and Daniel SichelFederal Reserve Board, Washington DC Published macroeconomic data traditionally exclude most intangible investment from measured GDP. This situation is beginning to change, but our estimates suggest that as much as $800 billion is still excluded from U.S. published data (as of 2003), and that this leads to the exclusion of more than $3 trillion of business intangible capital stock. To assess the importance of this omission, we add intangible capital to the standard sources-of-growth framework used by the BLS, and find that the inclusion of our list of intangible assets makes a significant difference in the observed patterns of U.S. economic growth. The rate of change of output per worker increases more rapidly when intangibles are counted as capital, and capital deepening becomes the unambiguously dominant source of growth in labor productivity. The role of multifactor productivity is correspondingly diminished, and labor's income share is found to have decreased significantly over the last 50 years. Introduction and BackgroundThe revolution in information technology is apparent in the profusion of new products available in the marketplace (goods with the acronyms PCs, PDAs, ATMs, wi-fi), as well as items like the internet, cell phones, and e-mail. These innovations are part of a broader technological revolution based on the discovery of the semiconductor, often called the "IT revolution." However, while its effects are apparent in the marketplace, its manifestation in the macroeconomic statistics on growth has been slow to materialize. Writing in 1987, Robert Solow famously remarked that "you see the computer revolution everywhere except in the productivity data" (Solow, 1987). Some ten years later, Alan Greenspan observed that the negative trends in measured productivity observed in many services industries seemed inconsistent with the fact that they ranked among the top computer-using 1 Greenspan also questioned the accuracy of the consumer price index, in part because of its failure to adequately account for the new or superior goods made possible by the IT revolution. 2 The IT revolution began to appear in the productivity data in the mid-1990s. This pickup has been linked to investment in IT capital in a series of papers (Jorgenson and Stiroh, 2000;Oliner andSichel, 2000, 2002;Jorgenson et al., 2002;Stiroh, 2002), all of which estimate the contribution of IT capital to output growth within the Solow-Jorgenson-Griliches sources-of-growth (SOG) framework. However, the productivity pickup did not remove all suspicion about the ability of official data to accurately capture the factors that affect U.S. economic growth. Both firm-level and national income accounting practice have historically treated expenditure on intangible inputs such as software and R&D as an intermediate expense and not as an investment that is part of GDP. The exclusion of intangibles obscures the role of many factors at the center of the innovation process that have, according to available evidence, played an importan...

T he performance of the U.S. economy over the past several years has been nothing short of remarkable. From 1995 through 1999, real gross domestic product rose at an annual rate of more than 4 percent (based on annual average data), a notable step-up from the pace during the first four years of this expansion . The rapid advance in recent years has been driven by a rebound in the growth of labor productivity. In the nonfarm business sector-the part of the economy on which productivity studies typically focus-output per labor hour rose at about a 2 1 ⁄2 percent annual rate between 1995 and 1999, nearly double the average pace of the preceding 25 years. Determining the source of this resurgence ranks among the key issues now facing economists.An obvious candidate is the high-tech revolution spreading through the U.S. business sector. In an effort to reduce costs, to coordinate large-scale operations, and to provide new or enhanced services, American firms have been investing in information technology at a furious pace. Indeed, business investment in computers and peripheral equipment, measured in real terms, jumped more than four-fold between 1995 and 1999. Outlays have also risen briskly for software and communication equipment, which are crucial components of computer networks.We first examined the link between computers and growth in Oliner and Sichel (1994). At that time, many observers were wondering why productivity growth had failed to revive despite the billions of dollars that U.S. companies had poured into information technology over the preceding decade. We concluded that, in fact, there was no puzzle-just unrealistic expectations. Using a standard neoclassical growth accounting framework, we showed that computers should not

Business outlays on intangible assets are usually expensed in economic and financial accounts. Following Hulten (1979), this paper develops an intertemporal framework for measuring capital in which consumer utility maximization governs the expenditures that are current consumption versus those that are capital investment. This framework suggests that any business outlay that is intended to increase future rather than current consumption should be treated as capital investment. Applying this principle to newly developed estimates of business spending on intangibles, we find that, by about the mid-1990s, business investment in intangible capital was as large as business investment in traditional, tangible capital. Relative to official measures, our framework portrays the U.S. economy as having had higher gross private saving and, under plausible assumptions, fractionally higher average annual rates of change in real output and labor productivity from 1995 to 2002.

This paper distinguishes two types of asymmetry in business cycles: deepness and steepness. Deepness is defined as the characteristic that troughs are further below trend than peaks are above. Most previous research has focused exclusively on steepness, which refers to cycles in which contractions are steeper than expansions. A test for deepness is proposed and applied to U.S. post‐war quarterly unemployment, real GNP, and industrial production. Evidence of deepness is found for unemployment and industrial production, while the evidence for real GNP is weaker. Previous evidence of steepness in unemployment is confirmed.