Methodology
What This System Measures
This system produces an economic health score for each of the top 50 U.S. metropolitan statistical areas (MSAs). The score answers a specific question: how healthy is this city’s labor market and cost environment for businesses considering locating or expanding there?
It is not a quality-of-life index, a population growth ranking, or a real estate investment guide. It is a signal of current and near-term economic conditions from the perspective of employers and workers making location decisions.
Geographic Scope
The report covers the 50 largest U.S. Metropolitan Statistical Areas (MSAs) by population, as defined by the Office of Management and Budget (OMB). Each MSA is represented by its primary city name. All 50 metros are scored simultaneously — each city’s percentile rank reflects its position relative to the other 49.
Core Mechanism: Percentile Ranking
Every metric is scored as a percentile rank across all 50 metros simultaneously. A score of 75 means that metro outperforms 75% of the other 49 cities on that specific metric. A score of 20 means it underperforms 80% of them. The median city scores 50 on any given metric.
Percentile ranks are bounded 0–100, immune to outliers pulling the scale, and immediately interpretable without knowing what a “normal” absolute value looks like. They are also self-calibrating: as conditions shift, rankings update naturally without manual threshold recalibration.
Metric Framework
Eight metrics are combined into a single weighted composite. The split is 85% Employment / 15% Housing — employment metrics directly measure labor market conditions; housing metrics capture whether workers can afford to live where businesses need them. The table below maps each scorecard label (shown on city pages) to its full technical name, weight, and data source.
| Code | Scorecard Label | Full Name | Weight | Category | Data Source |
|---|---|---|---|---|---|
| 107E | Labor Demand | Labor Demand Composite | 25% | Employment | BLS SAE — Employment & Weekly Hours |
| 101A | Unemployment | Unemployment Rate | 20% | Employment | BLS Local Area Unemployment Statistics (LAUS) |
| 103B | Wage Growth | Hourly Earnings YoY | 15% | Employment | BLS SAE — State & Metro Area Earnings |
| 104C | Cost of Living | Cost of Living Composite | 12% | Employment | Realtor.com / FRED / Census Bureau |
| 102A | Labor Force YoY | Civilian Labor Force YoY % Change | 10% | Employment | BLS Local Area Unemployment Statistics (LAUS) |
| 200B | Bldg. Permits | Building Permits YoY | 10% | Housing | Census Bureau Building Permits Survey / FRED |
| 204A | Days on Market | Days on Market Composite | 5% | Housing | Realtor.com / FRED |
| 105C | Office Economy | Office Worker Ratio Composite | 3% | Employment | BLS SAE — Industry Employment |
| Total | 100% |
The 8 Metrics Explained
Labor Demand — 107E — 25%
What it measures: A 2-component composite combining total nonfarm employment growth year-over-year (70% of the composite) with weekly hours deviation from each city’s own 12-month baseline (30%).
Why it’s the top-weighted metric: Labor demand is the central question this system is designed to answer. Employment growth tells you whether payrolls are expanding or contracting. Weekly hours deviation provides context — but the direction of that signal flips depending on whether employment is growing or shrinking. Hours above trend during job growth confirm genuine demand. Hours above trend during job losses signal a “survivor squeeze” where remaining workers absorb the load of eliminated positions — a warning, not a positive. This employment-conditional logic is what makes 107E a composite rather than two standalone metrics.
Scored higher when: Payrolls are growing and hours are running above each city’s own recent baseline.
Unemployment — 101A — 20%
What it measures: The share of the civilian labor force that is unemployed and actively seeking work. Sourced from BLS Local Area Unemployment Statistics (LAUS), which provides monthly metro-level estimates.
Why 20% weight: Unemployment is the most widely tracked, most politically salient, and most directly actionable labor market signal. A 0.5 percentage point difference represents tens of thousands of workers in a large metro. It is the single most powerful indicator of labor market health in this system.
Scored higher when: Unemployment is lower. This metric is inverted — a 3.0% unemployment rate scores better than a 5.0% rate.
Limitation: Unemployment is a lagging indicator. It peaks after recessions have already begun and falls after recoveries are underway. It also misses discouraged workers who have left the labor force entirely, which is why Civilian Labor Force Growth (102A) complements it.
Wage Growth — 103B — 15%
What it measures: The year-over-year percent change in average hourly earnings for all private-sector employees in the metro. Sourced from BLS State and Metro Area Employment, Hours, and Earnings (SAE).
Why 15% weight: Rising wages are a real-time demand signal — employers bid up labor prices when they need workers and expect revenue growth. Wage growth also directly affects worker purchasing power and a city’s ability to attract and retain talent. BLS earnings data updates monthly and captures genuine labor market tightness more dynamically than annual-anchored metrics.
Scored higher when: Wage growth is stronger. A city with +5.0% YoY earnings growth scores better than one at +1.5%.
Cost of Living — 104C — 12%
What it measures: A 3-component composite assessing housing cost burden relative to local wages. The underlying unit is price per square foot of housing divided by average hourly earnings — a ratio measuring how many hours of local work it takes to buy one square foot of housing. This normalizes costs against local wages rather than using a national price index.
The three components:
- Absolute affordability (50%): Where this metro sits on the min-max range of the PSF/earnings ratio across all 50 cities. Anchors the composite to actual affordability level so improving-but-expensive cities can’t outscore genuinely affordable ones.
- Trend direction (30%): Year-over-year change in the ratio, scored on a graduated linear scale from −5% (strongly improving) to +5% (strongly worsening). Graduated rather than binary to avoid over-penalizing cities with tiny cost upticks.
- Peer-relative trend (20%): How this city’s affordability trend compares to the national median. A city worsening when peers are also worsening is less alarming than one bucking a broad national improvement.
Scored higher when: The PSF/earnings ratio is lower (more affordable), improving, and improving faster than peers.
Labor Force Growth — 102A — 10%
What it measures: The year-over-year percent change in the civilian labor force — the total count of people who are either employed or actively seeking work. Sourced from BLS Local Area Unemployment Statistics (LAUS).
Why it complements unemployment: A city can report low unemployment simply because discouraged workers stopped looking — they exit the labor force and disappear from unemployment counts. Tracking the growth rate of the labor force captures whether the workforce supply is expanding (workers moving in or re-engaging) or contracting (discouraged workers exiting or population decline).
Why YoY % change instead of the participation rate: The traditional LFP rate uses an annual population benchmark from BLS as its denominator, meaning the denominator only updates meaningfully once per year. This makes the rate a slow-moving structural snapshot rather than a dynamic monthly signal. The YoY % change in the raw civilian labor force count avoids this denominator problem entirely and tracks supply-side momentum directly.
Scored higher when: Civilian labor force is growing faster year-over-year. A city attracting workers or seeing re-engagement scores better than one where the labor pool is shrinking.
Building Permits — 200B — 10%
What it measures: The year-over-year percent change in residential building permits, using a 3-month smoothed average to reduce monthly volatility. Sourced from the Census Bureau Building Permits Survey via FRED.
Why it matters: Rising permits indicate developer confidence in future demand and will eventually translate into housing supply — relevant both as a measure of current economic activity and as a leading indicator of future housing availability for workers. A city that is attracting investment in new housing is signaling expectations of continued population and employment growth.
Why smoothed: Building permits are volatile month-to-month due to project timing, seasonal factors, and batch-approval effects. The 3-month smoothed YoY compares the 3-month average ending this month to the 3-month average ending 12 months ago, substantially reducing noise without losing the trend signal.
Scored higher when: Permit growth is stronger year-over-year.
Days on Market — 204A — 5%
What it measures: A 2-component composite assessing housing market accessibility for workers, using median days a listing spends on market before going under contract. Sourced from Realtor.com via FRED.
The 60-day inflection point: The direction of the trend signal depends on where the market currently sits. This matters because the same directional change has opposite economic meaning depending on context:
- Below 60 days (tight market): Rising DoM is good — the market is gaining inventory and accessibility for incoming workers.
- Above 60 days (soft market): Rising DoM is bad — demand is softening, buyers can’t or won’t transact, and labor mobility is impaired because homeowners who can’t sell are unable to relocate.
The level component (40%): Scores the absolute DoM against a “healthy market” anchor using a bell-curve scale peaked at 35–80 days. Markets below 15 days are too competitive for incoming workers; markets above 130 days signal demand destruction. Both extremes score low.
Scored higher when: Days on market is in the healthy accessible range and trending in the appropriate direction for its current level.
Office Economy — 105C — 3%
What it measures: A 2-component composite assessing the concentration and growth of professional/office-based employment as a proxy for knowledge-economy job density. Underlying data is BLS employment in Information, Financial Activities, and Professional and Business Services sectors as a share of total nonfarm payroll.
The two components:
- YoY growth (60%): Whether knowledge-economy jobs are expanding in this market, based on the growth rate in the 3-month smoothed office worker count.
- Absolute share (40%): The structural depth of the professional economy — what percentage of all jobs are office-based, independent of recent trends.
Why only 3% weight: Office worker density is a useful tiebreaker signal — it differentiates knowledge-economy metros from industrial, logistics, and energy-dominated metros. However, it structurally penalizes legitimate economic models (energy, logistics, distribution) that carry fewer office workers by industry composition, not by economic weakness. At 3%, it provides directional signal without meaningfully distorting scores for non-office economies.
Scored higher when: Office-sector employment is a larger share of total jobs and growing.
Labor Market Signal
Each metro page displays a Labor Market Signal — a classification derived from two components of the Labor Demand metric: employment growth year-over-year and weekly hours deviation from each city’s own 12-month baseline. The signal captures what employment growth alone cannot: whether strong hours reflect genuine demand or a workforce being squeezed after layoffs.
| Signal | Condition | Interpretation |
|---|---|---|
| STRONG | Employment growing & hours above trend | Genuine demand confirmation. Employers are adding headcount and running existing workers above their normal hours — a double confirmation of labor demand. |
| GROWING | Employment growing & hours below trend | Healthy expansion with some moderation. Payrolls are rising but hours are softening, suggesting growth is broadening rather than concentrating on a shrinking workforce. |
| SQUEEZE | Employment falling & hours above trend | Survivor squeeze. Payrolls are contracting while remaining workers carry elevated hours — a warning signal that the labor pool is thinning and demand may be masking layoffs. |
| WEAK | Employment falling & hours below trend | Broad contraction. Both job counts and weekly hours are declining together, indicating generalized demand weakness rather than a transitional squeeze. |
| N/A | Insufficient data | One or both underlying data series (employment growth or weekly hours deviation) were unavailable for this metro at the time of calculation. |
Composite Score Calculation
The composite score is a weighted average of each metro’s 8 individual percentile scores:
weighted_score = ∑(percentile[metric] × weight[metric])
Since all weights sum to 100, the result is a single number on a 0–100 scale. The practical range observed across 50 metros is approximately 21–79 — the distribution compresses because no city can plausibly average 90+ across all 8 metrics simultaneously, and no city averages below 20.
Grade Thresholds
Thresholds are calibrated to the actual achievable range of scores, not the theoretical 0–100. They are set so the grade distribution is meaningful and discriminating across the full spectrum of metros.
| Score Threshold | Grade | Description |
|---|---|---|
| 68+ | A+ | Excellent |
| 63–67.9 | A | Very Good |
| 59–62.9 | A- | Good |
| 55–58.9 | B+ | Above Average |
| 50–54.9 | B | Average |
| 44–49.9 | B- | Below Average |
| 38–43.9 | C+ | Poor |
| 32–37.9 | C | Very Poor |
| 26–31.9 | C- | Critical |
| Below 26 | D | Emergency |
Data Sources
- BLS LAUS — Local Area Unemployment Statistics: unemployment rate, civilian labor force
- BLS SAE — State and Metro Area Employment, Hours, and Earnings: employment growth, hourly earnings, weekly hours, industry employment
- Census Bureau / FRED — residential building permits
- Realtor.com / FRED — median days on market, housing price per square foot
Update Cadence
The pipeline runs monthly, timed to BLS data release schedules. BLS LAUS and SAE data typically releases in the third or fourth week of each month for the prior month. Building permit data from Census releases approximately 16–18 days after month-end. Realtor.com housing data updates monthly.
Each run recalculates all 50 metro scores simultaneously. Percentile ranks are recomputed from scratch — a city’s score can change without any change in its own absolute data if conditions in other cities shift the distribution.
Limitations
- Not a forecast. The score reflects current and trailing conditions. It is a lagging-to-coincident indicator, not a prediction of future economic performance.
- Not size-adjusted. All metrics are rates and percentages. A metro with 500,000 workers and one with 5,000,000 are compared on the same basis — the question is health, not scale.
- Structural composition effects. Civilian labor force growth reflects both economic conditions and migration patterns. A city growing its labor pool through in-migration looks similar to one recovering from discouraged-worker exit. The percentile ranking captures relative momentum but does not distinguish between these drivers.
- Not a quality-of-life index. Amenities, climate, culture, and livability are not measured. A city can score highly and still be expensive, congested, or climatically challenging.
- Data lags. Some BLS metro-level series lag national estimates by 1–2 months. Scores reflect the most recently available data, which may not be the same calendar month for all metros.