Interactive Analysis of US Metropolitan Statistical Areas Investment Potential
Note: MSAs with populations below 300,000 are excluded from this dashboard.
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2024
MSA-level score by principal city (each dot represents one MSA)
| Rank | MSA Name | Population | Score | Actions |
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Adjust the weights below, then click Update Index Weights to apply ranking changes
| Rank | MSA Name | New Score | Change |
|---|
Evaluates strength and growth potential of an MSA's economic fundamentals.
Data Source: MSA-level data derived from U.S. Census Bureau datasets
Evaluates local housing affordability pressure relative to income.
Data Source: MSA-level data derived from U.S. Census Bureau datasets
Evaluates local supply-demand balance through multifamily pipeline growth and vacancy tightness.
Data Source: MSA-level data derived from U.S. Census Bureau datasets
Measures ability of landlords to raise rents over time.
Data Source: MSA-level data derived from U.S. Census Bureau datasets
Measures conversion-related value uplift by comparing multifamily and hotel valuation implied by the same NOI stream.
Data Source: MSA-level Annual rent inputs are derived from U.S. Census Bureau datasets. State-level cap rates and operating expenditure ratios are compiled from publicly available market data and industry reports, curated via Gemini-assisted prompt engineering
Captures policy and execution feasibility for hotel-to-multifamily conversion at the state level.
We convert state letter ratings into a monotonic [0,1] score to preserve rank order while allowing non-linear spacing between tiers. The mapping is intentionally non-equidistant: lower tiers (F, D-, D) receive steeper penalties to reflect higher execution and policy risk, while top tiers (A, A+) receive an additional premium for stronger conversion feasibility.
| State Rating | Hotel Conversion Relevance Score |
|---|---|
| A+ | 1.00 |
| A | 0.90 |
| A- | 0.84 |
| B+ | 0.78 |
| B | 0.66 |
| B- | 0.61 |
| C+ | 0.57 |
| C | 0.52 |
| C- | 0.40 |
| D+ | 0.33 |
| D | 0.25 |
| D- | 0.12 |
| F | 0.00 |
Data Source: State-level hotel conversion relevance ratings are based on policy and execution feasibility for hotel-to-multifamily conversion, synthesized from public policy materials via Gemini-assisted prompt engineering
Complete dataset showing MSA raw data (population, housing, employment, etc.) and 10 investment factors organized by 6 key dimensions
Data Source: U.S. Census Bureau and datasets
Data Source: U.S. Census Bureau datasets
Data Source: U.S. Census Bureau datasets
Data Source: U.S. Census Bureau datasets
Data Source: Annual rent inputs are derived from U.S. Census Bureau datasets. MSA-level cap rates and operating expenditure ratios are compiled from publicly available market data and industry reports, curated via Gemini-assisted prompt engineering
Data Source: State-level hotel conversion relevance ratings are based on policy and execution feasibility for hotel-to-multifamily conversion, synthesized from public policy materials via Gemini-assisted prompt engineering
The following data are state-level Operating Expenditure Ratio, Cap Rate, and Effective Tax Rate inputs.
The Operating Expenditure Ratio in real estate measures the proportion of a property’s operating costs relative to its income. It is defined as:
Operating expenses include costs such as maintenance, property management, utilities, insurance, and taxes, but exclude financing and depreciation. This ratio indicates how efficiently a property is managed, specifically how much cost is required to generate each dollar of income. A lower ratio suggests better operational efficiency, while a higher ratio indicates greater cost pressure. It is most meaningful when compared across similar property types.
Cap rate, or capitalization rate, measures the expected return of a real estate investment based on its income. It is defined as:
Net operating income represents income after operating expenses but before financing costs. The cap rate reflects how income relates to property value, with higher cap rates indicating higher risk and return, and lower cap rates suggesting more stable, lower-risk assets.
Hotel Cap Rate and Multifamily Cap Rate further capture state-level return expectations and pricing conditions across asset classes. They enable cross-asset valuation comparisons and help identify relative pricing tightness within different markets.
The effective tax rate measures the proportion of a company's pre-tax income that is paid in taxes, reflecting its actual tax burden. It is defined as:
Unlike statutory tax rates, the effective tax rate captures the impact of deductions, credits, and other tax planning strategies. A lower effective tax rate may indicate efficient tax management or favorable tax treatments, while a higher rate suggests a greater tax burden.
In real estate analysis, effective tax rates can vary across regions and asset types due to differences in local tax policies. As a result, they provide useful insight into after-tax returns and help improve the accuracy of cross-market investment comparisons.
Data Sources: Publicly available information retrieved via Gemini AI
The Home Energy Rating System (HERS) Index is the industry standard by which a home's energy efficiency is measured. It's also the nationally recognized system for inspecting and calculating a home's energy performance. https://www.hersindex.com/hers-index/understanding-hers-index/
A certified RESNET Home Energy Rater assesses the energy efficiency of a home, assigning it a relative performance score (the HERS® Index Score). The lower the number, the more energy efficient the home. A home built to 2006 energy efficiency standards scores 100.
A home with a HERS® Index Score of 70 is 30% more energy efficient than the RESNET Reference Home. A home with a HERS® Index Score of 130 is 30% less energy efficient than the RESNET Reference Home.
Due to inconsistency in HERS score availability and comparability across markets, this metric is not included in the 6-dimensional MSA ranking system. It is retained in the raw dataset for users' reference.
Select an MSA from the ranking table to view detailed analysis.
Compare markets across 6 key investment dimensions
Get a free key at aistudio.google.com → Create API Key. One key works for all models below.
Select 1–15 cities to generate a report.
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All 181 ranked MSAs are listed by investment score. Search by name, then tick the checkboxes for the cities you want to analyze (1–15).
Gemini AI generates structured market intelligence for each selected city — pipeline data, active projects, policy timelines, financial mechanisms, and news.
A full dashboard appears inline — KPI overview, pipeline bars, market scorecard, and per-city deep profiles. All in ~15–40 seconds.
Modify the prompt sent to Gemini. Leave unchanged to use the default.
Gemini is analyzing each city. This typically takes 15–40 seconds.
| City | Vacancy | Pipeline | YoY | Status |
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AI-researched profiles — catalysts, projects, policy timelines, financial mechanisms, and sourced intelligence.