Business Dynamics Statistics (BDS) API - Complete Variable Reference

Business Dynamics Statistics (BDS) API - Complete Variable Reference

API Overview

Endpoint: https://api.census.gov/data/timeseries/bds

Description: Provides time-series data on business dynamics including job creation, job destruction, establishment entry/exit, firm births/deaths, and employment changes. Data spans from 1978 to present.

Update Frequency: Annual

Use Cases for Business Initiative:

  • Business startup trends and survival rates
  • Job creation by industry and geography
  • Firm birth and death statistics
  • Industry growth and decline analysis
  • State-by-state business formation comparisons

Core Variables

Establishment Variables

ESTABS_ENTRY

  • Description: Number of new establishments (business locations) that entered the market
  • Data Type: Integer
  • Flag Variable: ESTABS_ENTRY_F (indicates data quality/suppression)
  • Use Case: Track new business locations opening, startup activity
  • Example: 790295 (new establishments in 2023)

ESTABS_EXIT

  • Description: Number of establishments that exited the market (closed)
  • Data Type: Integer
  • Flag Variable: ESTABS_EXIT_F
  • Use Case: Business closure rates, failure analysis
  • Example: 650123 (establishments closed in 2023)

ESTABS

  • Description: Total number of establishments (existing)
  • Data Type: Integer
  • Use Case: Total business count in market/industry

Job Creation Variables

JOB_CREATION

  • Description: Total number of jobs created (from all sources: births, expansions, continuers)
  • Data Type: Integer
  • Flag Variable: JOB_CREATION_F
  • Use Case: Overall job creation trends, economic growth indicators
  • Example: 15,234,567 (total jobs created in 2023)

JOB_CREATION_BIRTHS

  • Description: Jobs created by new firms (firm births)
  • Data Type: Integer
  • Flag Variable: JOB_CREATION_BIRTHS_F
  • Use Case: Jobs from startups, new business job creation
  • Example: 3,456,789 (jobs from new firms in 2023)

JOB_CREATION_CONTINUERS

  • Description: Jobs created by existing firms (expansions)
  • Data Type: Integer
  • Flag Variable: JOB_CREATION_CONTINUERS_F
  • Use Case: Growth of existing businesses, expansion activity
  • Example: 11,777,778 (jobs from existing firm expansions)

Job Destruction Variables

JOB_DESTRUCTION

  • Description: Total number of jobs destroyed (from all sources: deaths, contractions, continuers)
  • Data Type: Integer
  • Flag Variable: JOB_DESTRUCTION_F
  • Use Case: Job loss trends, economic contraction indicators

JOB_DESTRUCTION_DEATHS

  • Description: Jobs destroyed by firm deaths (business closures)
  • Data Type: Integer
  • Flag Variable: JOB_DESTRUCTION_DEATHS_F
  • Use Case: Job losses from business failures

JOB_DESTRUCTION_CONTINUERS

  • Description: Jobs destroyed by existing firms (contractions, layoffs)
  • Data Type: Integer
  • Flag Variable: JOB_DESTRUCTION_CONTINUERS_F
  • Use Case: Job losses from downsizing, not closures

Net Job Creation

NET_JOB_CREATION

  • Description: Net change in jobs (JOB_CREATION - JOB_DESTRUCTION)
  • Data Type: Integer
  • Flag Variable: NET_JOB_CREATION_F
  • Use Case: Overall employment growth/decline, economic health indicator
  • Example: 2,345,678 (net jobs added in 2023)

Firm Variables

FIRM

  • Description: Total number of firms (business entities)
  • Data Type: Integer
  • Use Case: Total business count, market size

FIRMDEATH_FIRMS

  • Description: Number of firms that died (closed permanently)
  • Data Type: Integer
  • Flag Variable: FIRMDEATH_FIRMS_F
  • Use Case: Business failure rates, survival analysis
  • Example: 450,123 (firms closed in 2023)

FIRMBIRTH_FIRMS

  • Description: Number of new firms (firm births)
  • Data Type: Integer
  • Flag Variable: FIRMBIRTH_FIRMS_F
  • Use Case: Startup rates, new business formation
  • Example: 550,234 (new firms in 2023)

Flag Variables (_F suffix)

All numeric variables have corresponding flag variables that indicate data quality:

  • No flag or empty: Data is reliable
  • D: Data suppressed (too few firms to report)
  • N: Not calculable (rate cannot be computed)
  • S: Suppressed due to data quality concerns
  • X: Structurally missing (not applicable)

Important: When a flag is present, the data value will be 0 or null.

Geography Options

National Level

  • us:* - United States total

State Level

  • state:* - All states
  • state:06 - California (use 2-digit FIPS code)
  • state:36 - New York
  • state:48 - Texas
  • Multiple states: state:06,36,48

County Level

  • county:* - All counties (within a state)
  • county:001 - Specific county (within state context)
  • state:06&county:* - All counties in California

Metropolitan Areas

  • metropolitan statistical area/micropolitan statistical area:* - All MSAs
  • metropolitan statistical area/micropolitan statistical area:31080 - Los Angeles MSA

Filter Options

NAICS Industry Codes

  • Parameter: NAICS2017 or NAICS2012
  • Format: 2-digit (sector) to 6-digit (industry)
  • Examples:
    • NAICS2017=54 - Professional, Scientific, and Technical Services
    • NAICS2017=72 - Accommodation and Food Services
    • NAICS2017=62 - Health Care and Social Assistance
  • Use Case: Industry-specific analysis

Firm Age

  • Parameter: AGE
  • Options:
    • 0 - Age 0 (new firms)
    • 1 - Age 1
    • 2 - Age 2
    • 3 - Age 3
    • 4 - Age 4
    • 5 - Age 5
    • 6 - Age 6+
  • Use Case: Analyze business survival by age

Employment Size of Firm

  • Parameter: EMPSZFI
  • Options:
    • 001 - 1-4 employees
    • 002 - 5-9 employees
    • 003 - 10-19 employees
    • 004 - 20-49 employees
    • 005 - 50-99 employees
    • 006 - 100-249 employees
    • 007 - 250-499 employees
    • 008 - 500-999 employees
    • 009 - 1000+ employees
  • Use Case: Analyze by business size

Geographic Component

  • Parameter: GEOCOMP
  • Options:
    • 00 - Total
    • 01 - In metropolitan statistical area
    • 02 - Not in metropolitan statistical area
  • Note: Use with METRO parameter

Time Parameters

YEAR

  • Required: No (optional for time series)
  • Format: 4-digit year (e.g., 2023)
  • Range: 1978 to present
  • Use Case:
    • Single year: YEAR=2023
    • Time series: Omit YEAR to get all years
    • Multiple years: Make separate calls or omit YEAR

Example API Calls

Example 1: National Business Startups (2023)

GET https://api.census.gov/data/timeseries/bds
Parameters:
  get: ESTABS_ENTRY,ESTABS_ENTRY_F,JOB_CREATION_BIRTHS,JOB_CREATION_BIRTHS_F
  for: us:*
  YEAR: 2023
  key: YOUR_API_KEY

Example 2: California Business Formations by Industry

GET https://api.census.gov/data/timeseries/bds
Parameters:
  get: ESTABS_ENTRY,FIRMBIRTH_FIRMS,JOB_CREATION_BIRTHS
  for: state:06
  YEAR: 2023
  NAICS2017: 54
  key: YOUR_API_KEY

Example 3: Job Creation by Firm Size (All States)

GET https://api.census.gov/data/timeseries/bds
Parameters:
  get: JOB_CREATION,JOB_CREATION_BIRTHS,NET_JOB_CREATION
  for: state:*
  YEAR: 2023
  EMPSZFI: 001
  key: YOUR_API_KEY

Example 4: Time Series - Business Formations (2010-2023)

GET https://api.census.gov/data/timeseries/bds
Parameters:
  get: ESTABS_ENTRY,FIRMBIRTH_FIRMS
  for: us:*
  # Omit YEAR to get all years
  key: YOUR_API_KEY

Common Variable Combinations for Business Initiative

Startup Analysis

Variables: ESTABS_ENTRY, FIRMBIRTH_FIRMS, JOB_CREATION_BIRTHS
Geography: state:* or us:*
Use: Compare startup rates across states/industries

Survival Analysis

Variables: ESTABS_ENTRY, ESTABS_EXIT, FIRMDEATH_FIRMS
Geography: us:* or state:*
Filter: AGE (to analyze by firm age)
Use: Business failure rates, survival statistics

Job Creation Analysis

Variables: JOB_CREATION, JOB_CREATION_BIRTHS, NET_JOB_CREATION
Geography: state:* or county:*
Filter: NAICS2017 (by industry)
Use: Employment growth, industry job creation

Industry Comparison

Variables: ESTABS_ENTRY, JOB_CREATION, FIRM
Geography: us:*
Filter: NAICS2017 (compare multiple industries)
Use: Which industries are growing fastest

Data Limitations & Notes

  1. Suppression: Small cell counts are suppressed (flagged as “D”)
  2. Time Lag: Data typically available 1-2 years after reference year
  3. Geographic Detail: County-level data may have more suppression
  4. Industry Detail: More detailed NAICS codes have more suppression
  5. Flag Variables: Always check _F variables for data quality

MCP Tool Usage

Tool Name: fetch_census_bds_data

Example Call:

{
  "variables": ["ESTABS_ENTRY", "JOB_CREATION_BIRTHS", "NET_JOB_CREATION"],
  "year": 2023,
  "geography": "state:06",
  "filters": {"NAICS2017": "54"}
}

References

  • Official Documentation: https://www.census.gov/data/developers/data-sets/business-dynamics-statistics.html
  • API User Guide: https://www.census.gov/data/developers/guidance/api-user-guide.html
  • Variable Definitions: https://www.census.gov/data/developers/data-sets/business-dynamics-statistics/bds-api.html