthly population forecasting
Just-in-time operational scaling
Typical lead time: 1–6 months

5.7 Certificates of Occupancy: population realized

Certificates of occupancy convert permitted population into actual population.

At this point:

Service demand begins immediately
Utility consumption appears
Forecasts can be validated

Forecast role:

Confirmation and calibration
Not prediction

6. Population forecasting as a confidence ladder

Development Stage	Population Certainty	Timing Precision	Planning Use
Annexation	Low	Very low	Strategic
Zoning	Low–Medium	Low	Capacity envelopes
Preliminary Plat	Medium	Medium	Phased planning
Final Plat	High	Medium–High	Budget & staffing
Infrastructure Built	Very High	High	Operational prep
Water Meters	Extremely High	Very High	Near-term ops
COs	Certain	Exact	Validation

Population forecasting in cities is therefore graduated, not binary.

7. From population to staffing

Once population arrival is staged, staffing can be forecast using service-specific ratios and fixed minimums.

7.1 Police example (illustrative ranges)

Sworn officers per 1,000 residents commonly stabilize within broad bands depending on service level and demand, also tied to known local ratios:

Lower demand: ~1.2–1.8
Moderate demand: ~1.8–2.4
High demand: ~2.4–3.5+

Civilian support staff often scale as a fraction of sworn staffing.

The appropriate structure is: $Officers = \alpha_{police} + \beta_{police} \cdot Population$ Officers=αpolice+βpolice⋅Population

Where α accounts for minimum 24/7 coverage and supervision.

7.2 General government staffing

Administrative staffing scales with:

Population
Number of employees
Asset inventory
Transaction volume

A fixed core plus incremental per-capita growth captures this reality more accurately than pure ratios.

8. From staffing to facilities

Facilities are a function of:

Headcount
Service configuration
Security and public access needs

A practical planning method: $Facility\ Size = FTE \cdot Gross\ SF\ per\ FTE$ Facility Size=FTE⋅Gross SF per FTE

Typical blended civic office planning ranges usually fall within:

~175–300 gross SF per employee

Specialized spaces (dispatch, evidence, fleet, courts) are layered on separately.

9. From facilities to capital and operating costs

9.1 Capital costs

Capital expansion costs are typically modeled as: $Capex = Added\ SF \cdot Cost\ per\ SF \cdot (1 + Soft\ Costs)$ Capex=Added SF⋅Cost per SF⋅(1+Soft Costs)

Where soft costs include design, permitting, contingencies, and escalation.

9.2 Operating costs

Facility operating costs scale predictably with size:

Electricity: kWh per SF per year
Maintenance: % of replacement value or $/SF
Custodial: $/SF
Lifecycle renewals

Electricity alone can be reasonably estimated as: $Annual\ Cost = SF \cdot kWh/SF \cdot \$/kWh$ Annual Cost=SF⋅kWh/SF⋅$/kWh

This is rarely exact—but it is directionally reliable.

10. Key modifiers that refine population models

Population alone is powerful but incomplete. High-quality forecasts adjust for:

Density and land use
Daytime population and employment
Demographics
Service standards
Productivity and technology
Geographic scale (lane miles, acres)

These modifiers refine, but do not replace, population as the base driver.

11. Why growth surprises cities anyway

When cities claim growth was “unexpected,” the issue is rarely lack of information. More often:

Development signals were not integrated into finance models
Staffing and capital planning lagged approvals
Fixed minimums were ignored
Threshold effects (new stations, expansions) were deferred too long

Growth that appears sudden is usually forecastable growth that was not operationalized.

12. Conclusion

Population is the primary driver of local government demand, but more importantly, it is a predictable driver. Through annexation, zoning, platting, infrastructure construction, utility connections, and certificates of occupancy, cities possess a multi-year advance view of population arrival.

This makes it possible to:

Phase staffing rationally
Time facilities before overload
Align capital investment with demand
Improve credibility with councils, auditors, and rating agencies

In local government, population growth is not a surprise. It is a permitted, engineered, and scheduled outcome of public decisions. A forecasting system that treats population as both a driver and a leading indicator is not speculative—it is simply paying attention to the city’s own approvals.

Appendix A

Defensibility of Population-Driven Forecasting Models

A response framework for auditors, rating agencies, and governing bodies

Purpose of this appendix

This appendix addresses a common concern raised during budget reviews, audits, bond disclosures, and council deliberations:

“Population-based forecasts seem too simplistic or speculative.”

The purpose here is not to argue that population is the only factor affecting local government costs, but to demonstrate that population-driven forecasting—when anchored to development approvals and adjusted for service standards—is methodologically sound, observable, and conservative.

A.1 Population forecasting is not speculative in local government

A frequent misconception is that population forecasts rely on demographic projections or external estimates. In practice, this model relies primarily on the city’s own legally binding approvals.

Population growth enters the forecast only after it has passed through:

Annexation agreements
Zoning entitlements
Preliminary and final plats
Infrastructure construction
Utility connections
Certificates of occupancy

These are public, documented actions, not assumptions.

Key distinction for reviewers:
This model does not ask “How fast might the city grow?”
It asks “What growth has the city already approved, and when will it become occupied?”

A.2 Population is treated as a leading indicator, not a lagging one

Traditional population measures (census counts, ACS estimates) are lagging indicators. This model explicitly avoids relying on those for near-term forecasting.

Instead, it uses development milestones as leading indicators, each with increasing certainty and narrower timing windows.

For audit and disclosure purposes:

Early-stage entitlements affect only long-range capacity planning
Staffing and capital decisions are triggered only at later, high-certainty stages
Near-term operating impacts are tied to utility connections and COs

This layered approach prevents premature spending while avoiding reactive under-staffing.

A.3 Fixed minimums prevent over-projection in small or slow-growth cities

A common audit concern is that per-capita models overstate staffing needs.

This model explicitly separates:

Fixed baseline capacity (α)
Incremental population-driven capacity (β)

This structure:

Prevents unrealistic staffing increases in early growth stages
Accurately reflects real-world minimum staffing requirements
Explains why per-capita ratios vary by city size

Auditors should note that this approach is more conservative than straight-line per-capita extrapolation.

A.4 Service standards are explicit policy inputs, not hidden assumptions

Population does not automatically dictate staffing levels. Staffing reflects policy decisions.

This model requires the city to explicitly state:

Response time targets
Service frequency goals
Coverage expectations
Hours of operation

As a result:

Changes in staffing can be clearly attributed to either population growth or policy change
Council decisions are transparently reflected in forecasts
The model separates “growth pressure” from “service enhancements or reductions”

This clarity improves accountability rather than obscuring it.

A.5 Facilities and capital projections follow staffing, not speculation

Another concern raised by reviewers is that population forecasts may be used to justify premature capital expansion.

This model deliberately enforces a sequencing discipline:

Population approvals observed
Staffing thresholds reached
Facility capacity constraints identified
Capital expansion triggered

Facilities are not expanded because population might grow, but because staffing—already justified by approved growth—can no longer be accommodated.

This mirrors best practices in asset management and avoids front-loading debt.

A.6 Operating cost estimates use industry-standard unit costs

Electricity, maintenance, custodial, and lifecycle costs are estimated using:

Per-square-foot benchmarks
Historical city utility data where available
Conservative unit assumptions

These are not novel or experimental methods. They are the same unit-cost techniques commonly used in:

CIP planning
Facility condition assessments
Energy benchmarking
Budget impact statements

Auditors should view these estimates as planning magnitudes, not precise bills—and that distinction is explicitly stated in the model documentation.

A.7 The model is testable and falsifiable

A major strength of this approach is that it can be validated against actual outcomes.

As certificates of occupancy are issued:

Actual population arrival can be compared to forecasts
Staffing changes can be reconciled
Utility consumption can be measured

This allows:

Annual recalibration
Error tracking
Continuous improvement

Models that can be tested and corrected are inherently more defensible than opaque judgment-based forecasts.

A.8 Why this approach aligns with rating-agency expectations

Bond rating agencies consistently emphasize:

Predictability
Governance discipline
Forward planning
Avoidance of reactive financial decisions

This framework demonstrates:

Awareness of growth pressures well in advance
Phased responses rather than abrupt spending
Clear linkage between approvals, staffing, and capital
Conservative treatment of uncertainty

As such, population-driven forecasting anchored to development approvals should be viewed as a credit positive, not a risk.

A.9 Summary for reviewers

For audit, disclosure, and governance purposes, the following conclusions are reasonable:

Population growth in cities is observable years in advance through public approvals.
Using approved development as a population driver is evidence-based, not speculative.
Fixed minimums and service-level inputs prevent mechanical over-projection.
Staffing precedes facilities; facilities precede capital.
Operating costs scale predictably with assets and space.
The model is transparent, testable, and adjustable.

Therefore:
A population-driven forecasting model of this type represents a prudent, defensible, and professionally reasonable approach to long-range municipal planning.

Appendix B

Consequences of Failing to Anticipate Population Growth

A diagnostic review of reactive municipal planning

Purpose of this appendix

This appendix describes common failure patterns observed in cities that do not systematically link development approvals to population, staffing, and facility planning. These outcomes are not the result of negligence or bad intent; they typically arise from fragmented information, short planning horizons, or the absence of an integrated forecasting framework.

The patterns described below are widely recognized in municipal practice and are offered to illustrate the practical risks of reactive planning.

B.1 “Surprise growth” that was not actually a surprise

A frequent narrative in reactive cities is that growth “arrived suddenly.” In most cases, the growth was visible years earlier through zoning approvals, plats, or utility extensions but was not translated into staffing or capital plans.

Common indicators:

Approved subdivisions not reflected in operating forecasts
Development tracked only by planning staff, not finance or operations
Population discussed only after occupancy

Consequences:

Budget shocks
Emergency staffing requests
Loss of credibility with governing bodies

B.2 Knee-jerk staffing reactions

When growth impacts become unavoidable, reactive cities often respond through hurried staffing actions.

Typical symptoms:

Mid-year supplemental staffing requests
Heavy reliance on overtime
Accelerated hiring without workforce planning
Training pipelines overwhelmed

Consequences:

Elevated labor costs
Increased burnout and turnover
Declining service quality during growth periods
Inefficient long-term staffing structures

B.3 Under-sizing followed by over-correction

Without forward planning, cities often alternate between two extremes:

Under-sizing due to conservative or delayed response
Over-sizing in reaction to service breakdowns

Examples:

Facilities built too small “to be safe”
Rapid expansions shortly after completion
Swing from staffing shortages to excess capacity

Consequences:

Higher lifecycle costs
Poor space utilization
Perception of waste or mismanagement

B.4 Obsolete facilities at the moment of completion

Facilities planned without reference to future population often open already constrained.

Common causes:

Planning based on current headcount only
Ignoring entitled but unoccupied development
Failure to include expansion capability

Consequences:

Expensive retrofits
Disrupted operations during expansion
Shortened facility useful life

This is one of the most costly errors because capital investments are long-lived and difficult to correct.

B.5 Deferred capital followed by crisis-driven spending

Reactive cities often delay capital investment until systems fail visibly.

Typical patterns:

Fire stations added only after response times degrade
Police facilities expanded only after overcrowding
Utilities upgraded only after service complaints

Consequences:

Emergency procurement
Higher construction costs
Increased debt stress
Lost opportunity for phased financing

B.6 Misalignment between departments

When population intelligence is not shared across departments:

Planning knows what is coming
Finance budgets based on current year
Operations discover impacts last

Consequences:

Conflicting narratives to council
Fragmented decision-making
Reduced trust between departments

Population-driven forecasting provides a common factual baseline.

B.7 Overreliance on lagging indicators

Reactive cities often rely heavily on:

Census updates
Utility consumption after occupancy
Service call increases

These indicators confirm growth after it has already strained capacity.

Consequences:

Persistent lag between demand and response
Structural understaffing
Continual “catch-up” budgeting

B.8 Political whiplash and credibility erosion

Unanticipated growth pressures often force councils into repeated difficult votes:

Emergency funding requests
Mid-year budget amendments
Rapid debt authorizations

Over time, this leads to:

Voter skepticism
Council fatigue
Reduced tolerance for legitimate future investments

Planning failures become governance failures.

B.9 Inefficient use of taxpayer dollars

Ironically, reactive planning often costs more, not less.

Cost drivers include:

Overtime premiums
Compressed construction schedules
Retrofit and rework costs
Higher borrowing costs due to rushed timing

Proactive planning spreads costs over time and reduces risk premiums.

B.10 Organizational stress and morale impacts

Staff experience growth pressures first.

Observed impacts:

Chronic overtime
Inadequate workspace
Equipment shortages
Frustration with leadership responsiveness

Over time, this contributes to:

Higher turnover
Loss of institutional knowledge
Reduced service consistency

B.11 Why these failures persist

These patterns are not caused by incompetence. They persist because:

Growth information is siloed
Forecasting is viewed as speculative
Political incentives favor short-term restraint
Capital planning horizons are too short

Absent a formal framework, cities default to reaction.

B.12 Summary for governing bodies

Cities that do not integrate development approvals into population-driven forecasting commonly experience:

Perceived “surprise” growth
Emergency staffing responses
Repeated under- and over-sizing
Facilities that age prematurely
Higher long-term costs
Organizational strain
Reduced public confidence

None of these outcomes are inevitable. They are symptoms of not using information the city already has.

B.13 Closing observation

The contrast between proactive and reactive cities is not one of optimism versus pessimism. It is a difference between:

Anticipation versus reaction
Sequencing versus scrambling
Planning versus explaining after the fact

Population-driven forecasting does not eliminate uncertainty. It replaces surprise with preparation.

Appendix C

Population Readiness & Forecasting Discipline Checklist

A self-assessment for proactive versus reactive cities

Purpose:
This checklist allows a city to evaluate whether it is systematically anticipating population growth—or discovering it after impacts occur. It is designed for use by city management teams, finance directors, auditors, and governing bodies.

How to use:
For each item, mark:

✅ Yes / In place
⚠️ Partially / Informal
❌ No / Not done

Patterns matter more than individual answers.

Section 1 — Visibility of Future Population

C-1 Do we maintain a consolidated list of annexed, zoned, and entitled land with estimated buildout population?

C-2 Are preliminary and final plats tracked in a format usable by finance and operations (not just planning)?

C-3 Do we estimate population by development phase, not just at full buildout?

C-4 Is there a documented method for converting lots or units into population (household size assumptions reviewed periodically)?

C-5 Do we distinguish between long-range potential growth and near-term probable growth?

Red flag:
Population is discussed primarily in narrative terms (“fast growth,” “slowing growth”) rather than quantified and staged.

Section 2 — Timing and Lead Indicators

C-6 Do we identify which development milestone triggers planning action (e.g., preliminary plat vs final plat)?

C-7 Are infrastructure completion schedules incorporated into population timing assumptions?

C-8 Are water meter installations or equivalent utility connections tracked and forecasted?

C-9 Do we use certificates of occupancy to validate and recalibrate population forecasts annually?

C-10 Is population forecasting treated as a rolling forecast, not a once-per-year estimate?

Red flag:
Population is updated only when census or ACS data is released.

Section 3 — Staffing Linkage

C-11 Does each major department have an identified population or workload driver?

C-12 Are fixed minimum staffing levels explicitly separated from growth-driven staffing?

C-13 Are staffing increases tied to forecasted population arrival, not service breakdowns?

C-14 Do hiring plans account for lead times (recruitment, academies, training)?

C-15 Can we explain recent staffing increases as either:

population growth, or
explicit policy/service-level changes?

Red flag:
Staffing requests frequently cite “we are behind” without reference to forecasted growth.

Section 4 — Facilities and Capital Planning

C-16 Are facility size requirements derived from staffing projections, not current headcount?

C-17 Do capital plans include expansion thresholds (e.g., headcount or service load triggers)?

C-18 Are new facilities designed with future expansion capability?

C-19 Are entitled-but-unoccupied developments considered when evaluating future facility adequacy?

C-20 Do we avoid building facilities that are at or near capacity on opening day?

Red flag:
Facilities require major expansion within a few years of completion.

Section 5 — Operating Cost Awareness

C-21 Are operating costs (utilities, maintenance, custodial) modeled as a function of facility size and assets?

C-22 Are utility cost impacts of expansion estimated before facilities are approved?

C-23 Do we understand how population growth affects indirect departments (HR, IT, finance)?

C-24 Are lifecycle replacement costs considered when adding capacity?

Red flag:
Operating cost increases appear as “unavoidable surprises” after facilities open.

Section 6 — Cross-Department Integration

C-25 Do planning, finance, and operations use the same population assumptions?

C-26 Is growth discussed in joint meetings, not only within planning?

C-27 Does finance receive regular updates on development pipeline status?

C-28 Are growth assumptions documented and shared, not implicit or informal?

Red flag:
Different departments give different growth narratives to council.

Section 7 — Governance and Transparency

C-29 Can we clearly explain to council why staffing or capital is needed before service failure occurs?

C-30 Are population-driven assumptions documented in budget books or CIP narratives?

C-31 Do we distinguish between:

growth-driven needs, and
discretionary service enhancements?

C-32 Can auditors or rating agencies trace growth-related decisions back to documented approvals?

Red flag:
Growth explanations rely on urgency rather than evidence.

Section 8 — Validation and Learning

C-33 Do we compare forecasted population arrival to actual COs annually?

C-34 Are forecasting errors analyzed and corrected rather than ignored?

C-35 Do we adjust household size, absorption rates, or timing assumptions over time?

Red flag:
Forecasts remain unchanged year after year despite clear deviations.

Scoring Interpretation (Optional)

Mostly ✅ → Proactive, anticipatory city
Mix of ✅ and ⚠️ → Partially planned, risk of reactive behavior
Many ❌ → Reactive city; growth will feel like a surprise

A city does not need perfect scores. The presence of structure, documentation, and sequencing is what matters.

Closing Note for Leadership

If a city can answer most of these questions affirmatively, it is not guessing about growth—it is managing it. If many answers are negative, the city is likely reacting to outcomes it had the power to anticipate.

Population growth does not cause planning problems.
Ignoring known growth signals does.

Appendix D

Population-Driven Planning Maturity Model

A framework for assessing and improving municipal forecasting discipline

Purpose of this appendix

This maturity model describes how cities evolve in their ability to anticipate population growth and translate it into staffing, facility, and financial planning. It recognizes that most cities are not “good” or “bad” planners; they are simply at different stages of organizational maturity.

Each level builds logically on the prior one. Advancement does not require perfection—only structure, integration, and discipline.

Level 1 — Reactive City

“We didn’t see this coming.”

Characteristics

Population discussed only after impacts are felt
Reliance on census or anecdotal indicators
Growth described qualitatively (“exploding,” “slowing”)
Staffing added only after service failure
Capital projects triggered by visible overcrowding
Frequent mid-year budget amendments

Typical behaviors

Emergency staffing requests
Heavy overtime usage
Facilities opened already constrained
Surprise operating cost increases

Organizational mindset

Growth is treated as external and unpredictable.

Risks

Highest long-term cost
Lowest credibility with councils and rating agencies
Chronic organizational stress

Level 2 — Aware but Unintegrated City

“Planning knows growth is coming, but others don’t act on it.”

Characteristics

Development pipeline tracked by planning
Finance and operations not fully engaged
Growth acknowledged but not quantified in budgets
Capital planning still reactive
Limited documentation of assumptions

Typical behaviors

Late staffing responses despite known development
Facilities planned using current headcount
Disconnect between planning reports and budget narratives

Organizational mindset

Growth is known, but not operationalized.

Risks

Continued surprises
Internal frustration
Mixed messages to council

Level 3 — Structured Forecasting City

“We model growth, but execution lags.”

Characteristics

Population forecasts tied to development approvals
Preliminary staffing models exist
Fixed minimums recognized
Capital needs identified in advance
Forecasts updated annually

Typical behaviors

Better budget explanations
Improved CIP alignment
Still some late responses due to execution gaps

Organizational mindset

Growth is forecastable, but timing discipline is still developing.

Strengths

Credible analysis
Reduced emergencies
Clearer governance conversations

Level 4 — Integrated Planning City

“Approvals, staffing, and capital move together.”

Characteristics

Development pipeline drives population timing
Staffing plans phased to population arrival
Facility sizing based on projected headcount
Operating costs modeled from assets
Cross-department coordination is routine

Typical behaviors

Hiring planned ahead of demand
Facilities open with expansion capacity
Capital timed to avoid crisis spending
Clear audit trail from approvals to costs

Organizational mindset

Growth is managed, not reacted to.

Benefits

Stable service delivery during growth
Higher workforce morale
Strong credibility with governing bodies

Level 5 — Adaptive, Data-Driven City

“We learn, recalibrate, and optimize continuously.”

Characteristics

Rolling population forecasts
Development milestones tracked in near-real time
Annual validation against COs and utility data
Forecast errors analyzed and corrected
Scenario modeling for alternative growth paths

Typical behaviors

Minimal surprises
High confidence in long-range plans
Early identification of inflection points
Proactive communication with councils and investors

Organizational mindset

Growth is a controllable system, not a threat.

Benefits

Lowest lifecycle cost
Highest service reliability
Institutional resilience

Summary Table

Level	Description	Core Risk
1	Reactive	Crisis-driven decisions
2	Aware, unintegrated	Late responses
3	Structured	Execution lag
4	Integrated	Few surprises
5	Adaptive	Minimal risk

Key Insight

Most cities are not failing—they are stuck between Levels 2 and 3. The largest gains come not from sophisticated analytics, but from integration and timing discipline.

Progression does not require:

Perfect forecasts
Advanced software
Large consulting engagements

It requires:

Using approvals the city already grants
Sharing population assumptions across departments
Sequencing decisions intentionally

Closing Observation

Cities do not choose whether they grow. They choose whether growth feels like a surprise or a scheduled event.

This maturity model makes that choice visible.

Affordability, Not Ideology: What the 2025 New York City Election Might Be Really Saying

November 6, 2025.Reading time 13 minutes.

A collaboration between Lewis McLain & AI

I find it easy, given my own anti-socialist and anti-communist persuasion, to dismiss the recent New York City election as another swing toward unsustainable government expansion. Yet, setting that aside for a moment, can I look at the undercurrents and learn something? It is with that tone that I ask the reader to do the same.

1. Beneath the Headlines

The surface story was political: a progressive candidate, Zohran Mamdani, wins the mayor’s office on a platform of rent freezes and expanded public services. The deeper story, however, may have little to do with ideology and everything to do with survival.

By mid-2025, Manhattan’s median rent had climbed above $5,000. Outer-borough rents rose by double digits. Nearly one-third of New York households spent more than 30 % of their income on housing. Real wages, adjusted for inflation, stagnated. Even a two-income household found itself slipping behind.

So, when voters filled out their ballots, were they embracing socialism—or simply trying to breathe? Never underestimate the mind of one gasping for air.

2. The Language of Livability

Affordability has quietly replaced ideology as the true dividing line in American cities. Once, debates centered on party and policy; today, they revolve around whether an ordinary worker can stay in the place they serve. It’s not “left” or “right”—it’s whether the math still works.

When groceries, utilities, childcare, and transportation rise faster than wages, the question becomes practical, not philosophical: How long can I keep this up?

And while official inflation may appear calm at 2–3 %, that number hides what many households actually feel—what I call “personal inflation.” It’s the unmeasured rise in daily living costs that comes from housing, insurance, food, and utilities outpacing wages year after year. (See Appendix A.)

3. Misreading the Message

Some national voices called the election a socialist surge. Perhaps that’s a comforting narrative for those who like clean storylines. But what if it was instead a referendum on affordability itself—a protest against unlivable economics, not capitalism?

People who can no longer afford their city don’t vote for theory; they vote for relief. To interpret that desperation as a political movement risks missing the lesson entirely.

4. A Mirror for Other States

It is no secret that Texas has been one of the largest beneficiaries of the affordability exodus from both New York and California. Companies, families, and entire industries have moved to Texas in search of lower taxes, less regulation, and a livable cost structure. That success is worth celebrating—but it should also serve as a warning.

When infrastructure begins to wear out, when roads, power grids, and water systems reach their limits, and when taxes inevitably rise to repair them, the same logic that drew businesses here could just as easily justify their departure. If our cost of living rises unchecked, Texas could become tomorrow’s cautionary tale.

Economic migration obeys no loyalty. It follows cost, opportunity, and predictability.

5. The Numbers Behind the Feeling

Nationwide indicators tell the same story:

The United States faces a housing shortfall of roughly 4.5 million homes.
Nearly half of renters are now “cost-burdened,” spending over 30 % of income on housing.
Real wage growth since the pandemic lags inflation by about one percentage point per year.
In large metros, home-price-to-income ratios have hit historic highs, locking out first-time buyers.

These are not partisan statistics. They describe a system under strain. The vote in New York, then, may have been less about political faith than about financial fatigue—and compounded by the gap between official and personal inflation.

6. What a Professional Reader Might Conclude

A city—or a state—cannot sustain endless cost escalation without losing its workforce and its investors. The “affordability signal” from New York should not alarm us ideologically but alert us practically. It says: If you neglect cost control, people and capital will find somewhere else to go.

For policymakers, that means:

Treat affordability as infrastructure—as essential to maintain as highways or water lines.
Encourage balanced housing growth, removing unnecessary zoning friction while preserving standards.
Manage public debt and taxation with restraint, so long-term costs don’t erode the very advantage that drew new residents and firms.
Invest in maintenance before crisis, since deferred repairs always cost more later.

These aren’t partisan remedies; they’re managerial ones.

7. Asking Instead of Declaring

Still, the most productive posture may not be to prescribe but to ponder. What if the real issue beneath New York’s vote was not belief but endurance? What if the new political currency isn’t ideology but livability? Could affordability, quietly, be the next great civic value—the measure of whether a city still works for the people who build it?

If so, the warning is clear and shared: when living becomes unaffordable, no philosophy can hold a city together.

8. Closing Reflection

So, before we dismiss the New York outcome as a drift toward socialism, we might instead see it as a flare on the economic horizon. It reminds us that affordability—whether in New York, Los Angeles, Austin, or Dallas—is not a slogan but a threshold. Cross it, and even the most loyal residents and businesses will leave.

The lesson is not political; it is operational. Affordability is the quiet foundation on which every ideology, every enterprise, and every community must stand.

Appendix A: Personal Inflation — The Hidden Multiplier of the Affordability Crisis

Every few weeks a headline reassures us that inflation is “under control,” that the national rate has settled near 2 % or 3 %. Yet nearly everyone you meet feels poorer, not richer. The explanation is both simple and unsettling: the inflation that matters most is personal, not official.

1. The Illusion of Average

The Consumer Price Index (CPI) measures national averages across hundreds of goods and services. It was never designed to mirror the reality of any one household. It’s the economic equivalent of averaging the temperatures of Alaska and Arizona and calling it a mild day.

The CPI basket assigns weights based on the average U.S. household—an imaginary blend that includes homeowners, renters, retirees, students, and high earners alike. But your household’s spending profile—your personal basket—is unique. When your largest costs are housing, insurance, utilities, and groceries, the “average” CPI number becomes almost meaningless.

2. The Real Basket Most Families Carry

Consider two households:

Household A, a retired couple with no mortgage and stable investments, spends mainly on travel, entertainment, and medical care.
Household B, a working family renting a home, paying for childcare, commuting daily, and carrying health and auto insurance.

Both face an “official” inflation rate of 2 %, yet Household B experiences cost increases closer to 8 – 10 %. Why? Because its essentials—housing, food, energy, and insurance—rise far faster than the discretionary goods that dominate CPI weightings. Economists call this the distributional effect of inflation: the same average conceals drastically different outcomes depending on what you buy.

3. Lagged Housing, Hidden Pain

Housing is the largest single cost in most budgets, yet it enters the CPI through a lagged and diluted formula called Owner’s Equivalent Rent. The index assumes homeowners “rent to themselves” and spreads changes over twelve months, muting spikes in real rents and mortgages.

By the time the official numbers catch up, renters have already moved, landlords have already raised rates, and affordability has already deteriorated. This delay creates a comforting illusion of stability while real budgets collapse.

4. Substitution and Shrinkflation

The CPI assumes that when prices rise, consumers substitute cheaper goods—switching from steak to chicken, name brands to generics. On paper, that keeps inflation low. In reality, it disguises a decline in living quality.

Shrinkflation compounds the deception: packages get smaller, ingredients cheaper, and value erodes while prices stay “flat.” Statistically, that looks stable. To families, it feels like theft by a thousand cuts.

5. The Arithmetic of Erosion

Even modest inflation compounds powerfully. A 4 % annual rise in essential costs over five years represents a 22 % real loss in purchasing power. If wages rise only 2 %, the gap widens relentlessly. The result is what we now see in every major city: households squeezed not by recession but by attrition—the slow bleed of paychecks that never quite stretch to the end of the month.

This is why polls show that even as official inflation cools, more than 70 % of Americans still feel the cost of living is worsening. Their perception is mathematically valid: their personal inflation truly is higher.

6. The Broader Consequence

When policymakers rely solely on headline inflation, they misread the economy’s pressure points. The data may suggest calm while households experience crisis. That false sense of stability delays corrective policy and allows affordability to deteriorate invisibly until it erupts as political unrest or migration.

This is the quiet multiplier behind the affordability crisis. Personal inflation erodes stability one paycheck at a time, magnifying every other vulnerability—housing shortages, wage stagnation, and public frustration. By the time the official metrics confirm distress, the damage is already systemic.

7. Texas and the Next Test

Texas currently enjoys the reputation of affordability that New York and California have lost. But the same arithmetic applies. Housing in major Texas metros has risen more than 40 % since 2019, property taxes are climbing faster than wages, and infrastructure maintenance is overdue. If local cost pressures continue unchecked, the same personal inflation that hollowed out coastal states could quietly take root here as well.

Economic migration follows cost mathematics, not state pride.

8. The Real Lesson

Maybe the story of the 2020s isn’t about whether the Federal Reserve hits its 2 % target, but about whether ordinary citizens can still afford to live with dignity. The charts may show victory, yet the grocery carts tell another story. Personal inflation—unseen, unmeasured, but deeply felt—is how an affordability problem becomes a societal one.

Until policymakers, employers, and communities account for this hidden inflation, they will continue to mistake quiet erosion for progress. Affordability will keep slipping, not because prices explode, but because the numbers that define “normal” no longer describe reality.

The Socialist Experiment in New York City: Vision Meets Fiscal Reality

November 4, 2025.Reading time 13 minutes.

A collaboration between Lewis McLain & AI

Introduction

The election of a mayor in New York City who identifies as a democratic socialist signals a dramatic shift in the city’s political narrative. Proposals such as fare-free public transit, universal childcare, city-run grocery stores, and rent freezes have energized supporters who see them as necessary correctives to inequality and high living costs.

Yet beneath that enthusiasm lies a more sobering arithmetic: the city’s finances are already tight, its labor and pension obligations immense, and its economy increasingly dependent on a shrinking number of high-income taxpayers. The balance between compassion and solvency — between vision and viability — will determine whether this new era becomes an urban renewal or a fiscal unraveling.

I. New York City’s Financial Context

The latest Comprehensive Annual Financial Report (FY 2025) shows that the city closed the year with revenues of $117.66 billion and expenditures of $117.69 billion — essentially a balanced budget achieved by drawing modestly from restricted funds. After adjustments, a small $5 million surplus was credited to the Rainy Day Fund, raising it to $1.97 billion.

This appears healthy until one examines the trend lines. The City Comptroller and State Comptroller both forecast out-year deficits of $2.6 billion in FY 2026, widening to $7–10 billion by FY 2028–29. Pension obligations remain enormous despite an 89 percent funded ratio, labor costs are escalating, and COVID-era federal funds have largely expired.

In other words, New York is balancing its budget in a good year with almost no margin for error. A downturn, a real-estate correction, or an over-ambitious spending spree could easily tip it back into the red.

II. The Socialist Policy Agenda

The mayor’s policy wish-list targets affordability at its roots:

Free or low-cost mass transit
Universal childcare and pre-K
City-operated grocery stores in food deserts
Expanded tenant protections and rent freezes
Greater municipal ownership of infrastructure

Each of these goals carries moral appeal. But together, they represent billions of dollars in recurring obligations that will persist long after political enthusiasm fades. Implementing even half of these programs without new recurring revenues would expand the city’s structural deficit dramatically.

III. Revenue, Tax Base, and Business Climate

The proposed funding approach — raising taxes on high-income residents, large corporations, and real-estate speculation — will face both political and economic resistance.

Political resistance: Many of these measures require approval from Albany, where state lawmakers must balance suburban and upstate constituencies less receptive to urban redistribution.
Economic resistance: Roughly 1 percent of taxpayers provide nearly 40 percent of personal income-tax revenue in NYC. Even modest out-migration among high earners or firms could erase the expected gains from new tax rates.
Market perception: Wall Street, real-estate developers, and major employers watch credit outlooks closely. Higher taxes and heavy regulation could depress hiring, slow construction, and weaken commercial-property values — already under pressure from remote work and high vacancies.

These effects don’t occur overnight, but over several budget cycles they can hollow out the very tax base needed to sustain social programs.

IV. Bond Ratings and Borrowing Capacity

At present, New York City’s credit ratings remain high — Aa2 from Moody’s, AA from S&P, and AA from Fitch — all with stable outlooks. These ratings assume continued budget discipline, strong tax collections, and access to credit markets.

Should the city run persistent multi-billion-dollar deficits or fund recurring programs with one-time revenues, that stability could erode. Even a single-notch downgrade would increase borrowing costs by tens of millions of dollars per issuance. Plus, rating changes usually apply to all outstanding issues, meaning the largest consistency for all governments will get equally stiffed. Given the city’s dependence on annual borrowing of $12–14 billion for capital projects, that would quickly compound into hundreds of millions in added interest.

V. Legal Liabilities and Operational Costs

The city already pays roughly $1.4–1.5 billion annually in legal claims — police misconduct, labor disputes, civil-rights cases, and infrastructure accidents. A socialist administration likely to push faster hiring, expanded benefits, and new regulations may unintentionally increase exposure to lawsuits and administrative complexity.

These are not hypothetical: NYC’s risk portfolio is vast, and new programs create new compliance risks. Legal settlements and overtime overruns have quietly strained the budget for years — issues any mayor, socialist or not, must confront.

VI. The Broader Economic Setting

Even without policy shocks, New York’s economy is fragile in several sectors:

Office occupancy remains below pre-pandemic levels, reducing property-tax growth.
Hospitality and retail have recovered unevenly.
Finance and tech, the city’s fiscal engines, are cost-sensitive to regulatory or tax changes.

Layering aggressive redistribution atop those fragilities could dampen hiring or investment. While not catastrophic immediately, the cumulative effect would be slower growth, fewer jobs, and ultimately lower tax receipts — precisely when the city’s spending commitments rise.

VII. The National Ripple Effect

Other progressive cities — Chicago, Seattle, Boston, perhaps Austin — may watch New York closely. They will adopt pieces of this agenda (municipal grocery pilots, partial transit-fare relief) if results seem favorable. But few will gamble their bond ratings or business ecosystems on full replication.

In this sense, New York’s mayor becomes both pioneer and cautionary tale: admired for ambition, judged by execution.

VIII. The Realistic Risks Ahead

A sober appraisal must acknowledge what can realistically go wrong:

Revenue Shortfall Spiral: If tax hikes trigger out-migration or weak compliance, revenues could decline even as spending rises. Once bond markets sense erosion of the tax base, borrowing costs climb and confidence wanes.
Program Cost Overruns: City-run enterprises and free-service models are historically prone to inefficiency. Without strict oversight, projected costs could double, as seen in past housing and transit initiatives.
Labor and Pension Escalation: Expanding public programs often means expanding payrolls. Each new civil-service position brings long-term pension liabilities the city cannot easily reverse.
State Disputes: If Albany resists authorizing new taxes or programs, the city could face legal stalemates that delay funding while political promises remain unmet.
Economic Shock: A recession, commercial real-estate correction, or major loss in Wall Street profits could instantly erase the city’s narrow surplus and expose the fragility of its social agenda. Recessions are not if but when the next one occurs.
Credit Downgrade: Persistent deficits or fiscal gimmicks would lead rating agencies to shift outlooks to negative, forcing the city to cut spending, raise taxes further, or both — a cycle that can quickly turn populism into austerity. They are the only independent entity that cares not just about today but how the future bondholders are going to get paid.

IX. The Most Likely Scenario

The most realistic projection is a politically energized but fiscally constrained administration. The mayor will likely succeed in implementing a handful of visible programs — perhaps expanded childcare and targeted transit subsidies — but larger ambitions will stall amid budget shortfalls, business pushback, and credit scrutiny.

The public narrative may celebrate “bold change,” but the spreadsheets will show a city juggling rising obligations, marginal surpluses, and deepening long-term gaps.

In short: the dream will proceed, but only as far as the balance sheet allows.

X. The Black Swan Scenario — The Wrong Time for New York, the Right Time for Texas

While New York experiments with costly new commitments, Texas is quietly building the next great financial center. The Texas Stock Exchange (TXSE), headquartered in Dallas, is preparing to launch with backing from major investors such as BlackRock and Citadel Securities. Goldman Sachs is constructing a campus for 5,000 employees; JPMorgan Chase already employs more people in Texas than in New York; Nasdaq has announced a regional headquarters there.

If a black swan event hits — a financial-market crash, a sudden collapse in NYC commercial real-estate values, or a capital-gains exodus triggered by new taxation — the balance of power could shift rapidly. Texas, with no personal income tax, lower costs, abundant housing, and an open regulatory climate, would absorb the outflow of capital and talent. Texas could be the black swan event!

The timing could not be more opposite for the two states. New York is entering a period of fiscal experimentation with razor-thin margins, while Texas is in a period of economic expansion and institutional investment. A severe downturn would strike New York when it can least afford it — saddled with new spending and declining revenues — but it would strike Texas at a moment when it can capture opportunity.

In that worst-case but plausible scenario:

Wall Street decentralizes as firms expand or relocate to Texas, eroding NYC’s tax base.
Bond markets lose confidence and demand higher yields on NYC debt.
Layoffs and migration accelerate, reducing both population and purchasing power.
Property values decline, cutting the city’s largest revenue source.
Austerity returns, undoing the very social ambitions that inspired the movement.

It would be, in essence, a black swan reversal of roles — Texas ascending as New York falters, the right place meeting the right time while the old capital of finance learns how quickly vision can collide with math.

Conclusion: Vision Without Solvency Defies Common Sense

New York City’s socialist experiment will test whether progressive ideals can coexist with fiscal realism. The mayor’s heart may be with the working poor, but numbers are stubborn things: every new entitlement must be paid for in perpetuity, not just proclaimed at a press conference.

Without disciplined budgeting, credible revenue streams, and cooperation from the state, even noble ambitions could accelerate the city toward financial distress. Remember 1975? The world’s financial capital cannot thrive if it loses the confidence of those who fund it, employ it, or lend to it.

History teaches that great cities fall not from bold ideas but from ignoring basic arithmetic. Unless ideology bends to economic gravity, the risk is not revolution — it is regression.

Fund 999

October 25, 2025.Reading time 15 minutes.

A collaboration between Lewis McLain & AI

Expanded Municipal Conference Edition
(A municipal one-act for finance directors, auditors, city managers, and anyone who fears the phrase “per GASB …”)

Dramatis Personae

Socrates — “Temporary Fiscal Clarity Consultant.”
Clerk — keeper of keys, minutes, and mysteries.
Finance Director — calm, caffeinated, bindered.
Auditor — cheerful, bespectacled, powered by sampling.
Councilmember — earnest, reform-minded, occasionally literal.
Budget Analyst — Excel whisperer, existential worrier.
Grants Coordinator — compliance hobbyist, binder color-coder.
IT Person — speaks API, fears “Final_FINAL_v27.xlsx.”
Bond Counsel (Cameo) — invokes covenants, vanishes.
City Manager — thunder on loafers.
Stranger — walk-on comic angel of clarity.
Chorus — two staffers labeled “Chart of Accounts,” who sing footnotes and disclaimers.

Scene 1 — Records Room, 8:01 a.m.

(A pull-chain bulb. Filing cabinets labeled “Special Revenue (Ancient)” and “Projects We Definitely Finished.” A banker’s box glows faintly.)

Clerk: (whispering) I found it behind the 1998 copier lease and an unsigned MOU.
Socrates: (peering in) Ah! A relic with a number: Fund 999. The last digit thrice—the mystics will be unbearable.
Clerk: We numbered it so we’d remember it. We forgot it because we numbered it.
Socrates: Thus the first law of bureaucracy: name a thing, and it hides behind the label.

(Enter Finance Director with coffee.)

Finance Director: We don’t use Fund 999. It’s legacy. Dormant. Harmless.
Socrates: Dead or sleeping?
Finance Director: With funds there is “active,” “should’ve been closed,” and “awaiting discovery by auditors.”
Chorus: (soft hum) GASB fifty-four… five flavors… evermore…
Socrates: Five flavors? I hope they pair with coffee.
Finance Director: They pair with pain.

(Lights shift.)

Scene 2 — The Conference Room of Unfinished Business

(Whiteboard reads: “CLOSE-OUT PLAN — DRAFT OF THE DRAFT.” A plate of cookies labeled “For Council Only.”)

Budget Analyst: We think it began as a Special Revenue Fund.
Socrates: “Special” in the sense of purpose or in the sense of “we didn’t know where else to put it”?
Budget Analyst: (shrugs) Column G says purpose. Column H says “¯\(ツ)/¯”.
Grants Coordinator: I found a 2004 email: “Use Fund 999 for ‘Economic Vibrancy Initiatives.’”
Socrates: A phrase so broad that even philosophy can’t hug it.

Finance Director: (opens binder) Under GASB 54, fund balance has five flavors: Nonspendable, Restricted, Committed, Assigned, Unassigned.
Socrates: Like Greek virtues, but with footnotes and acronyms. Which flavor is 999?
Finance Director: (grim) It says Assigned.
Socrates: Assigned by whom?
Finance Director: People who no longer work here and possibly never existed.

Councilmember: If it’s assigned, can we un-assign it and buy sidewalks?
Socrates: Can a promise made at midnight guide a parade at noon?

(Enter Auditor, jolly and terrifying.)

Auditor: I sensed ambiguity. I came as soon as it balanced.

(They gather around a laptop that immediately requests updates.)

Scene 3 — Field Audit, with Flashlight

(A worktable of binders, highlighters, and a flashlight for dramatic effect.)

Auditor: Three classic reasons a fund like this persists:

Revenue vanished, meetings continued.
It became a parking lot for “temporary” due-to/due-from balances during the Bronze Age.
Someone feared commingling like they fear cilantro—

(Door SLAMS. Enter City Manager, thunder on loafers.)

City Manager: (booming) WHO SPOKE THE C-WORD?
(Everyone freezes. Coffee trembles.)
City Manager: The C-word is worse than profanity! It shall never enter your mind nor cross your lips. Should you contemplate inter-fund cross-pollination, your tenure shall be concluded by end of day—by end of lunch if I’ve had decaf! We separate by purpose, by law, by covenant, by destiny! Are we clear?
All: Crystal!
City Manager: Carry on. (Exits like a thunderclap. The doorknob impelled the wall and won’t close until maintenance can come.)

Socrates: Behold, a policy sermon in one act.
Auditor: We shall say “cash cross-contamination.”
Grants Coordinator: I prefer “inter-fund salsa.”
Finance Director: Let’s say none of that in the minutes.

Auditor: As I was saying: trace origin, verify restrictions, clear “temporary” balances old enough to vote, and—if unconstrained—close or repurpose per policy.
Socrates: A funeral with paperwork.
Budget Analyst: And an obituary in Column J.

Chorus: (singing softly) Schedule of Expenditures of Federal Awards… SEFA, SEFA, hallelujah…

Scene 4 — The Council Work Session That Lasts Forever

(Slide: “Agenda Item 7: Fund 999 — Close-Out Options.” The clock reads 5 p.m. It will continue to read 5 p.m.)

Councilmember: Why do we have so many funds?
Socrates: Because the human heart loves categories. Also, reports paginate badly.
Finance Director: Funds aren’t piles of cash; they’re accounting entities. The question: does 999 still serve a public purpose with the correct basis of accounting, or is it an honorary title we forgot to retire?
Councilmember: And the risk?
Finance Director: Confusion, misreporting, and the slow death of transparency by a thousand “Other Financing Sources.”
Socrates: When is a Special Revenue Fund truly special?
Finance Director: When a revenue is legally restricted or formally committed. “We like it this way” is not a restriction.
Socrates: Capital Projects Fund?
Finance Director: For major construction tracked over years.
Socrates: Internal Service?
Finance Director: Shared services—fleet, IT, insurance—half science, half therapy.
Socrates: Enterprise?
Finance Director: Water, sewer, airport—where depreciation is theoretical until cash runs out.
Councilmember: So Fund 999 may be none of these.
Socrates: Or all in spirit and none in substance—Schrödinger’s Fund- you know, the quantum mechanics thingy.
Auditor: And remember: no cross-conta—
All: SHH!
Auditor: (solemn) The thing we do not name.

(Suddenly, the door opens. A man in jeans and a checked shirt leans in, microphone in hand.)

Stranger: You might be a redneck if the only thing you know about debits and credits applies to your bar tab!

(He tips his hat and leaves before anyone can speak. A beat of stunned silence.)

Budget Analyst: Was that Jeff Foxworthy?
Councilmember: Sure looked like him.
Finance Director: Who invited him to this workshop?
Clerk: Dunno, but he nailed our internal controls problem.
Socrates: A wandering comic sage—he spoke truth in accruals.
Auditor: And violated no procurement policy.
(They shrug and return to the slide.)

Scene 5 — The Archive Yields a Scroll

(The IT Person hustles in with a USB drive labeled “Do_Not_Delete.”)

IT Person: I found the creation memo in a retired share. Also twelve copies named “Final.”
Budget Analyst: (reading) “Fund 999 established to collect developer contributions for ‘Vibrancy Improvements’: benches, trees, and public art—until expended.”
Grants Coordinator: That smells like Restricted—by agreement, maybe even by location.
Finance Director: If contribution agreements limit geography and purpose, the money can’t fund sidewalks three miles away or festival confetti.
Socrates: The fund’s soul is not empty; merely mislabeled.

Auditor: Proposed remedy:

Inventory balances; tie dollars to source agreements and zones.
Finish intended projects or amend agreements in public.
Anything orphaned goes to the closest lawful purpose via resolution, with a bright-line audit trail.

Councilmember: And if any dollars touched bonds?
(Enter Bond Counsel like a thundercloud.)
Bond Counsel: Then behold private use and spend-down rules. One does not mix—
All: SHH!
Bond Counsel: —one does not cohabit bond proceeds with things best left separate. (Vanishes.)
Socrates: A god descended, spoke in acronyms, and departed.

Scene 6 — The Ritual of Reclassification

(Whiteboard now reads: “Close-Out Steps (No New Mysteries).”)

Finance Director:

Document the origin — revenue source, legal constraints, geographic limits.
Reconcile balances — clear “temporary” due-tos/froms and identify encumbrances older than our interns.
Reclassify fund balance — from “Assigned” to Restricted where supported; from myth to Committed via Council action; true orphans to Unassigned in General Fund—but only if truly free.
Council resolution — honor original intent, specify projects, authorize closure or continuation in a proper fund.
ERP updates — lock Fund 999; migrate remaining activity with a clean audit trail and a change log longer than the Iliad.
Public report — plain-English: “Where it came from, where it’s going, why it’s right.”

Auditor: And when you close it, do not create a brand-new “Miscellaneous Special” for leftovers. That’s like cleaning your desk by buying a bigger drawer.
Budget Analyst: (guilty) Drawer 4 is full.

Socrates: Adopt a Fund Rationalization Policy:

Sunset clauses (“close within 24 months of project completion”).
Criteria for when a special revenue fund is warranted vs. a department in General.
An annual Fund Cemetery Review: who can be merged, closed, or resurrected only with cause.

Finance Director: (scribbling) I’ll title it “The No New Mysteries Act.”
Grants Coordinator: With an appendix: “Words We Don’t Say.”
All: (in unison) The C-word.

Scene 7 — The Public Hearing

(A citizen with a stroller; a teenager in a marching band shirt; a retiree holding a sapling.)

Councilmember: Tonight we confess: sometimes we created complex things for simple purposes, then forgot the purpose. We bind ourselves to clarity.
Citizen: Does this mean the benches and trees are finally coming?
Finance Director: (smiles) In the right places, for the right reasons, with the right dollars.
Socrates: If a city can discover the meaning of “assigned,” it can surely plant a tree.

Chorus: (like a lullaby)
Nonspendable for what cannot be spent,
Restricted by law and covenant;
Committed by council’s earnest vote,
Assigned by those who mind the float;
Unassigned to cushion rain…
and never hide your funds again.

Scene 8 — Epilogue in the Records Room

(The box labeled “Fund 999” now bears a red tag: “CLOSED—SEE RES. 2025-117.”)

Clerk: Will there be others like it?
Socrates: Anything built by people is half cathedral, half maze.
Finance Director: But now we keep a map—and a list of words we do not speak.
Auditor: See you next year. Fewer legends, more sidewalks.
(They nod. The bulb clicks off.)

Closing Hymn (Tempo: Workshop After 5 p.m.)

Verse 1
We opened every ledger, we traced the oldest thread,
Found dollars softly sleeping in the archives of the dead.
We numbered them with reverence, we labeled them with care,
Then closed them with a policy and sunlight everywhere.

Chorus
Oh sing the five fund flavors, in balance true and kind:
Restricted, Committed, Assigned, Unassigned!
And when the auditors arrive, we greet them with a grin—
For legends fade to footnotes when the policies begin.

Verse 2
We honored covenants sacred, we planted trees at last,
We cleared the “temporary” items from the echoes of the past.
If ever funds grow labyrinths on shelves we cannot see,
We’ll ask the simplest question first: “What is the purpose, be?”

Chorus (repeat)

Quick Reference

GASB 54 Fund Balance: Nonspendable / Restricted / Committed / Assigned / Unassigned
Special Revenue Fund: Use only for legally or formally constrained revenues.
Capital Projects Fund: Track major construction across years.
Internal Service Fund: Shared services; mind rate setting and net position.
Enterprise Fund: Business-type; depreciation is real (and so is cash).
Close-Out Steps: Origin → Reconcile → Reclassify → Council Action → ERP Migration → Public Summary.
Policy Fixes: Sunset clauses; annual fund rationalization; bright-line handling of orphans; glossary of “Words We Do Not Say.”

Staging & Use Notes

Run time ≈ 15–18 minutes. Cast 8–10. Props: banker’s box, scary binder, whiteboard, pull-chain bulb, one cookie labeled “For Council Only.”
Handout: Close-Out Checklist + Five Flavors explainer.

The Shutdown That Won’t End: How America’s Fiscal Stalemate Became a Test of Creditworthiness

October 12, 2025.Reading time 11 minutes.

And Why the Bond Rating Agencies May Hold the Only Key to Ending It

By Lewis F. McLain, Jr.

I. The Standoff That Never Ends

Another fiscal year, another government shutdown.
The United States now governs by brinkmanship — running on a series of temporary spending bills that barely prevent collapse but never deliver stability. Each new “continuing resolution” buys only weeks of political truce.

In Washington, they call it negotiation. Everywhere else, it looks like a nation living paycheck to paycheck. It is actually worse than that. The U.S. has gotten by only by putting most of its excess on a credit card to the tune of $35,598,000 or $324,100 per taxpayer!

These short-term fixes, designed to “keep the lights on,” have become the defining symbol of America’s fiscal dysfunction. Lawmakers boast of avoiding disaster while guaranteeing the next one. The cost is not measured in missed paychecks alone, but in lost credibility — both with citizens and with the global markets that finance the republic.

II. Why the “Big Beautiful Bill” Didn’t Fix the Problem

When Congress passed the One Big Beautiful Bill Act (OBBBA) earlier this year, it was hailed as the long-awaited cure to America’s budget ills.
It was indeed a sweeping structural law — extending key tax cuts, revising welfare programs, and reshaping federal-state funding formulas.

But OBBBA was a policy framework, not an appropriations bill. It set the rules for how money could be spent but didn’t actually fund the government. The twelve annual spending bills that keep every agency running — from Defense to Education — remain incomplete.

Thus, the government shut down not because it lacked a vision, but because it lacked a functioning process. Even the worst person for financial management on planet earth could do better than the U.S. Government.

III. The Politics of Delay

Short-term CRs are not bureaucratic accidents; they are political strategy.

They Preserve Leverage.
A short CR allows each side to claim the next cliff as bargaining power.
They Manufacture Urgency.
By setting artificial deadlines, Congress ensures every debate becomes a crisis.
They Diffuse Blame.
Everyone claims partial credit for “keeping government open,” while no one takes responsibility for its paralysis.

This cycle — a patchwork of temporary lifelines — has become normalized. Yet in any other organization, such repeated failure to adopt a budget would be grounds for a downgrade, a leadership change, or both.

IV. The Rating Agencies: Watchful, But Timid

The major rating agencies — Fitch, Moody’s, and S&P — continue to issue cautious statements, but their restraint now borders on abdication. One must remember that they charge a fee to the governmental entity being rated, they represent the bondholders! The bondholders are the greatest constituency to be found. There are 350 billion U.S. citizens. Compare that to the $37 trillion “constituents” they represent.

Fitch warns that shutdowns “highlight governance challenges” but sees no immediate rating impact.
Moody’s, more decisive, already downgraded the U.S. from Aaa to Aa1 in May 2025, citing deficits and political dysfunction.
S&P notes that each week of shutdown could shave up to 0.2% from GDP growth but stops short of taking further action.
Scope Ratings in Europe calls the shutdowns a “negative signal of democratic decay.”

They are not wrong — just toothless.

Bond rating agencies are worthless when they only rattle sabers, if that.
Warnings without enforcement invite complacency, not reform. If a sovereign borrower can repeatedly risk default on its own operations without consequence, the rating system itself becomes performative — an echo chamber of polite disapproval.

V. The Garland Precedent: When Ratings Spoke Loudly

There is precedent for courage I am aware of. In the 1970s, the bond rating agency visited the City of Garland, Texas in person — not to offer advice, but to deliver a direct warning message.

The message was simple: “Stop playing tough on fiscal decisions. Balance your budget responsibly or face a likely immediate downgrade.”

The City Council took the warning seriously. By the next meeting, they had adopted corrective measures, and the city’s fiscal health stabilized. The visit worked not because Garland Council feared markets, but because it respected accountability.

It’s a story quietly echoed in other cities of that era, I’m sure — times when rating agencies acted like stewards of discipline, not commentators on chaos.

VI. The Case for Action Now

If such resolve worked in a Texas city half a century ago, imagine its effect on Washington today.
Bond rating agencies have the authority — and arguably the duty — to intervene decisively.

They could collectively declare this message before October 1:

“The United States has two weeks to fully reopen and fund the government, or face a downgrade of more than one notch.”

That single sentence would do what months of posturing cannot. Markets would react within hours.
Treasury yields would rise, the White House and congressional leaders would receive immediate pressure from financial institutions and state treasurers, and public attention would snap to the true cost of dysfunction. By the way, do you know how much of the $37 trillion is owned by foreign investors? What happens if the day comes for their $9 trillion in holdings to mature, they take the money, and decide to invest elsewhere? Go to http://www.debtclock.org to appreciate how fast it takes to rack up another $1 trillion in debt!

It would no longer be a debate about ideology — but about national credit survival.

VII. Why This Matters

Bond markets are not emotional. They reward stability and punish delay.
The United States retains its privileged position — as issuer of the world’s reserve currency — largely because investors still believe in its reliability.
But belief is not infinite. Every short-term CR and every unending shutdown erodes the myth of American infallibility.

A bold, time-bound ultimatum from the rating agencies would instantly clarify what is at stake:
that U.S. governance, not solvency, is now the chief risk to U.S. credit.

VIII. The Moral of the Shutdown Era

The nation’s fiscal problem is not a shortage of dollars — it is a shortage of discipline.
The Treasury and Federal Reserve can print money; it cannot print credibility.

Congress treats shutdowns as leverage. Presidents treat them as bargaining stages.
And the bond market, by refusing to act, has become the enabler of dysfunction.

The rating agencies have a choice: to remain cautious chroniclers of decline, or to be the mirror that forces reform. Their ratings are not just financial metrics — they are moral verdicts on governance.

IX. Conclusion: The Rating That Could Save a Republic

“Credit,” wrote Alexander Hamilton, “is the soul of a nation’s economy.”
But in our age, it may also be the conscience of a government that has lost its will to govern.

The bond rating agencies can end this stalemate — not by writing reports, but by drawing a line.
Two weeks. No more delays.
Reopen the government fully or face a downgrade severe enough to awaken both Wall Street and Main Street.

If they have the courage to act — as they once did in Garland, Texas — they could remind America that accountability still matters.

Because credibility, once lost, cannot be borrowed back.

Lewis is a municipal finance expert living in McKinney, Texas. While semi-retired (after 52 years), he was once the Garland Budget Director, the Dallas County Budget Officer (first in Texas) and then a VP in Public Finance for First National Bank in Dallas (now Bank of America). After his first ten years, he started consulting for local governments (about 40).

He still consults with about 16 entities such as DART, Brazoria County and the cities of Denton, Groves, Highland Village, Killeen, Leander, McKinney, Midland, Pearland, Richardson, Southlake, Stafford, Victoria and Wichita Falls. He has written several hundred articles, essays and blogs, most of which can be found at citybaseblog.net. He has also given hundreds of presentations at workshops all over Texas and other states, including a training session for young bond rating analysts in NYC years ago.

He was the Executive Director for the Government Finance Officers of Texas years ago and had an Ethics Award created in his name.

Government Shutdowns: Crisis or Farce?

September 29, 2025.Reading time 12 minutes.

A collaboration between Lewis McLain & AI

From 1976 to Today

Every few years, Americans brace for news of a looming federal government shutdown. Media coverage describes them as looming catastrophes, filled with images of barricaded monuments, national parks closed, and frustrated travelers at airports. Politicians on both sides amplify the tension, using the threat of shutdown as leverage in their broader battles. But step back from the noise, and a more complicated picture emerges. Shutdowns are disruptive, yes—but much of the panic they generate stems from a broader financial reality: many workers, public and private alike, simply don’t have enough savings to weather even a temporary pause in pay.

The Mechanics of a Shutdown

By law, when Congress fails to pass appropriations, agencies must cease operations that are not legally “excepted” for safety or essential services. Furloughed employees are ordered home, barred from working even if they wish to. Others—air traffic controllers, Border Patrol agents, TSA officers—must continue working without pay until the shutdown ends. Since the Government Employee Fair Treatment Act of 2019, federal workers are guaranteed back pay once the government reopens. Contractors, however, are not: a janitor or cafeteria worker may permanently lose income for the weeks the government was closed.

The Record Since 1976

The modern shutdown era began after a 1976 Justice Department opinion forced agencies to halt during funding gaps. Since then, there have been 10 shutdowns where furloughs actually occurred:

In the early 1980s, several shutdowns lasted 1–3 days each over spending disputes.
In 1986, there was a 1-day lapse.
In 1990, a 3-day shutdown unfolded during deficit reduction talks.
In late 1995, the government closed for 5 days, followed soon after by a 21-day shutdown into early 1996.
In 2013, the government shut down for 16 days over the Affordable Care Act.
In January 2018, a 3-day lapse occurred, followed by a few-hour closure in February 2018.
From December 2018 to January 2019, the U.S. endured its longest shutdown, lasting 34–35 days over border wall funding.

The averages

10 shutdowns since 1976 with furloughs.
~87 total days lost to shutdowns.
Average length: about 8–9 days each.
Average spacing: roughly 51 months between shutdowns or just over 4 years.
Longest: 2018–19 (35 days). Second-longest: 1995–96 (21 days).

The Savings Problem

Here lies the heart of the issue. For all the headlines about missed paychecks, the true problem is one shared across the American economy: too many households have little or no emergency savings. Federal Reserve surveys consistently show that a significant share of Americans struggle to cover even a $400 unexpected bill.

To put this in perspective, the average federal worker earns about $75,000 per year, or roughly $6,250 per month before taxes. If an employee had just one month’s salary set aside, most shutdowns—lasting a week or two—would be a financial nuisance rather than a personal crisis. Yet many federal workers, like many in the private sector, do not keep that cushion. The result is that a temporary disruption is felt as if it were permanent.

Public vs. Private Sector Contrast

In fact, federal employees are relatively shielded compared to their private-sector counterparts. Federal workers furloughed during a shutdown now know they will receive full back pay once it ends. That makes a shutdown more like a forced, interest-free loan taken from their personal finances—unpleasant, but not ruinous for those with only modest savings.

Private-sector workers, by contrast, face layoffs or plant closures with no promise of retroactive pay. When a factory shuts down or a store closes, wages are gone permanently. The drama over government shutdowns often overlooks this harsher reality faced daily by millions outside the public sector.

The Theatrics of Shutdowns

Here lies the “farce.” The political theater surrounding shutdowns magnifies their significance beyond their actual economic scope. Members of Congress stage dramatic press conferences in front of locked gates to national parks or shuttered museums. Leaders exchange blame in nightly news cycles, accusing the other party of holding the nation hostage.

Yet the reality is that these shutdowns are typically short—averaging less than nine days over the last 50 years—and resolved with little structural change. They function less as fiscal turning points and more as bargaining chips in partisan standoffs. For many politicians, the shutdown becomes a stage prop: a way to appear tough, principled, or uncompromising before their base, while knowing full well that the lights will turn back on once both sides agree to a continuing resolution.

Anecdotal Stories and Media Amplification

The media plays its own role in heightening the drama. During shutdowns, reporters easily find stories of hardship: a young family lining up at a food pantry, a federal employee selling personal belongings online, or a worker worried about making rent. These are real and often heartbreaking situations, but they are also selective snapshots. By highlighting the most sympathetic cases, the press frames shutdowns as universal devastation rather than as uneven disruptions that many households could withstand with even modest savings. The cycle feeds public anxiety, while offering politicians ready-made examples to cite in their rhetorical battles.

Conclusion and Prescription

Government shutdowns are disruptive and unnecessary, but they are not the economic cataclysm they are often made out to be. Federal employees, uniquely, are made whole with back pay; private-sector workers are not so fortunate. The real lesson is not just about partisan gridlock but about financial preparedness. If American households—federal and private alike—had even a modest emergency fund, much of the sting would disappear.

Epilogue: Preparing for the Inevitable

Shutdowns are not a question of if but when. For the average federal employee earning approximately $6,250 per month (gross pay), setting aside 5–10% of their income could quickly build a safety net. Within two to three years, such a worker could accumulate two months’ expenses in savings—enough to glide through even the 35-day shutdown of 2018–19 without panic. The same principle applies to private-sector employees, who face even harsher risks with no guarantee of back pay. Theatrics will continue in Washington, but for workers, the best defense is the same as for any economic shock: live as though a disruption is always around the corner, and be ready when it arrives.

Beyond Government: A Call for Financial Common Sense

One final lesson extends beyond shutdowns: governments and all employers should take a proactive role in preparing their workers for financial resilience. Offering personal finance workshops—covering emergency savings, debt management, and budgeting—would give employees tools to withstand not just shutdowns but any economic shock. Teaching that a minimum of one month’s savings is essential could shift shutdowns from feared national dramas to mere inconveniences. In the end, the best safeguard against political theater is not another law from Congress, but households equipped with the discipline and knowledge to weather storms on their own.

Appendix: Common-Sense Financial Resilience Training — Questions for Employees

Premise: don’t be surprised by the predictable. Cars age. Roofs wear out. Water heaters (tanks) fail. Paychecks get disrupted. The goal is to plan for what will happen so you don’t add new debt when it does.

A. Paycheck Reality Check

If your paycheck stopped today, how many days could you cover essential bills (housing, utilities, food, transportation) from cash on hand?
Could you cover one missed paycheck? two? What specifically would break first?

B. Emergency Fund

What is one month of essentials for your household (in dollars)?
Do you have that amount in liquid savings?
What automatic transfer (5–10% of pay) will get you there in the next 12 months?

C. Predictable Replacements

Car: age, mileage, major repairs due? Tires, brakes, battery?
Roof: age, replacement cost target?
HVAC: age (12–15 year lifespan), plan if failure hits peak season?
Water heater: age (8–12 years), funds set aside for replacement?
Appliances: fridge, washer/dryer, dishwasher—what’s next to fail?

D. Insurance & Deductibles

Do you have cash equal to your health, auto, and home/renter deductibles?
Do you know your out-of-pocket max for health insurance?

E. Debt

Balances, interest rates, and minimums?
Which debts can be deferred in hardship?
Which must be paid first to avoid cascading damage?

F. Cash-Flow Triage

What subscriptions and extras get cut first?
Which bills stay on autopay, which switch to manual to prevent overdraft?
Who do you call in week 1 (landlord, mortgage servicer, credit cards, utilities)?

G. Banking Setup

Do you keep your emergency cash in a separate account?
Are due dates aligned with paydays?
Is overdraft protection turned off to avoid hidden fees?

H. Income Backstops

What side jobs or overtime are realistic in a crunch?
Do you have licenses/gear ready to activate them?

I. Documentation

Do you have account numbers, phone contacts, hardship scripts written down?
Are IDs and policies stored securely but accessibly?

J. Household Coordination

Does every adult know the cutback order?
What are the “spending freeze” triggers?

K. Shutdown-Specific Planning

Federal employees: do you have one month’s expenses in cash (back pay is coming)?
Contractors: do you have 2+ months saved (no back pay guarantee)?

L. After-Action & Rebuild

After disruption, do you rebuild the emergency fund before lifestyle upgrades?
What habit (auto transfer, monthly review) keeps the cushion growing?