In this article, we use cross-state panel and cross-U.S. commuting-zone data to look at the relationship between innovation, top income inequality and social mobility. We find positive correlations between measures of innovation and top income inequality. We also show that the correlations between innovation and broad measures of inequality are not significant. Next, using instrumental variable analysis, we argue that these correlations at least partly reflect a causality from innovation to top income shares. Finally, we show that innovation, particularly by new entrants, is positively associated with social mobility, but less so in local areas with more intense lobbying activities

Procuring an innovation involves motivating a research effort to generate a new idea and then implementing that idea efficiently. If research efforts are unverifiable and implementation costs are private information, a trade-off arises between the two objectives. The optimal mechanism resolves the trade-off via two instruments: a cash prize and a follow-on contract. It primarily uses the latter, by favouring the innovator at the implementation stage when the value of the innovation is above a certain threshold and handicapping the innovator when the value of the innovation is below that threshold. A cash prize is employed as a supplementary incentive only when the value of innovation is sufficiently high. These features are consistent with current practices in the procurement of innovation and the management of unsolicited proposals

We study a model of innovation with a large number of firms that create new technologies by combining several discrete ideas. These ideas are created via private investment and spread between firms. Firms face a choice between secrecy, which protects existing intellectual property, and openness, which facilitates learning from others. Their decisions determine interaction rates between firms, and these interaction rates enter our model as link probabilities in a learning network. Higher interaction rates impose both positive and negative externalities, as there is more learning but also more competition. We show that the equilibrium learning network is at a critical threshold between sparse and dense networks. At equilibrium, the positive externality from interaction dominates: the innovation rate and welfare would be dramatically higher if the network were denser. So there are large returns to increasing interaction rates above the critical threshold. Nevertheless, several natural types of interventions fail to move the equilibrium away from criticality. One effective policy solution is to introduce informational intermediaries, such as public innovators who do not have incentives to be secretive. These intermediaries can facilitate a high-innovation equilibrium by transmitting ideas from one private firm to another

We introduce non-homothetic preferences into an innovation-based growth model and study how income and wealth inequality affect economic growth. We identify a (positive) price effect—where increasing inequality allows innovators to charge higher prices and (negative) market-size effects—with higher inequality implying smaller markets for new goods and/or a slower transition of new goods into mass markets. It turns out that price effects dominate market-size effects. We also show that a redistribution from the poor to the rich may be Pareto improving for low levels of inequality

This paper shows that in a frictional labour market part of the productivity gains from general training will be captured by future employers. As a result, investments in general skills will be suboptimally low, and contrary to the standard theory, part of the costs may be borne by the employers. The paper also demonstrates that the interaction between innovation and training leads to an amplification of this inefficiency and to a multiplicity of equilibria. Workers are more willing to invest in their skills by accepting lower wages today if they expect more firms to innovate and pay them higher wages in the future. Similarly, firms are more willing to innovate when they expect the quality of the future workforce to be higher, thus when workers invest more in their skills

The purpose of this paper is to explain why some markets for financial products take off while others vanish as soon as they have emerged. To this end, we model an infinite sequence of CAPM-economies in which financial products can be used for insurance purposes. Agents' participation in these financial products, however, is restricted. Consecutive stage economies are linked by a mapping (“transition function”) which determines the next period's participation structure from the preceding period's participation. The transition function generates a dynamic process of market participation which is driven by the percentage of informed traders and the rate at which a new asset is adopted. We then analyse the evolutionary stability of stationary equilibria. In accordance with the empirical literature on financial innovation, it is obtained that the success of a financial innovation, a mutation, depends on a sufficiently high trading volume, marketing, and new and differentiated hedging opportunities. In particular, a set of complete markets forming a stationary equilibrium is robust with respect to any further financial innovation while this is not necessarily true for a set of incomplete markets

This paper develops a model of repeated innovation with knowledge spillovers. The model's novel feature is that firms compete on two dimensions: (1) product quality, where one firm's innovation ultimately spills over to other firms; and (2) distribution costs, where there are no spillovers across firms and where learning-by-doing on the part of incumbent firms gives them a competitive advantage over would-be entrants. Such firm-specific learning-by-doing has two important consequences: (1) it can in some circumstances dramatically reduce the long-run average level of innovation; (2) it leads to endogeneous bunching, or waves, in innovative activity

How do innovation and education policy affect individual career choices and aggregate productivity? This paper analyses the effect of R&D subsidies and higher education policy on productivity growth through the supply of innovative talent. We put scarce talent, higher education attainment, and career choice at the centre of a new endogenous growth framework with individual-level heterogeneity in talent, financial resources, and preferences. We link the model to micro-level data from Denmark on the backgrounds of who obtains a PhD and becomes an inventor and the outcomes of a set of policy interventions. We find that R&D subsidies can be strengthened when combined with higher education subsidies, which enable talented but poor youth to pursue a career in research. Education and innovation policies not only alleviate different frictions, but also impact innovation at different time horizons. Education policy is more effective in societies with higher income inequality

This paper investigates a possibly fundamental aspect of technological progress. If knowledge accumulates as technology advances, then successive generations of innovators may face an increasing educational burden. Innovators can compensate through lengthening educational phases and narrowing expertise, but these responses come at the cost of reducing individual innovative capacities, with implications for the organization of innovative activity—a greater reliance on teamwork—and negative implications for growth. Building on this “burden of knowledge” mechanism, this paper first presents six facts about innovator behaviour. I show that age at first invention, specialization, and teamwork increase over time in a large micro-data set of inventors. Furthermore, in cross-section, specialization and teamwork appear greater in deeper areas of knowledge, while, surprisingly, age at first invention shows little variation across fields. A model then demonstrates how these facts can emerge in tandem. The theory further develops explicit implications for economic growth, providing an explanation for why productivity growth rates did not accelerate through the 20th century despite an enormous expansion in collective research effort. Upward trends in academic collaboration and lengthening doctorates, which have been noted in other research, can also be explained in this framework. The knowledge burden mechanism suggests that the nature of innovation is changing, with negative implications for long-run economic growth

The authors analyze a dynamic North-South model of innovation, technology transfer, and trade. Northern firms conduct R&D using labor, which has alternative uses producing in the R&D sector or a nontraded good sector. Since technology trans fer prevents the North from fully appropriating benefits of R&D, the optimal rate of innovation for either profit-maximizing firms or a ut ility-maximizing northern planner is less than globally optimal. An i nceased transfer rate intensifies competition of lower wage southern workers with northern workers in production, so profit-maximizing Nor thern firms reallocate labor toward R&D