. "4 Limitations of the Current Data System for Measuring Business Dynamics." Understanding Business Dynamics: An Integrated Data System for America's Future. Washington, DC: The National Academies Press, 2007.
The following HTML text is provided to enhance online
readability. Many aspects of typography translate only awkwardly to HTML.
Please use the page image
as the authoritative form to ensure accuracy.
Understanding Business Dynamics: An Integrated Data System for America’s Future
capital equipment, or human capital. Recent studies (e.g., Becker et al., 2005) show that investment rates in physical capital by very young businesses are high, but these businesses are not covered in a representative manner by surveys of capital expenditures. There is a paucity of data on the activities of the nonemployer universe of firms, and even less is known about the transitions and interactions between the employer and nonemployer universes. Data on this transitional phase are essential for understanding the entrepreneurial process whereby firms evolve to the point at which workers are hired. Moreover, the level of activity in the nonemployer universe of firms is substantial. Census Bureau figures indicate that there are over 18 million nonemployer firms in the United States—roughly three times the number of employer firms. In general, little is known about the evolution of these firms (Davis et al., 2006).
While data on the universe of nonemployer firms (which is dominated by very small producers) actively engaged in business are sparse, even less is known about the firm-formation process in the preproduction phase. Before the presence of activity by a new entity can be detected in a business register, it must have either positive sales or employment (the two standard ways that administrative systems identify firms). In order to learn about entrepreneurial activities in the preproduction stage, a different data collection approach that surveys households or individuals (e.g., the Current Population Survey [CPS]) is most likely required. Fairlie (2006) uses the CPS questions about self-employment income to identify entrepreneurial activity, and the Kauffmann Foundation publishes an index of entrepreneurial activity based on these data. In order to measure entrepreneurial activities in the preproduction phase (before income is earned and tax returns are filed), one must ask specific questions about the topic in household surveys such as the CPS or perhaps BLS’s American Time Use Survey.
Fairlie enumerated a list of advantages of data collected from households relative to that collected from businesses. Household data sources currently offer comparatively large sample sizes and long time series; more timely estimates of business ownership and entrepreneurship; built-in comparison groups of nonbusiness owners; the potential, when in panel form, for measuring entrepreneurship, business creation, transitions into and out of self-employment,11 and for examining income growth (e.g., the National
By linking the CPS files over time, longitudinal data can be created, which allows business creation to be examined. The Kauffman Index of Entrepreneurial Activity attempts to do just this: using matched data from the 1996-2004 CPS, all individuals ages 20-64 who do not own a business as their main job are identified in the first survey month. It is then determined whether these individuals own a business as their main job (15 or more hours typically worked per week) in the following survey month. Unfortunately, at the present time very little information is obtained about the nature of these new business activities.