Comparison of one section of the 1997 HOK
TL;DR
The 1997 Impacts Study covers a great deal of material. The Executive Summary makes many claims. We agree with its conclusions in the broad strokes. We created these breakdowns of specific cities, with an emphasis on how they align with the official NEPA/SEPA Sea-Tac Airport 1996 EIS.
- Study Period: 20 years post-runway construction
- Assumes: Service to begin in 2000
- Total Socio-Economic Cost: $6.4 million (2000-2020)
- Primary Impact: Property tax revenue loss from declining home values
- Key Finding: Airport benefits flow to region, costs concentrated locally
Core problem: geographic inequity
Who Uses vs. Who Pays
- 95% of airport passengers live elsewhere in Puget Sound region
- 5% live in the 5 most impacted communities
- Benefits: Distributed across Western Washington
- Costs: Concentrated in neighborhoods near airport
“While the study acknowledges the benefit of the Airport to the region and the State, these benefits are not experienced locally in the five impacted communities.”
How airport expansion hurts property values
- $4,450 loss in home value for every quarter-mile closer to flight tracks
- Properties 0.25 miles from flight track: lose 3.4% of value
- Des Moines average home: $109,122 baseline value
Cascade Effect
- Direct Impact: Noise and overflights reduce property appeal
- Indirect Impact: Lower values → more rentals → demographic shift
- Induced Impact: More services needed + lower tax base = fiscal squeeze
Property Tax Revenue Impact Analysis
| Impact Source | 20-Year Loss | Annual Average | % of Total |
|---|---|---|---|
| General Operations | $3.66M | $183K | 57% |
| Flight Track Shadow | $2.73M | $137K | 43% |
| TOTAL | $6.39M | $320K | 100% |
Why Des Moines gets hit so hard
- 2.77 miles of new flight track directly over city
- 1,491 housing units affected by flight track noise gradient
- Higher impact density than other communities
Educational impact spiral
How Airport Expansion hurts schools
- Property values decline → School district tax base shrinks
- Homeowners become renters → More transient, lower-income families
- Student demographics shift → Higher per-pupil costs needed for same outcomes
- Tax base + higher costs → Voters resist levy increases
Specific educational challenges
- Noise interrupts classroom instruction → Student stress increases
- Lower-income students require more resources to achieve grade-level performance
- High household turnover → Unstable peer relationships
- Single-parent households increase → Additional support services needed
“At the same time the District would be faced with a need to increase expenditures per student to maintain quality… it would face growing voter resistance to raising levy rates.”
Community service impact predictions
Demographic Shift Consequences
Single-family homes → Rentals creates:
- Higher demand for social services
- Increased public safety costs (rental areas have higher crime)
- More community center usage (transient populations need more services)
- Child care and senior services pressure
“Blighting” Process
- Homes take longer to sell near airport
- Owners convert to rentals to maintain income
- Rental areas attract more transient populations
- Community stability decreases
- Property values decline further (negative cycle)
Mitigation Alternatives Analyzed
Option 1: Property Tax Relief Program
Cost: $5.74M (Des Moines share of $40.7M total)
- Port of Seattle makes partial property tax payments to affected homeowners
- $927 average annual payment per affected property
- 6,197 housing units would be eligible
Option 2: Revenue Offset to Cities
Cost: $6.4M direct payments to Des Moines over 20 years
- Compensates for lost property tax revenue
- Maintains city service levels despite eroded tax base
- Annual payments of approximately $320K
Option 3: Home Ownership Loan Fund
Cost: TBD (shared program)
- Revolving loan fund to help renters become owners
- Prevents rental conversion cascade
- Maintains neighborhood stability
What the study got right
Accurate Predictions
- Property value impacts materialized – Airport areas do have slower appreciation–despite spending over $300,000,000 on sound insulation, property values
- Commercial investment did not materialize almost in direct relation to distance from the runway
- Rental conversion occurred – Many areas became more transient
- School challenges emerged – Demographics did shift as predicted
- Regional benefit/local cost disparity – Still evident today
Sophisticated Analysis Methods
- Regression modeling to isolate airport impact from other factors
- Comparable property analysis holding other variables constant
- 20-year projection methodology based on realistic assumptions
- Multiple mitigation alternatives rather than single approach
What Actually Happened
- Sound insulation programs were implemented (less extreme option)
- No neighborhood buyouts occurred (extreme $1.4B option rejected)
- Operational modifications adopted (trivial flight track adjustments)
Study Limitations
“The calculation of quantitatively probable, rather than illustrative, economic impacts… requires a research effort not possible within the resources available under the current study.”
Translation: Some numbers were estimates to establish ranges rather than precise predictions.
Unknowns
- The study was published before spending over $300,000,000 on sound insulation
- New forms of air pollution, especially ultrafine particles, were unknown
- New forms of water pollution, especially 6PPDQ and PFAS were unknown
- The final alignment for SR-509 had not been arrived at
Key Miss
It was assumed that encouraging expanded commercial development to a wider radius would provide significant economic benefits for all five cities–in effect, a powerful mitigation strategy.
Strategic value
Creating Decision Framework
By calculating multiple mitigation approaches, the study:
- Established negotiating position – $6.4M became “reasonable”
- Provided cost-benefit analysis – Sound insulation vs. buyouts vs. revenue sharing
- Created accountability mechanism – Specific impacts with specific remedies
- Enabled targeted solutions – Addressed root causes, not just symptoms
Methodological Strengths
- Transparent assumptions about property value impacts
- Detailed geographic analysis down to neighborhood level
- Multi-year impact projections based on realistic scenarios
- Alternative solutions matrix giving decision-makers options
Key Analysis Sections
- Property value methodology: Section 9.02-9.03, Tables 9.04-9.07
- Tax revenue calculations: Section 9.04-9.06, Table 9.08
- Educational impact analysis: Section 9.11, Table 9.15
- Mitigation alternatives: Section 9.12-9.14, Table 9.17
Supporting Data
- Regression analysis details: Page 9-6, Figure 9.01
- Community demographic analysis: Section 9.08-9.09
- 20-year projection methodology: Pages 9-27 to 9-33
Bottom Line
The Third Runway project shows just how unknowable the future is. The HOK assumes the project will be on-line in 2000. But 9/11 occurs, lawsuits drag out until 2004, costs balloon to 4X, and operational benefits only begin after 2012. But despite having so many incorrect inputs, its conclusions are ultimately correct because underlying trends were apparent.
Unlike the environmental analysis (which relied heavily on extreme buyout scenarios), the socio-economic section demonstrated strong analytical rigor.
The $6.4M figure represents sophisticated analysis of real impacts with practical mitigation solutions – exactly the kind of digestible justification that makes policy decisions possible. Today, with cost-effective access to so much more data, and the benefit of hindsight, it should be possible to build far better models. In short: the HOK is the ‘before’ which proves the ‘after’.