BURNOUT INDEX — CA — #25th OF 50
San Francisco-Oakland-Berkeley
San Francisco-Oakland-Berkeley, CA
Median household income is +66% vs. the national median with a BEA RPP of 106.2, implying relatively favorable purchasing power. Unemployment at 4.3% and a 31.8-minute average commute keep San Francisco-Oakland-Berkeley near the bottom of the burnout ranking. The labor market conditions here, on these three metrics, work less hard against you.
Scored 2026-05-04. Data: Census ACS 5-year 2023, BEA RPP 2024. Unemployment: BLS LAUS (most recent month).
The receipts
Three components, three public sources. Each term is clamped to [0, 1] before weighting. The formula is published on the methodology page; any change to the weights requires a public ADR (ADR-0013+).
| Component | Raw value | vs. national | Weight | Contribution | Source |
|---|---|---|---|---|---|
| Pay-to-cost gap Median HH income vs. cost of living. Purchasing power index: 1.56 (wages above cost-adjusted national) | $133,780 RPP 106.2 | +66% national median income | 40% | 0 | Census ACS 2023 BEA RPP 2024 |
| Mean commute Minutes/day, ACS 5-year. Capped at 60 min. | 31.8 min | 5.3 min longer than 26.5 min national | 30% | 15.9 | Census ACS 2023 |
| Unemployment rate BLS LAUS (monthly, MSA-level). Capped at 8%. Preliminary. | 4.3% | 0.4pp above 3.9% national (ACS period) | 30% | 16.1 | BLS LAUS LAUMT064186000000003 |
| Total score | 32 | ||||
San Francisco-Oakland-Berkeley in context
San Francisco-Oakland-Berkeley ranks 25th out of 50 major US metro areas on the Office Blues Burnout Index. The index measures three labor-market signals that directly affect worker quality of life: the gap between wages and cost of living, commute time, and unemployment pressure. It does not measure culture, management quality, or RTO mandates — those signals are not yet available at MSA level from primary sources without scraping.
The metro area population is approximately 4,749,008, making it one of the top-50 US metros by size. The data covers the San Francisco-Oakland-Berkeley, CA Metropolitan Statistical Area (CBSA 41860), which typically extends well beyond the core city limits.
On wages vs. cost of living: median household income here is $133,780 per year (+66% the national median of $80,610). Against a BEA Regional Price Parity of 106.2 (national average = 100, higher = more expensive), that works out to a purchasing-power index of 1.56 relative to a national baseline of 1.0. Wages here stretch further than the national average on a cost-adjusted basis — that's why the pay-to-cost gap contributes 0 points, not more.
On commute: the average one-way trip takes 31.8 minutes — 5.3 min longer than the national mean of 26.5 minutes. The commute component contributes 15.9 points out of a possible 30 (capped when commute ≥ 60 minutes). Commute time is the most consistent predictor of reported job dissatisfaction in the academic literature; it compounds every other signal.
On unemployment: the rate is 4.3%, which is 0.4pp above the national reference figure of 3.9% for the ACS measurement period. The unemployment component contributes 16.1 points out of a possible 30 (capped at 8%). High unemployment signals a weak labor market where workers have fewer outside options — the classic condition for wage suppression and lower bargaining power. This figure is from BLS LAUS (2026-02-28), the most current available.
The score formula is editorial — 40/30/30 weights are a deliberate choice, not derived from regression. If you think the weights are wrong, the methodology page explains the rationale. Weight changes require a public ADR (ADR-0013+). The sources are federal, license-free for reuse with attribution.
HOW THIS IS CALCULATED
Formula (ADR-0012, binding):
burnout_score = round( 40 × clamp₀₁(1 − normalized_wage / cost_norm) // pay-to-cost gap + 30 × clamp₀₁(commute_min / 60) // commute + 30 × clamp₀₁(unemployment_pct / 8) // unemployment )
Where:
normalized_wage= $133,780 ÷ $80,610 (national median) = 1.6596cost_norm= 106.185 ÷ 100 = 1.0619pay_term= clamp₀₁(1 − 1.6596 ÷ 1.0619) = 0.0000commute_term= clamp₀₁(31.8 ÷ 60) = 0.5300unemp_term= clamp₀₁(4.3 ÷ 8) = 0.5375
Score = round(40 × 0.0000 + 30 × 0.5300 + 30 × 0.5375) = round(32.02) = 32
Full methodology, weight rationale, and source citations: /methodology#burnout-index. Weight changes are a brand contract — any modification requires ADR-0013+.
What changed since last update
Score moved from 36 to 32 (-4 points). Data sources refresh weekly via CI cron. Score changes reflect BLS LAUS monthly releases (unemployment) and are recomputed every Monday at 14:30 UTC.
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Raw JSON: /burnout-index/san-francisco-ca.json · License: CC BY 4.0 · Cite as: Office Blues Burnout Index, San Francisco-Oakland-Berkeley, CA, officeblues.net/burnout-index/san-francisco-ca, 2026-05-04