ment, investment, prices, and productivity, but it also should allow research that requires use of microdata. In particular, as noted above, individual-level business data are important for studying such areas as productivity growth, firm entry and exit, the role of young and small businesses in fueling economic growth, the characteristics of business owners, and the interactions between large and small businesses. A system capable of such analyses must thus collect a range of key data items beyond the basic information contained in the business register, although the register is certainly one important input. Measurement of transitions (e.g., mergers, acquisitions, and spin-offs) allows researchers to identify such things as expanding employment areas, structural changes in the economy, and business cycle turning points.
Just as important as the capacity to track transitions for existing businesses is the ability to detect the birth and growth of new firms. Maintaining ownership type and owner demographics on the business register is just the first step. The data system must also facilitate measurement of gross flows from employee to self-employed categories. To best understand these nascent entrepreneurs, additional information is necessary. First, it would be useful to be able to identify the location of self-employment—specifically, whether the business activity takes place at home or somewhere else. Data capturing time use in different business activities are also essential.
In order to understand the underlying sources of growth in the economy, data are needed on a range of business attributes that may be linked to performance. Tangible capital is one important area for which information is sparse, particularly for small firms. Becker et al. (2006) have shown that, in the Annual Capital Expenditures Survey, entrants and younger firms are underrepresented, even though the evidence suggests that capital expenditures in the start-up process of businesses are high. If true, the current survey is missing an important, and nonrandom, component of capital expenditures for U.S. businesses.
For new and growing firms, knowing more about financing is of particular interest. A business data system would, therefore, ideally include financial and balance sheet information, including equity, debt financing, and venture capital financing; measures of capital stocks and investments would also be useful. Important expenditures include investments in physical capital and also in technology and research and development (R&D), human capital, and organizational capital. Corrado, Hulten, and Sichel (2006) argue that better measurement is needed of three types of intangible capital: computerized information, knowledge acquired through scientific R&D and creative activities, and economic competencies. The ideal business data system would allow users to calculate intangible capital figures for such categories as stock of education and training in a firm and new investments in human capital and organizational capital. We emphasize