I develop an idea flows theory of firm and worker dynamics in order to assess the consequences of population aging. Older people are less likely to attempt entrepreneurship and switch employers because they have found better jobs. Consequently, aging reduces entry and worker mobility through a composition effect. In equilibrium, the lower entry rate implies fewer new, better job opportunities for workers, while the better matched labor market dissuades job creation and entry. Aging accounts for a large share of substantial declines in firm and worker dynamics since the 1980s, primarily due to equilibrium forces. Cross-state evidence supports these predictions.

Official statistics display a significant slowdown in U.S. aggregate productivity growth that begins in 2004. We show how offshore profit shifting by U.S. multinational enterprises affects GDP and, thus, productivity measurement. Under international statistical guidelines, profit shifting causes part of U.S. production generated by multinationals to be excluded from official measures of U.S. production. Profit shifting has increased significantly since the mid-1990s, resulting in lower measures of U.S. aggregate productivity growth. We construct an alternative measure of value added that adjusts for profit shifting. The adjustments raise aggregate productivity growth rates by 0.09 percent annually for 1994-2004, 0.24 percent annually for 2004-2008, and lowers annual aggregate productivity growth rates by 0.09 percent after 2008. Our adjustments mitigate, but do not eliminate, the measured productivity slowdown. The adjustments are especially large in R&D-intensive industries, which most likely produce intangible assets that facilitate profit shifting. The adjustments boost value added in these industries by as much as 8 percent in the mid-2000s.

Randomness in individual discovery tends to spread out productivities in a population, while learning from others keeps productivities together. In combination, these two mechanisms for knowledge accumulation give rise to long-term growth and persistent income inequality. This paper considers a world in which those with more useful knowledge can teach those with less useful knowledge, with competitive markets assigning students to teachers. In equilibrium, students who are able to learn quickly are assigned to teachers with the most productive knowledge. The long-run growth rate of this economy is governed by the rate at which the fastest learners can learn. The income distribution reflects learning ability and serendipity, both in individual discovery and in the assignment of students to teachers. Because of naturally arising indeterminacies in this assignment, payoff irrelevant characteristics can be predictors of individual income growth. Ability rents can be large when fast learners are scarce, when the process of individual discovery is not too noisy, and when overhead labor costs are low.

Innovative activities have public good characteristics in the sense that the cost of producing the innovation is high compared to the cost of producing subsequent units. Moreover, knowledge of how to produce subsequent units is widely known once the innovation has occurred and is, therefore, non-rivalrous. The main question of this paper is whether mechanisms can be found which exploit market information to provide appropriate incentives for innovation. The ability of the mechanism designer to exploit such information depends crucially on the ability of the innovator to manipulate market signals. We show that if the innovator cannot manipulate market signals, then the efficient levels of innovation can be implemented without deadweight losses–for example, by using appropriately designed prizes. If the innovator can use bribes, buybacks, or other ways of manipulating market signals, patents are necessary.

Given a common technology for replicating blueprints, high-quality blueprints will be replicated more quickly than low-quality blueprints. If quality begets quality, and firms are identified with collections of blueprints derived from the same initial blueprint, then, along a balanced growth path, Gibrat’s Law holds for every type of firm. A firm size distribution with the thick right tail observed in the data can then arise only when the number of blueprints in the economy grows over time, or else firms cannot grow at a positive rate on average. But when calibrated to match the observed firm entry rate and the right tail of the size distribution, this model implies that the median age among firms with more than 10,000 employees is about 750 years. The problem is Gibrat’s Law. If the relative quality of a firm’s blueprints depreciates as the firm ages, then the firm’s growth rate slows down over time. By allowing for rapid and noisy initial growth, this version of the model can explain high observed entry rates, a thick-tailed size distribution, and the relatively young age of large U.S. corporations.

This paper presents a simple model of search and matching between consumers and firms. The firm size distribution has a Pareto-like right tail if the population of consumers grows at a positive rate and the mean rate at which incumbent firms gain customers is also positive. This happens in equilibrium when entry is sufficiently costly. As entry costs grow without bound, the size distribution approaches Zipf’s law. The slow rate at which the right tail of the size distribution decays and the 10% annual gross entry rate of new firms observed in the data suggest that more than a third of all consumers must switch from one firm to another during a given year. A substantially lower consumer switching rate can be inferred only if part of the observed firm entry rate is attributed to factors outside the model. The realized growth rates of large firms in the model are too smooth.

During the Second Industrial Revolution, 1860–1900, many new technologies, including electricity, were invented. These inventions launched a transition to a new economy, a period of about 70 years of ongoing, rapid technical change. After this revolution began, however, several decades passed before measured productivity growth increased. This delay is paradoxical from the point of view of the standard growth model. Historians hypothesize that this delay was due to the slow diffusion of new technologies among manufacturing plants together with the ongoing learning in plants after the new technologies had been adopted. The slow diffusion is thought to be due to manufacturers’ reluctance to abandon their accumulated expertise with old technologies, which were embodied in the design of existing plants. Motivated by these hypotheses, we build a quantitative model of technology diffusion which we use to study this transition to a new economy. We show that it implies both slow diffusion and a delay in growth similar to that in the data.

Randomness in individual discovery disperses productivities, whereas learning from others keeps productivities together. Long-run growth and persistent earnings inequality emerge when these two mechanisms for knowledge accumulation are combined. This paper considers an economy in which those with more useful knowledge can teach others, with competitive markets assigning students to teachers. In equilibrium, students with an ability to learn quickly are assigned to teachers with the most productive knowledge. This sorting on ability implies large differences in earnings distributions conditional on ability, as shown using explicit formulas for the tail behavior of these distributions.

The Pareto-like tail of the size distribution of firms can arise from random growth of productivity or stochastic accumulation of capital. If the shocks that give rise to firm growth are perfectly correlated within a firm, then the growth rates of small and large firms are equally volatile, contrary to what is found in the data. If firm growth is the result of many independent shocks within a firm, it can take hundreds of years for a few large firms to emerge. This paper describes an economy with both types of shocks that can account for the thick-tailed firm size distribution, high entry and exit rates, and the relatively young age of large firms. The economy is one in which aggregate growth is driven by the creation of new products by both new and incumbent firms. Some new firms have better ideas than others and choose to implement those ideas at a more rapid pace. Eventually, such firms slow down when the quality of their ideas reverts to the mean. As in the data, average growth rates in a cross section of firms will appear to be independent of firm size, for all but the smallest firms.