Changing Business Dynamism and Productivity: Shocks vs. Responsiveness

The pace of business dynamism as measured by indicators such as job reallocation has declined in recent decades in the U.S., and theory suggests that this may have implications for productivity. The declining dynamism in sectors like Retail Trade disproportionately accounted for these trends in the 1980s and 1990s, and was productivity enhancing. In contrast, the pace of reallocation in High-Tech industries has a rising then falling pattern during the 1990s and 2000s that mimics the pattern of U.S. productivity growth. We investigate whether these trends in dynamism and productivity are related by drawing insights from canonical models of firm dynamics. Focusing on the High-Tech sector, we ask whether observed patterns of reallocation reflect changes in the volatility of idiosyncratic productivity shocks or changes in the marginal responsiveness of businesses to those shocks. Using Manufacturing TFP data we show that shock volatility rises over time but that the plant-level marginal responsiveness of business growth to productivity rises then falls in tandem with the hump-shaped behavior of both job reallocation and productivity growth in the High-Tech sector. The results are particularly notable for young businesses. During the 1990s, rising responsiveness yields an increase in the contribution of reallocation to productivity growth of as much as half a log point per year; during the post-2000 period, responsiveness declines precipitously implying as much as a two log point per year reduction in the annual contribution of reallocation to industry-level productivity growth. Using new economywide data on firm-level labor productivity, we further show that the post-2000 Manufacturing results generalize to the entire U.S. economy and the broad High-Tech sector specifically. Rising within-industry dispersion in firm-level labor productivity in the post-2000 period is consistent with an increase in frictions or distortions in the U.S. economy. *Board of Governors of the Federal Reserve System, University of Maryland and NBER, U.S. Census Bureau, and U.S. Census Bureau, respectively. We gratefully acknowledge financial support from the Kauffman Foundation. Cody Tuttle provided excellent research assistance. We thank John Abowd, Rudi Bachmann, Martin Baily, Dave Byrne, Chris Foote, Lucia Foster, Bronwyn Hall, Kristin McCue, and conference or seminar participants at the 2015 Atlanta Fed Conference on Secular Changes in Labor Markets, the ASSA 2016 meetings, the 2016 Brookings “productivity puzzle” conference, the 3rd International ZEW conference, the 2016 ICC conference, Drexel University, the Federal Reserve Board, George Mason University, Georgetown University and the New York Fed for helpful comments. We are grateful for the use of the manufacturing productivity database developed in Foster, Grim and Haltiwanger (2016) as well as the revenue productivity database developed in Haltiwanger et al. (2016), and we thank Peter Schott for providing guidance and data for constructing import penetration data. Any opinions and conclusions expressed herein are those of the authors and do not necessarily represent the views of the U.S. Census Bureau or of the Board of Governors or its staff. All results have been reviewed to ensure that no confidential information is disclosed.