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 (TFP) coincidentally with large changes in hours and investment. This mismeasurement leaves business cycle modelers with large and unexplained labor wedges accounting for most of the fluctuations in aggregate data. In this paper, I incorporate intangible investments into a multi-sector general equilibrium model and parameterize income and cost shares using data from the U.S. input and output tables, with intangible investments added to final goods and services. I use maximum likelihood methods and observations on sectoral gross outputs and per capita hours for the period 1948–2014 to estimate processes for latent sectoral TFPs—that have common and idiosyncratic components—and a time-varying labor wedge. I find that neither a large and unexplained labor wedge nor a large common TFP shock is needed to account for fluctuations in these data. ∗ The views expressed herein are those of the authors and not necessarily those of the Federal Reserve Bank of Minneapolis or the Federal Reserve System.