The U.S. retail trade sector underwent a massive restructuring and reallocation of activity in the 1990s with accompanying technological advances. Using a data set of establishments in that sector, we quantify and explore the relationship between this restructuring and reallocation and labor productivity dynamics. We find that virtually all of the labor productivity growth in the retail trade sector is accounted for by more productive entering establishments displacing much less productive exiting establishments. The productivity gap between low-productivity exiting single-unit establishments and entering high-productivity establishments from large, national chains plays a disproportionate role in these dynamics. Copyright by the President and Fellows of Harvard College and the Massachusetts Institute of Technology.

The high pace of reallocation across producers is pervasive in the US economy. Evidence shows that this high pace of reallocation is closely linked to productivity. While these patterns hold on average, the extent to which the reallocation dynamics in recessions are “cleansing” is an open question. We find that downturns prior to the Great Recession are periods of accelerated reallocation even more productivity enhancing than reallocation in normal times. In the Great Recession, we find that the intensity of reallocation fell rather than rose and that the reallocation that did occur was less productivity enhancing than in prior recessions.

Using establishment‐level data, we shed light on the sources of the changes in the structure of production, wages, and employment that have occurred over recent decades. Our findings are: (1) the between‐plant component of wage dispersion is an important and growing part of total wage dispersion; (2) much of the between‐plant increase in wage dispersion is within industries; (3) the between‐plant measures of wage and productivity dispersion have increased substantially over recent decades; and (4) a significant fraction of the rising dispersion in wages and productivity is accounted for by changes in the distribution of computer investment across plants.

There is considerable evidence that producer-level churning contributes substantially to aggregate (industry) productivity growth, as more productive businesses displace less productive ones. However, this research has been limited by the fact that producer-level prices are typically unobserved; thus within-industry price differences are embodied in productivity measures. If prices reflect idiosyncratic demand or market power shifts, high "productivity" businesses may not be particularly efficient, and the literature's findings might be better interpreted as evidence of entering businesses displacing less profitable, but not necessarily less productive, exiting businesses. In this paper, we investigate the nature of selection and productivity growth using data from industries where we observe producer-level quantities and prices separately. We show there are important differences between revenue and physical productivity. A key dissimilarity is that physical productivity is inversely correlated with plant-level prices while revenue productivity is positively correlated with prices. This implies that previous work linking (revenue-based) productivity to survival has confounded the separate and opposing effects of technical efficiency and demand on survival, understating the true impacts of both. We further show that young producers charge lower prices than incumbents, and as such the literature understates the productivity advantage of new producers and the contribution of entry to aggregate productivity growth.

We explore current interpretations of firm-level dispersion in revenue-based productivity measures. Since revenue function estimates using proxy methods differ from factor elasticities, the residual emerging from this method remains a combination of demand and technical effciency shocks, and is not equal to the concept of revenue productivity that plays an important role in recent literature on misallocation. This has implications for applications where measured revenue productivity dispersion is used as an indicator of misallocation. Our empirical evidence suggests, under iso-elastic demand, measured dispersion may indicate either distortions or variation in demand shocks and technical effciency or all of the above.

Partnering with the US Census Bureau, we implement a new survey of “structured” management practices in two waves of 35,000 manufacturing plants in 2010 and 2015. We find an enormous dispersion of management practices across plants, with 40 percent of this variation across plants within the same firm. Management practices account for more than 20 percent of the variation in productivity, a similar, or greater, percentage as that accounted for by R&D, ICT, or human capital. We find evidence of two key drivers to improve management. The business environment, as measured by right-to-work laws, boosts incentive management practices. Learning spillovers, as measured by the arrival of large “Million Dollar Plants” in the county, increases the management scores of incumbents.