What Is the Business Failure Rate in the US? #
The business failure rate in the United States is a core metric for anyone evaluating market entry, investment risk, or competitive landscape. According to the Census Bureau's Business Dynamics Statistics (BDS), roughly 20% of new employer businesses exit within their first year of operation (Census BDS, 2023). By year five, fewer than half of all new firms survive — a pattern that holds with remarkable consistency across economic cycles.
The term "failure" in federal data typically means business exit — the cessation of a firm's operations as tracked through payroll records, employer identification numbers, and establishment filings. This is distinct from bankruptcy, which is a legal proceeding tracked separately through federal court records. Federal exit data, sourced from the Census Bureau's Statistics of U.S. Businesses (SUSB) and County Business Patterns (CBP), captures the broadest picture of market attrition.
It is important to distinguish between firm exits and establishment closures. A multi-location company closing one location registers as an establishment exit, not a firm failure. Analysts working from CBP data should apply this distinction carefully to avoid overstating failure rates in sectors dominated by chain operations.
Failure Rates by Industry: Which Sectors Are Riskiest? #
Not all industries carry equal risk. Small business failure rates vary significantly by NAICS sector, and federal data makes those differences measurable. The BLS Business Employment Dynamics program publishes survival rates by industry division, allowing analysts to compare sector-level attrition with precision.
| Industry Sector (NAICS) | Approx. 1-Year Survival | Approx. 5-Year Survival |
|---|---|---|
| Healthcare & Social Assistance (62) | ~85% | ~55% |
| Professional & Technical Services (54) | ~84% | ~54% |
| Construction (23) | ~80% | ~47% |
| Retail Trade (44-45) | ~79% | ~41% |
| Food Services & Drinking Places (722) | ~77% | ~35% |
Source: BLS Business Employment Dynamics, survival rate estimates by industry, 2023. Figures are approximations derived from published cohort data.
Construction sits in the middle of the risk spectrum. While entry barriers are low, revenue concentration risk — dependence on a handful of contracts — drives elevated exit rates past year three. Professional services firms show stronger durability, largely because human capital constitutes their primary asset and overhead scales efficiently.
NAICS-level granularity matters here. A report covering "Retail Trade" broadly will obscure the difference between, say, auto dealers (NAICS 441) and clothing stores (NAICS 448), which carry meaningfully different survival profiles. Verified federal data from the SUSB allows analysts to drill to the 4- and 6-digit NAICS level for precise sector comparisons.
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The First Five Years: Survival Curves from Census Data #
Federal longitudinal data tells a consistent story: the business survival rate declines steeply in years one through three, then stabilizes. The Census Bureau's Business Dynamics Statistics tracks annual cohorts of new employer firms, providing year-by-year survival curves that span decades of economic history.
Source: Census Bureau Business Dynamics Statistics (BDS), employer firm survival by cohort year, 2023.
The steepest attrition — approximately 22 percentage points — occurs between years one and three. Firms that cross the five-year threshold show markedly lower exit probabilities going forward. This pattern holds across recessions, recoveries, and expansion periods, suggesting structural rather than cyclical drivers dominate early-stage exits.
The startup failure rate conversation often conflates venture-backed tech startups with the broader universe of new employer businesses. These are different populations. Venture-backed firms represent less than 1% of new business formation annually (Census SUSB, 2023). The federal survival curves cited above reflect all NAICS-classified employer firms — restaurants, contractors, consultancies, manufacturers — providing a far more representative baseline.
Why Businesses Fail: Patterns from Federal Data #
Federal datasets do not directly record the reason a business exits — there is no checkbox on a tax filing marked "undercapitalization." But by combining data streams, analysts can identify structural patterns behind elevated exit rates. The most common reasons businesses fail emerge clearly when payroll, revenue, and employment data are read together.
Key failure drivers identifiable through federal data:
- Revenue concentration risk: Census SUSB revenue distribution data reveals that firms in the bottom quartile of their industry's revenue range exit at two to three times the rate of median firms. Small absolute revenue with high fixed costs is a structural vulnerability.
- Labor cost pressure: BLS Occupational Employment and Wage Statistics (OES) tracks compensation trends by NAICS code. Industries where median wages are rising faster than sector revenue growth — a divergence visible in FRED economic data — show correlated upticks in business exits.
- Market saturation: CBP establishment counts by ZIP code and NAICS reveal where firm density is increasing without corresponding population or spending growth. High-saturation markets produce predictably higher attrition rates in subsequent years.
- Undercapitalization at entry: BDS data shows that firms entering with fewer than five employees in capital-intensive sectors (manufacturing, construction) exit at rates nearly double those entering with 10 or more employees (Census BDS, 2022).
How to Use Failure Rate Data for Risk Assessment #
Understanding business failure statistics is only useful if they inform a decision. For investors, lenders, market entrants, and economic developers, federal survival data translates directly into risk-adjusted frameworks — provided the data is properly sourced, NAICS-classified, and current.
Four applied use cases for federal failure rate data:
- Market entry decisions: Comparing your target sector's 5-year survival rate against the all-industry average gives a baseline risk premium. A sector with a 35% 5-year survival rate (e.g., food services) requires a materially different capitalization and payback assumption than one at 55% (e.g., healthcare).
- Lender underwriting: Community banks and SBA lenders can overlay CBP establishment density growth against BLS QCEW payroll volatility in a given market to assess whether local saturation risk is rising before a loan closes.
- Competitive landscape analysis: High exit rates in a sector create market share opportunities for surviving firms. Census SUSB tracks firm counts and revenue simultaneously — declining firm counts with stable or growing total sector revenue signals consolidation, not decline.
- Economic development targeting: Municipal planners using BDS data can identify which NAICS sectors in their geography show below-average survival rates and direct support programs accordingly.
The gap between raw federal data and a usable risk metric is where most practitioners stall. Each source uses different firm definitions, time lags, and geographic aggregations. Normalizing across BDS, CBP, and QCEW for a single NAICS code in a specific metro area is a multi-step process that benefits from pre-built analytical frameworks.
VantaInsights reports address exactly this — delivering pre-calculated survival benchmarks, establishment concentration metrics, and payroll trend data for 1,000+ NAICS-classified industries, sourced entirely from verified federal datasets. Where traditional research subscriptions run $925 or more annually, VantaInsights offers one-time report purchases starting at $239, with no proprietary estimates substituted for real federal figures.