Gig work mediated through online platforms has received much recent attention. We find only one sector—the transportation services sector—in which there is unambiguous evidence of substantial and rapidly growing gig activity. A challenge for tracking and understanding the rise in gig activity is that core household surveys are missing the recent overall rise in self-employment that is apparent in administrative and private sector transactions data. We show that this limitation of available household survey data is evident even in the transportation services sector, where the growth in self-employment activity since 2013 has been exponential.

Gig work mediated through online platforms has received much recent attention. We find only one sector—the transportation services sector—in which there is unambiguous evidence of substantial and rapidly growing gig activity. A challenge for tracking and understanding the rise in gig activity is that core household surveys are missing the recent overall rise in self-employment that is apparent in administrative and private sector transactions data. We show that this limitation of available household survey data is evident even in the transportation services sector, where the growth in self-employment activity since 2013 has been exponential.

Key macro indicators such as output, productivity, and inflation are based on a complex system across multiple statistical agencies using different samples and levels of aggregation. The Census Bureau collects nominal sales, the Bureau of Labor Statistics collects prices, and the Bureau of Economic Analysis constructs nominal and real GDP using these data and other sources. The price and quantity data are integrated at a high level of aggregation. This paper explores alternative methods for reengineering key national output and price indices using item-level data. Such reengineering offers the promise of greatly improved key economic indicators along many dimensions.

Key macro indicators such as output, productivity, and inflation are based on a complex system across multiple statistical agencies using different samples and levels of aggregation. The Census Bureau collects nominal sales, the Bureau of Labor Statistics collects prices, and the Bureau of Economic Analysis constructs nominal and real GDP using these data and other sources. The price and quantity data are integrated at a high level of aggregation. This paper explores alternative methods for reengineering key national output and price indices using item-level data. Such reengineering offers the promise of greatly improved key economic indicators along many dimensions.

Gig work mediated through online platforms has received much recent attention. We find only one sector—the transportation services sector—in which there is unambiguous evidence of substantial and rapidly growing gig activity. A challenge for tracking and understanding the rise in gig activity is that core household surveys are missing the recent overall rise in self-employment that is apparent in administrative and private sector transactions data. We show that this limitation of available household survey data is evident even in the transportation services sector, where the growth in self-employment activity since 2013 has been exponential.

An optimal pace of business dynamics—encompassing the processes of entry, exit, expansion, and contraction—would balance the benefits of productivity and economic growth against the costs to firms and workers associated with reallocation of productive resources. It is difficult to prescribe what the optimal pace should be, but evidence accumulating from multiple datasets and methodologies suggests that the rate of business startups and the pace of employment dynamism in the US economy has fallen over recent decades and that this downward trend accelerated after 2000. A critical factor in accounting for the decline in business dynamics is a lower rate of business startups and the related decreasing role of dynamic young businesses in the economy. For example, the share of US employment accounted for by young firms has declined by almost 30 percent over the last 30 years. These trends suggest that incentives for entrepreneurs to start new firms in the United States have diminished over time. We do not identify all the factors underlying these trends in this paper but offer some clues based on the empirical patterns for specific sectors and geographic regions.

Private equity critics claim that leveraged buyouts bring huge job losses and few gains in operating performance. To evaluate these claims, we construct and analyze a new dataset that covers US buyouts from 1980 to 2005. We track 3,200 target firms and their 150,000 establishments before and after acquisition, comparing to controls defined by industry, size, age, and prior growth. Buyouts lead to modest net job losses but large increases in gross job creation and destruction. Buyouts also bring TFP gains at target firms, mainly through accelerated exit of less productive establishments and greater entry of highly productive ones. (JEL D24, G24, G32, G34, J23, J63, L25)

An optimal pace of business dynamics—encompassing the processes of entry, exit, expansion, and contraction—would balance the benefits of productivity and economic growth against the costs to firms and workers associated with reallocation of productive resources. It is difficult to prescribe what the optimal pace should be, but evidence accumulating from multiple datasets and methodologies suggests that the rate of business startups and the pace of employment dynamism in the US economy has fallen over recent decades and that this downward trend accelerated after 2000. A critical factor in accounting for the decline in business dynamics is a lower rate of business startups and the related decreasing role of dynamic young businesses in the economy. For example, the share of US employment accounted for by young firms has declined by almost 30 percent over the last 30 years. These trends suggest that incentives for entrepreneurs to start new firms in the United States have diminished over time. We do not identify all the factors underlying these trends in this paper but offer some clues based on the empirical patterns for specific sectors and geographic regions.

Private equity critics claim that leveraged buyouts bring huge job losses and few gains in operating performance. To evaluate these claims, we construct and analyze a new dataset that covers US buyouts from 1980 to 2005. We track 3,200 target firms and their 150,000 establishments before and after acquisition, comparing to controls defined by industry, size, age, and prior growth. Buyouts lead to modest net job losses but large increases in gross job creation and destruction. Buyouts also bring TFP gains at target firms, mainly through accelerated exit of less productive establishments and greater entry of highly productive ones. (JEL D24, G24, G32, G34, J23, J63, L25)

Private equity critics claim that leveraged buyouts bring huge job losses and few gains in operating performance. To evaluate these claims, we construct and analyze a new dataset that covers US buyouts from 1980 to 2005. We track 3,200 target firms and their 150,000 establishments before and after acquisition, comparing to controls defined by industry, size, age, and prior growth. Buyouts lead to modest net job losses but large increases in gross job creation and destruction. Buyouts also bring TFP gains at target firms, mainly through accelerated exit of less productive establishments and greater entry of highly productive ones. (JEL D24, G24, G32, G34, J23, J63, L25)