MISSION:
BUILD A PLATFORM
TO MAKE FIDI
A MODEL DISTRICT
FOR THE FUTURE
CHALLENGES:
Three forces are driving the next urban market: will change planning, operations, automation, and services; will force investment in resilience, adaptation, and decarbonization; and will reshape housing, mobility, healthcare, energy, safety, and public services. Invent City turns those pressures into a market for solutions.
OBJECTIVES:
- Accelerate deployment of critical urban solutions.
- Create jobs, economic activity, and tax revenue for NYC.
GENERAL APPROACH:
Invent City will build an urban solutions innovation district in FiDi. An urban Trade Mart anchors the district. Immersive showrooms, events, media, data, digital platforms, and AI turn it into a year-round marketplace with global reach.
MODELED RESULTS FOR NYC:
- $4B in annual economic activity.
- 15,000 jobs.
- $380M in annual tax revenue.
STRATEGY:
LEAD WITH ECONOMICS,
USE WHAT WORKS,
ACTIVATE FIDI,
SCALE WITH AI
Economics moves cities. Inaction gets more expensive every year. Solutions create value now. Invent City focuses on for every key stakeholder: jobs for NYC, stronger companies, a larger tax base, better investor returns, and more sales.
For investors and companies, cities are a massive and . More than 4 billion people live in urban areas today; roughly 6 billion could by 2100. Mature cities must modernize. Fast-growing cities must build fast. Both need better systems.
Deployment depends on who fund, approve, buy, regulate, operate, and live with change. The captures what they need now, anticipates what comes next, and turns those signals into demand, sales, and investment intelligence.
Climate damages could reach $38T a year by 2050. Target urban-solution markets could exceed $43T in annual revenue by mid-century.
Demographics
Urban growth is expanding demand for housing, mobility, services, and infrastructure.
Rising Urban Populations
Growth in Developing Cities
AI impact
AI is reshaping city systems, improving performance while raising new risks and governance questions.
AI Spendingby Area
Immediate potential of AI in NYC
Environmentals
Heat, flooding, and climate stress are driving demand for more resilient urban systems.
Sea Level Rise
Rising Temperatures
An concentrates companies, buyers, talent, capital, suppliers, and civic partners so they move faster together. Like Kendall Square and 22@Barcelona, Invent City will turn FiDi’s underused office and retail space into a living lab, marketplace, and global showcase for what cities need next.
Invent City targets urban needs: water, flooding, sea-level rise, subsidence, heat, mobility, housing, energy, waste, safety, and public services. These are also opportunities because cities cannot ignore them. The problems are urgent. The budgets are real. The buyers need proof.
start with faster discovery, comparison, sales, and deployment. include more investment, stronger company formation, new jobs, higher visitor demand, and a better use for vacant real estate.
A Trade Mart is a year-round marketplace built to turn products into sales. Companies do more than display ideas. They demonstrate solutions, meet qualified buyers, reach investors and partners, and move deals forward.
For Invent City, the Urban Trade Mart is the district’s commercial engine. It gives urban-solution companies a permanent platform to showcase products, run live demos, meet customers, launch pilots, secure financing, and convert interest into deployment.
The model draws from worldwide. The Trade Mart concentrates the market and speeds adoption. it brings customers, partners, investors, agencies, and project teams into one place. it makes solutions easier to find, compare, test, finance, and deploy.
The Trade Mart uses to make complex urban solutions visible, testable, and easier to buy. Events bring the market to FiDi. Digital platforms keep it active everywhere.
turn sales pitches into proof. Buyers can experience future streets, buildings, parks, rooftops, waterfronts, and city systems before they invest.
Buildings
Urban Agriculture
Consumer Products
Energy & Power
Urban Robotics
Urban AI
Wastewater
Water Systems
Transportation
gives Invent City instant credibility. It concentrates capital, media, talent, tourism, culture, real estate, agencies, employers, universities, and the decision-makers cities and companies follow. NYC makes the platform visible to the world.
Within NYC, gives Invent City leverage: transit, Wall Street capital, global visibility, historic identity, waterfront risk, vacant office and retail space, and direct access to buyers, investors, agencies, founders, media, and civic leaders.
John Street
Nassau Street
S William and Beaver
Under the FDR
Broad Street @ NYSE
William Street @ Fosun Plaza
Wall Street
Gotham Park
The venue strategy is simple: use what exists. FiDi has vacant offices, retail, POPS, streets, parks, and public-realm assets, including . This lowers cost, speeds launch, and turns underused space into productive space. becomes an economic asset when companies, showrooms, events, services, and street activity fill it.
Office vacancy
Vacant FiDi office space can become productive economic infrastructure faster than major redevelopment.
Retail vacancy
Vacant storefronts can become street-level showrooms, pop-ins, pilots, and visitor-facing demonstrations.
Lower cost
Existing FiDi space can be activated faster and at far lower cost than conversion or ground-up development.
RedevelopmentCosts
Faster revenue
A Trade Mart can move from vacant space to market activity much faster than major redevelopment.
Time toRevenue
Flexible rollout
The platform can start small, prove demand, and expand as companies, buyers, and capital follow.
FlexibleRollout
can package essential street services in one place: last-mile logistics, Blue Highway freight transfer, e-bike charging, battery exchange, micromobility, waste collection, storage, public bathrooms, worker support, shade, water, information, and emergency response.
can add major public-realm upside, including support for projects such as Gotham Park. Invent City does not depend on it, but Gotham Park could showcase water innovation, mobility, vegetation, lighting, and public-space technology.
AI can become one of NYC’s biggest economic engines: a growth industry and a productivity layer for finance, real estate, healthcare, media, government, logistics, and public services. Invent City turns that opportunity into a market platform for testing, demonstration, governance, financing, and sales.
FiDi can test urban AI in the real world. Companies can prove what works, what saves money, what reduces risk, what scales, and what needs stronger oversight.
Invent City makes AI visible. Buyers, investors, agencies, operators, and delegations can compare solutions, run simulations, review data, understand ROI, and move faster.
Invent City extends beyond FiDi. Events, media, data, digital platforms, and AI keep the market active every day and give cluster companies global reach. connects the platform with founders, buyers, investors, policymakers, operators, delegations, and press. lets audiences across time zones explore, compare, share, and engage anytime. links physical and digital channels, turning attention into trust, investment, procurement, pilots, and deployment.
Events
Live programming turns attention into meetings, pilots, partnerships, and deal flow.
Events
Media
Content expands the Trade Mart beyond FiDi and keeps buyers engaged between visits.
Media
Digital reach
Digital and AI channels keep discovery, comparison, and follow-up active 24/7.
DigitalReach
FOR NYC:
$4B IN ECONOMIC ACTIVITY,
15,000 JOBS,
$380M TAX REVENUES
Tourism brings outside dollars into New York. Invent City adds high-value business and innovation visitors to FiDi, supporting hotels, restaurants, retail, culture, transit, events, and local services.
Invent City adds buyers, delegations, trade events, media, and global attention.
They stay longer and support hotels, restaurants, retail, transit, culture, and services.
They travel year-round, spend heavily, and create steadier demand. Invent City is built for deal-driven visits.
| Tourism summary | Mid |
|---|---|
| Annual visitors | 1,000,000 |
| Traveler spending ($/yr) | $1,348,750,000 |
| Total economic impact ($/yr) | $2,090,562,500 |
| Tourism-supported jobs | 6,034 |
| Modeled taxes and fees ($/yr, no PIT) | $159,240,625 |
| Rounded taxes and fees ($/yr, no PIT) | $159,200,000 |
| Note: PIT excluded to avoid double counting with Trade Mart payroll impacts. | |
| Tourism summary | Low | Mid | High |
|---|---|---|---|
| Annual visitors | 1,000,000 | 1,000,000 | 1,000,000 |
| Traveler spending ($/yr) | $1,035,000,000 | $1,348,750,000 | $1,768,750,000 |
| Total economic impact ($/yr) | $1,604,250,000 | $2,090,562,500 | $2,741,562,500 |
| Tourism-supported jobs | 6,034 | 6,034 | 6,034 |
| Modeled taxes and fees ($/yr, no PIT) | $123,684,375 | $159,240,625 | $206,796,875 |
| Rounded taxes and fees ($/yr, no PIT) | $123,700,000 | $159,200,000 | $206,800,000 |
| Note: PIT excluded to avoid double counting with Trade Mart payroll impacts. | |||
| 1. Base assumptions: 1.0M visitors/yr | Visitors/year | Avg nights | Hotel room-nights | Visitor-days |
|---|---|---|---|---|
| International overnight | 250,000 | 5 | 1,250,000 | 1,250,000 |
| Domestic overnight | 250,000 | 2 | 500,000 | 500,000 |
| Domestic day | 500,000 | 0 | 0 | 500,000 |
| Total | 1,000,000 | — | 1,750,000 | 2,250,000 |
| 2. Spending inputs | Low | Mid | High |
|---|---|---|---|
| Hotel room-nights | 1,750,000 | 1,750,000 | 1,750,000 |
| ADR ($/room-night) | $250 | $325 | $425 |
| International other spend ($/day) | $350 | $450 | $600 |
| Domestic overnight other spend ($/day) | $200 | $275 | $350 |
| Domestic day other spend ($/day) | $120 | $160 | $200 |
| Note: ADR = average daily hotel room rate. “Other spend” = non-hotel visitor spending. | |||
| 2A. Hotel and other traveler spending | Low ($/yr) | Mid ($/yr) | High ($/yr) |
|---|---|---|---|
| Hotel revenue | $437,500,000 | $568,750,000 | $743,750,000 |
| Other spending (non-hotel) | $597,500,000 | $780,000,000 | $1,025,000,000 |
| Total traveler spending | $1,035,000,000 | $1,348,750,000 | $1,768,750,000 |
| Formula: Other spend = sum of (visitor-days by segment × spend/day by segment). | |||
| 2B. Total economic impact | Low | Mid | High |
|---|---|---|---|
| Traveler spending ($/yr) | $1,035,000,000 | $1,348,750,000 | $1,768,750,000 |
| Impact ratio | 1.55x | 1.55x | 1.55x |
| Total economic impact ($/yr) | $1,604,250,000 | $2,090,562,500 | $2,741,562,500 |
| Rounded total economic impact ($/yr) | $1,604,000,000 | $2,091,000,000 | $2,742,000,000 |
| Formula: Total economic impact = traveler spending × 1.55. | |||
| 3. Tourism-supported jobs | Input / Output | Value |
|---|---|---|
| NYC visitors (2024) | 64.3M visitors | |
| NYC tourism-supported jobs (2024) | 388,000+ jobs | |
| Jobs per 1M visitors | 6,034+ jobs | |
| IC annual visitors (assumption) | 1.0M visitors | |
| IC tourism-supported jobs (modeled) | 6,034+ jobs | |
| Formula: Jobs per 1M visitors = 388,000 / 64.3. | ||
| 4A. Hotel room taxes and fees | Low | Mid | High |
|---|---|---|---|
| NYS sales tax on hotel rooms (4.0%) | $17,500,000 | $22,750,000 | $29,750,000 |
| NYC sales tax on hotel rooms (4.5%) | $19,687,500 | $25,593,750 | $33,468,750 |
| MCTD sales tax on hotel rooms (0.375%) | $1,640,625 | $2,132,813 | $2,789,063 |
| NYC hotel occupancy tax (5.875%) | $25,703,125 | $33,414,063 | $43,695,313 |
| NYC per-room hotel tax ($2.00 × room-nights) | $3,500,000 | $3,500,000 | $3,500,000 |
| NYS hotel unit fee ($1.50 × room-nights) | $2,625,000 | $2,625,000 | $2,625,000 |
| 4B. Sales tax on other spending | Low | Mid | High |
|---|---|---|---|
| NYS sales tax (4.0%) | $23,900,000 | $31,200,000 | $41,000,000 |
| NYC sales tax (4.5%) | $26,887,500 | $35,100,000 | $46,125,000 |
| MCTD sales tax (0.375%) | $2,240,625 | $2,925,000 | $3,843,750 |
| Total sales tax on other spending | $53,028,125 | $69,225,000 | $90,968,750 |
| 4C. Tax totals roll-up (no PIT) | Low | Mid | High |
|---|---|---|---|
| NYS total (hotel + other) | $44,025,000 | $56,575,000 | $73,375,000 |
| NYC total (hotel + other) | $75,778,125 | $97,607,813 | $126,789,063 |
| MCTD total (hotel + other) | $3,881,250 | $5,057,813 | $6,632,813 |
| Grand total (no PIT) | $123,684,375 | $159,240,625 | $206,796,875 |
| Rounded grand total (no PIT) | $123,700,000 | $159,200,000 | $206,800,000 |
| 4D. Tax formulas and notes | Low | Mid | High |
|---|---|---|---|
| Hotel revenue formula | room-nights × ADR | room-nights × ADR | room-nights × ADR |
| NYS hotel-room sales tax | Hotel revenue × 4.0% | Hotel revenue × 4.0% | Hotel revenue × 4.0% |
| NYC hotel-room sales tax | Hotel revenue × 4.5% | Hotel revenue × 4.5% | Hotel revenue × 4.5% |
| MCTD hotel-room sales tax | Hotel revenue × 0.375% | Hotel revenue × 0.375% | Hotel revenue × 0.375% |
| NYC hotel occupancy tax | Hotel revenue × 5.875% | Hotel revenue × 5.875% | Hotel revenue × 5.875% |
| NYC per-room hotel tax | $2.00 × room-nights | $2.00 × room-nights | $2.00 × room-nights |
| NYS hotel unit fee | $1.50 × room-nights | $1.50 × room-nights | $1.50 × room-nights |
| NYS sales tax on other spending | Other spending × 4.0% | Other spending × 4.0% | Other spending × 4.0% |
| NYC sales tax on other spending | Other spending × 4.5% | Other spending × 4.5% | Other spending × 4.5% |
| MCTD sales tax on other spending | Other spending × 0.375% | Other spending × 0.375% | Other spending × 0.375% |
| Scope note: PIT excluded to avoid double counting with Trade Mart payroll impacts. | |||
The Trade Mart turns urban innovation into recurring commercial activity. Jobs, payroll, procurement, buyer traffic, events, travel, and tax revenue all build from the same commercial engine.
The Trade Mart supports on-site jobs, events, services, building operations, hospitality, and spillover activity.
Buyers, sellers, delegations, events, project teams, and business visitors support hotels, restaurants, retail, and services.
Upside comes from payroll, rent, property values, sales taxes, hotel taxes, permits, business activity, and multipliers.
| Trade Mart summary | Mid |
|---|---|
| Direct on-site jobs | 8,500 |
| Direct payroll ($/yr) | $1,427,500,000 |
| Local procurement ($/yr) | $428,250,000 |
| Total direct activity ($/yr) | $1,855,750,000 |
| Note: Direct activity shown here is kept separate from tourism and real-estate modules to reduce double counting. | |
| Trade Mart summary | Low | Mid | High |
|---|---|---|---|
| Direct on-site jobs | 8,500 | 8,500 | 8,500 |
| Direct payroll ($/yr) | $1,140,000,000 | $1,427,500,000 | $1,790,000,000 |
| Total jobs incl. indirect + induced | 12,750 | 15,300 | 17,850 |
| Knock-on jobs | 4,250 | 6,800 | 9,350 |
| Note: Only direct jobs should be treated as additive across modules to avoid double counting. | |||
| 1. Jobs based on area | Area | Density | Direct jobs |
|---|---|---|---|
| Showrooms | 1,000,000 sf | 1,000 sf/job | 1,000 |
| Support offices | 1,500,000 sf | 200 sf/job | 7,500 |
| Trade Mart total | 2,500,000 sf | — | 8,500 |
| Formula: Jobs = Area / Density. Example: 1,500,000 sf / 200 sf per job = 7,500 jobs. | |||
| 2A. Low-case payroll detail | Jobs | Low wage ($/yr) | Payroll ($/yr) |
|---|---|---|---|
| Showrooms | 1,000 | $90,000 | $90,000,000 |
| Support offices | 7,500 | $140,000 | $1,050,000,000 |
| Total for direct | 8,500 | $1,140,000,000 |
| 2B. Mid-case payroll detail | Jobs | Mid wage ($/yr) | Payroll ($/yr) |
|---|---|---|---|
| Showrooms | 1,000 | $115,000 | $115,000,000 |
| Support offices | 7,500 | $175,000 | $1,312,500,000 |
| Total for direct | 8,500 | — | $1,427,500,000 |
| 2C. High-case payroll detail | Jobs | High wage ($/yr) | Payroll ($/yr) |
|---|---|---|---|
| Showrooms | 1,000 | $140,000 | $140,000,000 |
| Support offices | 7,500 | $220,000 | $1,650,000,000 |
| Total for direct | 8,500 | — | $1,790,000,000 |
| 2D. Direct jobs | Jobs | Low wage | Mid wage | High wage |
|---|---|---|---|---|
| Showrooms | 1,000 | $90,000/yr | $115,000/yr | $140,000/yr |
| Support offices | 7,500 | $140,000/yr | $175,000/yr | $220,000/yr |
| Total direct jobs | 8,500 | — | — | — |
| Total payroll ($/yr) | 8,500 | $1,140,000,000/yr | $1,427,500,000/yr | $1,790,000,000/yr |
| 3. Local procurement | Low | Mid | High |
|---|---|---|---|
| Procurement assumption (% of payroll) | 20% | 30% | 40% |
| Local procurement ($/yr) | $228,000,000 | $428,250,000 | $716,000,000 |
| Formula: Local procurement = Payroll × Procurement share. | |||
| What it reflects: Tenant and campus operating spend—security, cleaning, repairs, IT/AV, catering, event staffing, printing/signage, and local logistics; excludes landlord building OpEx. | |||
| 4. Direct campus activity (Economic expansion) | Low | Mid | High |
|---|---|---|---|
| Payroll ($/yr) | $1,515,000,000 | $1,902,500,000 | $2,390,000,000 |
| Local procurement ($/yr) | $303,000,000 | $570,750,000 | $956,000,000 |
| Total direct activity ($/yr) | $1,818,000,000 | $2,473,250,000 | $3,346,000,000 |
| Formula: Total direct activity = Payroll + Local procurement. | |||
| 5. Indirect and induced jobs | Low | Mid | High |
|---|---|---|---|
| Direct jobs | 8,500 | 8,500 | 8,500 |
| Total jobs incl. indirect + induced | 12,750 | 15,300 | 17,850 |
| Knock-on jobs | 4,250 | 6,800 | 9,350 |
| Implied total multiplier | 1.50x | 1.80x | 2.10x |
| What this shows: Additional off-site jobs supported through suppliers, vendors, and household spending. | |||
| Definitions: Direct = on-site Trade Mart jobs. Indirect = supplier and vendor jobs supported by Trade Mart spending. Induced = jobs supported by household spending from wages. Knock-on = indirect + induced combined. | |||
| 6. Modeled tax revenues | Low | Mid | High |
|---|---|---|---|
| NYS PIT | $62,700,000 | $85,650,000 | $116,350,000 |
| NYC resident PIT | $34,200,000 | $45,680,000 | $60,860,000 |
| MCTMT | $10,203,000 | $12,774,125 | $16,020,500 |
| Sales tax on employee spending | $17,688,469 | $22,150,602 | $27,779,445 |
| Sales tax on local procurement | $10,117,500 | $18,998,344 | $31,772,500 |
| Total modeled taxes ($/yr) | $134,908,969 | $185,253,070 | $252,782,445 |
| Rounded total modeled taxes ($/yr) | $134,900,000 | $185,300,000 | $252,800,000 |
| NYS stands for New York State, NYC for New York City, PIT for personal income tax, and MCTMT stands for the Metropolitan Commuter Transportation Mobility Tax. | |||
| 6A. Tax assumptions and formulas | Low | Mid | High |
|---|---|---|---|
| NYS PIT effective rate | 5.5% | 6.0% | 6.5% |
| NYC resident PIT rate | 3.0% | 3.2% | 3.4% |
| MCTMT rate | 0.895% | 0.895% | 0.895% |
| Employee spending sales tax assumption | Payroll × 35% local spend × 50% taxable × 8.875% | ||
| Procurement sales tax assumption | Local procurement × 50% taxable × 8.875% | ||
| Procurement assumption | Payroll × 20% | Payroll × 30% | Payroll × 40% |
| NYS PIT formula | NYS PIT = Payroll × NYS PIT rate | ||
| NYC resident PIT formula | NYC PIT = Payroll × NYC resident PIT rate | ||
| MCTMT formula | MCTMT = Payroll × 0.895% | ||
| Employee spending sales tax formula | Payroll × 35% × 50% × 8.875% | ||
| Procurement sales tax formula | Local procurement × 50% × 8.875% | ||
| 6B. Scope note and caveat | Value |
|---|---|
| Scope note | NYC resident PIT assumes employees are NYC residents. If some workers commute from outside NYC, this line should be reduced accordingly. NYS PIT would still apply. |
| Additivity note | To avoid double counting across modules, only direct jobs should be treated as additive; indirect and induced jobs should not be added again in Tourism or other spillover modules. |
Real estate matters because Invent City can make underused FiDi space productive again. Filling 3.0M sf can support NOI, values, refinancing, reinvestment, street life, and public revenue.
Filling 3.0M sf can expand NYC’s recurring revenue base through stronger income, values, and long-term tax capacity.
Absorb vacant office and retail space. Improve NOI. Support valuations. Rebuild confidence in FiDi.
Vacancy creates the opening. Existing space launches faster and costs less than ground-up development.
The Trade Mart also attracts companies. A year-round FiDi marketplace puts firms near buyers, investors, agencies, partners, media, talent, and customers.
| Real estate summary | Low | Mid | High |
|---|---|---|---|
| Stabilized leased area (sf) | 3,000,000 | 3,000,000 | 3,000,000 |
| Annual rent ($/yr) | $165,000,000 | $165,000,000 | $165,000,000 |
| NOI ($/yr) | $111,750,000 | $106,860,000 | $102,000,000 |
| Illustrative implied value at 6.0% cap ($) | $1,862,500,000 | $1,781,000,000 | $1,700,000,000 |
| Modeled recurring NYC revenue capacity ($/yr) | $69,704,500 | $70,675,890 | $71,313,250 |
| Rounded recurring NYC revenue capacity ($/yr) | $69,700,000 | $70,700,000 | $71,300,000 |
| Note: This module is kept separate to avoid double counting with jobs, tourism, and construction modules. | |||
| 1. Leasing assumptions | Area | Asking rent | Annual rent |
|---|---|---|---|
| Trade Mart - Showrooms | 1,000,000 sf | $40/sf/yr | $40,000,000/yr |
| Trade Mart - Support offices | 1,500,000 sf | $60/sf/yr | $90,000,000/yr |
| Trade Mart - Total | 2,500,000 sf | — | $130,000,000/yr |
| Additional offices (separate) | 500,000 sf | $70/sf/yr | $35,000,000/yr |
| IC rent total (all space) | 3,000,000 sf | — | $165,000,000/yr |
| 1A. Average gross rent across all space | Value |
|---|---|
| Total area (sf) | 3,000,000 |
| Total annual rent ($/yr) | $165,000,000 |
| Average gross rent ($/sf/yr) | $55.00/sf/yr |
| 1B. Operating expense assumptions | OpEx ($/sf/yr) |
|---|---|
| Low | $17.75 |
| Mid | $19.38 |
| High | $21.00 |
| 1C. Cap-rate assumptions | Cap rate |
|---|---|
| Low cap | 5.5% |
| Base cap | 6.0% |
| Higher cap | 7.0% |
| High cap | 8.0% |
| 1D. Property-tax uplift assumptions | Value |
|---|---|
| NYC Class 4 assessment ratio | 45% |
| NYC Class 4 tax rate | 10.848% |
| Illustrative phase-in | 50% / 75% / 100% |
| 1E. CRT assumptions | Value |
|---|---|
| Rent base proxy ($/yr) | $165,000,000 |
| Effective CRT rate | 3.9% |
| Coverage factor | 70% / 85% / 95% |
| CRT gross upper bound ($/yr) | $6,435,000 |
| 1F. Vacancy context | Value |
|---|---|
| FiDi Financial East office vacancy (a) | 26.0% |
| FiDi Insurance office vacancy (a) | 29.5% |
| Retail storefront vacancy in FiDi/BPC (Q3 2024) (b) | 24% |
| Source note | (a) Cushman & Wakefield, Q4 2025; (b) Small Business Services |
| 2. Real-estate logic | Definition |
|---|---|
| Gross rent | Total annual rent collected |
| OpEx | Building operating expenses |
| NOI | Gross rent minus OpEx |
| Implied value | NOI divided by cap rate |
| 2A. NOI per square foot | Gross rent ($/sf/yr) | OpEx ($/sf/yr) | NOI ($/sf/yr) |
|---|---|---|---|
| Low expense | $55.00 | $17.75 | $37.25 |
| Mid expense | $55.00 | $19.38 | $35.62 |
| High expense | $55.00 | $21.00 | $34.00 |
| 2B. Total NOI on 3.0M sf | NOI ($/sf/yr) | Area (sf) | Total NOI ($/yr) |
|---|---|---|---|
| Low expense | $37.25 | 3,000,000 | $111,750,000 |
| Mid expense | $35.62 | 3,000,000 | $106,860,000 |
| High expense | $34.00 | 3,000,000 | $102,000,000 |
| 2C. Implied value from capitalized NOI | Cap rate | Implied value ($) | Value per sf |
|---|---|---|---|
| Low expense | 5.5% | $2,031,818,182 | $677.27/sf |
| Low expense | 6.0% | $1,862,500,000 | $620.83/sf |
| Low expense | 7.0% | $1,596,428,571 | $532.14/sf |
| Low expense | 8.0% | $1,396,875,000 | $465.63/sf |
| Mid expense | 5.5% | $1,942,909,091 | $647.64/sf |
| Mid expense | 6.0% | $1,781,000,000 | $593.67/sf |
| Mid expense | 7.0% | $1,526,571,429 | $508.86/sf |
| Mid expense | 8.0% | $1,335,750,000 | $445.25/sf |
| High expense | 5.5% | $1,854,545,455 | $618.18/sf |
| High expense | 6.0% | $1,700,000,000 | $566.67/sf |
| High expense | 7.0% | $1,457,142,857 | $485.71/sf |
| High expense | 8.0% | $1,275,000,000 | $425.00/sf |
| 2D. Plain-English economic benefits | Value |
|---|---|
| Benefit 1 | Fills vacant office and retail space |
| Benefit 2 | Creates steady rental income |
| Benefit 3 | Improves NOI |
| Benefit 4 | Supports stronger building values |
| Benefit 5 | Helps owners refinance, reinvest, and stabilize assets |
| Benefit 6 | Can improve confidence in the broader FiDi market |
| 3. Job-counting treatment | Value |
|---|---|
| Approach | This module does not claim incremental job creation, to avoid double counting with separate Trade Mart operations, tourism, and construction modules. |
| Why | It shows how filling vacant space can improve building income, support asset value, and expand recurring city revenue. |
| Caveat | Stabilizing vacant space can still support employment indirectly by making buildings more viable and attracting more tenants, activity, and investment. |
| 4A. Commercial Rent Tax (CRT) | Low | Mid | High |
|---|---|---|---|
| CRT gross upper bound ($/yr) | $6,435,000 | $6,435,000 | $6,435,000 |
| Coverage factor | 70% | 85% | 95% |
| CRT modeled ($/yr) | $4,504,500 | $5,469,750 | $6,113,250 |
| Rounded CRT modeled ($/yr) | $4,500,000 | $5,500,000 | $6,100,000 |
| 4B. Property-tax capacity uplift (mid-case illustration) | Value |
|---|---|
| Mid-case implied value ($) | $1,781,000,000 |
| Assessment ratio | 45% |
| Class 4 tax rate | 10.848% |
| Phase-in | 75% |
| Property-tax capacity uplift ($/yr) | $65,206,140 |
| Rounded property-tax capacity uplift ($/yr) | $65,200,000 |
| Formula: Property-tax capacity uplift ≈ market value × 45% × 10.848% × phase-in | |
| 4C. Total modeled recurring NYC revenue capacity | Low | Mid | High |
|---|---|---|---|
| Property-tax capacity uplift ($/yr) | $65,200,000 | $65,206,140 | $65,200,000 |
| CRT modeled ($/yr) | $4,504,500 | $5,469,750 | $6,113,250 |
| Total recurring NYC revenue capacity ($/yr) | $69,704,500 | $70,675,890 | $71,313,250 |
| Rounded total recurring NYC revenue capacity ($/yr) | $69,700,000 | $70,700,000 | $71,300,000 |
| 4D. Plain-English tax benefits | Value |
|---|---|
| Benefit 1 | More leased space can support higher building income |
| Benefit 2 | Higher income can support higher property value |
| Benefit 3 | Higher value can support higher NYC property-tax revenue capacity |
| Benefit 4 | Leased commercial space can also generate CRT revenue |
| 4E. Scope note |
|---|
| This section models recurring NYC revenue capacity from stabilized leasing and value. It excludes one-time transaction taxes such as RPTT, RETT, and mortgage recording tax, and keeps jobs separate to avoid double counting. |
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