The pace of job reallocation has declined in the United States in recent decades. We draw insight from canonical models of business dynamics in which reallocation can decline due to (i) lower dispersion of idiosyncratic shocks faced by businesses, or (ii) weaker marginal responsiveness of businesses to shocks. We show that shock dispersion has actually risen, while the responsiveness of business-level employment to productivity has weakened. Moreover, declining responsiveness can account for a significant fraction of the decline in the pace of job reallocation, and we find suggestive evidence this has been a drag on aggregate productivity.

Many observers, and many investors, believe that young people are especially likely to produce the most successful new firms. Integrating administrative data on firms, workers, and owners, we study start-ups systematically in the United States and find that successful entrepreneurs are middle-aged, not young. The mean age at founding for the 1-in-1,000 fastest growing new ventures is 45.0. The findings are similar when considering high-technology sectors, entrepreneurial hubs, and successful firm exits. Prior experience in the specific industry predicts much greater rates of entrepreneurial success. These findings strongly reject common hypotheses that emphasize youth as a key trait of successful entrepreneurs.

Modern market economies are characterized by the reallocation of resources from less productive, less valuable activities to more productive, more valuable ones. Businesses in the High Tech sector play a particularly important role in this reallocation by introducing new products and services that impact the entire economy. In this paper we describe an extension to the Census Bureau’s Business Dynamics Statistics that tracks job creation, job destruction, startups, and exits by firm and establishment characteristics, including sector, firm age, and firm size in the High Tech sector. We preview the resulting statistics, showing the structural shifts in the High Tech sector over the past 30 years, including the surge of entry and young firm activity in the 1990s that reversed abruptly in the early‐2000s.

The field of entrepreneurship is growing rapidly and expanding into new areas. This article presents a new compilation of administrative panel data on the universe of business start-ups in the United States, which will be useful for future research in entrepreneurship. To create the US start-up panel data set, the authors link the universe of non-employer firms to the universe of employer firms in the Longitudinal Business Database (LBD). Start-up cohorts of more than five million new businesses per year, which create roughly three million jobs, can be tracked over time. To illustrate the potential of the new start-up panel data set for future research, the authors provide descriptive statistics for a few examples of research topics using a representative start-up cohort.

We use Hurricane Katrina’s damage to the Mississippi coast in 2005 as a natural experiment to study business survival in the aftermath of a capital-destruction shock. We find very low survival rates for businesses that incurred physical damage, particularly for small firms and less-productive establishments. Conditional on survival, larger and more-productive businesses that rebuilt their operations hired more workers than their smaller and less-productive counterparts. Auxiliary evidence from the Survey of Business Owners suggests that the differential size effect is tied to the presence of financial constraints, pointing to a socially inefficient level of exits and to distortions of allocative efficiency in response to this negative shock. Over time, the size advantage disappeared and market mechanisms seem to prevail.

This paper provides theory and evidence on micro-level pricing behavior needed to model an aggregate New Keynesian Phillips Curve. We start with individual firms that are heterogeneous in their production technology and in the demand curves they face. We estimate the parameters of supply and demand curves by utilizing prices and quantities of outputs and factor inputs of firms along with exogenous downstream demand instruments from global input-output and trade data. The research addresses model heterogeneity using a clustering method to classify firms according to their production technology and observed price pass-through. The results show that more productive firms exhibit a lower price response to changes in demand. We find that the aggregate price response to demand shocks will be smaller when more productive firms absorb a larger portion of demand shocks, which generally is the case. At the same time, our results imply that idiosyncratic shifts in demand to clusters of firms with more rapidly rising marginal cost curves, or cost shocks to clusters of firms with high pass-through, will result in a higher aggregate price response. Finally, this paper provides a framework to incorporate heterogeneous pricing behavior into an estimate of the slope of the aggregate Phillips Curve.

This paper develops a micro-founded framework linking price-cost and wage markups to intangible assets. Intangible assets, once created, are a source of firm rents. Owing to limits to enforceable ownership and the non-rival nature of knowledge, these rents can be both retained by the origin firm and transferred to a competitor through poaching of workers. Search and matching frictions affect labor mobility and result in bargaining over rents between the firm and the worker. This environment generates hold-up in intangible asset creation and motivates rent sharing. Under non-compete agreements, poached workers face start delays that weaken outside options. Using microdata from the Netherlands, we document higher price-cost and wage markups in more intangible-intensive firms and lower wages for workers with non-compete agreements, consistent with the model.

Utilizing near real-time QuickBooks data from over 1.6 million small businesses and a targeted survey, this paper highlights the critical role credit card financing plays for small business activity. We examine a two year period beginning in January of 2021. A turbulent period during which, credit card usage by small U.S. businesses nearly doubled, interest payments rose by 60%, and delinquencies reached 2.8%. We find, first, monthly credit card payments were up to three times higher than loan payments during this time. Second, we use targeted surveys of these small businesses to establish credit cards as a key financing source in response to firm-level shocks, such as uncertain cash flows and overdue invoices. Third, we establish the importance of credit cards as an important financial transmission mechanism. Following the Federal Reserve’s rate hikes in early 2022, banks cut credit card supply, leading to a 15.75% drop in balances and a 10% decline in revenue growth, as well as a 1.5% decrease in employment growth among U.S. small businesses. These higher rates also rendered interest payments unsustainable for many, contributing to half of the observed increase in delinquencies. Lastly, a simple heterogeneous firm model with a cash-in-hand constraint illustrates the significant macroeconomic impact of credit card financing on small business activity.

We document and dissect a new stylized fact about firm growth: the shift from labor to intermediate inputs. This shift occurs in input quantities, cost and output shares, and output elasticities. We establish this fact using German firm-level data and replicate it in administrative firm data from 11 additional countries. We also document these patterns in micro-aggregated industry data for 20 European countries (and, with respect to industry cost shares, for the US). We rationalize this novel regularity within a parsimonious model featuring (i) an elasticity of substitution between intermediates and labor that exceeds unity, and (ii) an increasing shadow price of labor relative to intermediates, due to monopsony power over labor or labor adjustment costs. The shift from labor to intermediates accounts for one half to one third of the decline in the labor share in growing firms (the remainder is due to wage markdowns and markups) and rationalizes most of the labor share decline in growing industries.

We study changes in job reallocation in Europe after 2000 using novel microaggregated data that we collected for 19 European countries. In all countries, we document broad-based declines in job reallocation rates that concern most economic sectors and size classes. These declines are mainly driven by dynamics within sectors, size, and age classes rather than by compositional changes. Simultaneously, employment shares of young firms decline. Consistent with US evidence, firms’ employment has become less responsive to productivity shocks. However, the dispersion of firms’ productivity shocks has decreased too. To enhance our understanding of these patterns, we derive and apply a firm-level framework that relates changes in firms’ market power, labor market imperfections, and production technology to firms’ responsiveness and job reallocation. Using German firm-level data, we find that changes in markups and labor output elasticities, rather than adjustment costs, are key in rationalizing declining responsiveness.