1. Richard Clayton and Akbar Sadeghi
Measuring American Entrepreneurship: New Data from the Bureau of Labor Statistics
Richard Clayton and Akbar Sadeghi
US Bureau of Labor Statistics
International Roundtable on Business Survey Frames
Wiesbaden, Germany
October 2007
Appreciation to Dave Talan, Merissa Piazza and Carol Leming

2. Goals & Data Source To profile “early research” data
To provide a platform for identifying strengths and weaknesses
To help identify definitional issues
Source: Quarterly Census of Employment and Wages (QCEW), a BLS program
quarterly employment and wages
Available with 4 month lag, published with 6 month lag
about 9 million establishments
linked longitudinally (1990-current quarter)

3. Profile of New Research Data
These are early research results developed to help BLS and the OECD Steering Group develop new data definitions. These data are not official, not for citation.
Births/deaths
Towards High Growth measures: profile of 7 year survivors
Age profile of US businesses
Business Density for the US States

4. Desired Characteristics of Entrepreneurship Data
Accurate, timely, relevant
Frequent and current: these features allow us to see whether policy changes have positive effects in short order.
Reasonable data movements
Detailed industry
Detailed geography
Satisfies users?

5. Birth and Death Rates

6. Number of Openings: Births

7. Gross Jobs from Openings/ Births

8. Average Employment Size of Births

9. Average size of Establishment Birth vs
Average size of Establishment Birth vs. Multifactor Productivity: Does productivity account for size decline?

10. Job Growth vs. Establishment Growth

11. Firms Births per 1000 in Labor Force

12. Age: Share of Employment and Number of Establishments in Q3/06

13. Recession

14. Survival Rates vs. Employment of Survivors
Recession

15. Recession

16. Survival over Seven Years
Survival rates continue to be fairly stable across industries
Surviving establishments continue to grow over their lifetime
A greater percentage of establishments survive in the fifth year and beyond
WE’ve added only one new conclusion to our study, that surviving establishments have a greater chance of survival if they have survived to the fourth year.
Reiterate that future analysis will extend to:
Size class
Finer industry detail
Characteristics of seven year survivors

17. What can Survivors Tell Us?
Recession
What are the characteristics of surviving establishments?

18. What can Survivors Tell Us?
Recession
Do most new firms get to their “operating level or satisfy business model” very quickly?

19. Percentage Distribution of Growth Rates of Survivors (Seven Year Annual Average)
200
175
Percent
150
125
100 75
≈ 66,000 units
48 units 50 25
-500
500
1500
2500
3500
4500
5500
6500
7500
8500
9500
Seven Year Annual Average Growth Rate (survivors only)
Looking at the distribution of the seven year average growth rate one can see that it is concentrated around zero

20. Percentage Distribution of Growth Rates of Survivors (-15<Growth>15, Seven Year Annual Average) 25 20
≈ 5% of units grew by 14% over the seven years
Percent 15 10 5 By
-25
-21
-17
-13 -9 -5 -1 1 5 9 13 17 21 25
Seven Year Annual Average Growth Rate (survivors only)
The majority of the cohort has growth rates, on average over the seven years, from -25% to 25%

21. Characteristics of Survival: Growth Rates
The average growth rate of all surviving establishments over the full seven year period
= 21.4%
Largest growth is in the first year, again, businesses reach their target level quickly
Most growth is concentrated on average over the seven years from -25% to 25%

22. Thoughts: Definitional Issues of High Growth
Questions to ask when defining high growth:
Do we use all units? Or just survivors?
Trigger:
10 employees?
Greater than15% growth?
Size trigger vs. Age trigger?

23. Business Density by State 2005 Number of Business Establishments Working Age Population (Age 18-64)

24. Next Steps We will expand on these and other measures
Adjust definitions to reveal sensitivity to alternatives
Retab by industry to see if this is really changes in industry composition vs. other economic factors.