Intangible Capital and Measured Productivity

Because firms invest heavily in R&D, software, brands, and other intangible assets—at a rate close to that of tangible assets—changes in measured GDP, which does not include all intangible investments, understate the actual changes in total output. If changes in the labor input are more precisely measured, then it is possible to observe little change in measured total factor productivity coincidentally with large changes in hours and investment. This mismeasurement leaves business cycle modelers with large and unexplained labor wedges accounting for most of aggregate fluctuations. Intangible investments are introduced in a multi-sector general equilibrium model with income and cost shares matched to data from the U.S. input and output tables, which now include some intangible investments along with final goods and services. I use MLE methods and observations on sectoral business receipts and per capita hours to estimate processes for latent sectoral TFPs--that have common and idiosyncratic components—-and a time-varying labor wedge. I find that the model’s common TFP component accounts for most of the variation in the observed series, including the downturn of 2008–2009, while the time-varying labor wedge accounts for almost none. The correlation of the model’s common TFP component and measured U.S. TFP is roughly zero.