of the business population that are most likely to be in transition and that provide early indicators of the future directions of the economy.
To measure business dynamics more effectively, the Census Bureau and the Bureau of Labor Statistics (BLS) should increase the sampling of younger units in their surveys. This will require that business age be included as one of the stratifying variables and that business lists, on which the surveys are based, cover recent business entrants.
Given the panel’s conclusion that essential policy-based research relies on information about new businesses, it follows that key data programs must keep track of how long business entities have existed. Business statistics in the federal system are regularly disaggregated along other dimensions—by firm or establishment size, for example—but very little information is systematically produced or tabulated by age. However, it is clear that a better understanding of dynamic trends in industry evolution, firm entry into markets, and the productivity impact of new firms requires data on business age.
The Census Bureau and BLS should exploit their administrative record systems to produce public-release statistics on economic activity disaggregated by indicators of business age. Readily available business age indicators in these administrative records systems include the application date for an Employer Identification Number, the point at which positive revenues are generated, and the first period with positive payroll.
A focus on publishing statistics by business age would also be compatible with the recent innovations in measuring producer dynamics, such as those developed in association with the Business Employment Dynamics (BED) program produced by BLS and the Statistics of U.S. Businesses (SUSB) produced by the Census Bureau (and the closely related Longitudinal Business Database (LBD) microdata program at the Census Bureau).
Because current data collection focuses on larger business entities and traditional sectors and employment arrangements, activities associated with some of the most interesting and rapidly changing components of the economy are imprecisely, or slow to be, detected. Measurement and analysis of the processes through which businesses are born and grow require going beyond conventional data collection from employer businesses. The most direct way to get at early life-cycle dynamics involves focusing on household or individual units. While there are limitations to household-based data, such as the typical absence of information on business performance, they can be used as a screening vehicle for identifying nascent and young businesses and, subsequently, for generating information on their