Publications

Summary

Financial constraints have an important impact on the development of eco-innovations but their effect varies according to the type of funding. This article studies the interaction between public funding on the one hand, and internal and external lack of funding on the other. The empirical analysis is based on a sample of European small- and medium-sized enterprises, and exploits information on firms’ involvement in eco-innovation activities, their drivers, and obstacles. Our results show that, even accounting for demand-pull effects and regulatory interventions, access to public funds and fiscal incentives is effective for improving the firm’s ability to introduce eco-innovations, particularly if the company has ample funds from either internal or external sources. Our findings suggest also that public funding is perceived by firms as complementary to other external finance.

Summary

We study a stochastic dynamic game of process innovation in which firms can initiate and terminate R&D efforts and production at different times. We discern the impact of knowledge spillovers on the investments in existing markets, as well as on the likely structure of newly forming markets, for all possible asymmetries in production costs between firms. While an increase in spillovers may improve the likelihood of a competitive market, it may at the same time reduce the level to which a technology is developed. We show that the effects of spillovers on investments and surpluses crucially depend on the stage of technology development considered. In particular, we show that high spillovers are not necessarily pro-competitive as they can make it harder for the laggard to catch up with the technology leader.

Summary

Using a dynamic heterogeneous agent industry model, we examine the impact of manager remuneration schemes on firms’ investment decisions and on the evolution of their competitiveness and share values. Whereas an increase in the share-based manager remuneration component is always beneficial to the manager, it is beneficial for shareholders only if such a change in the remuneration scheme is adopted by all firms in the industry. In that case, productivity growth is slowed down and workers’ real wages are reduced.

Summary

A very timely issue for economic agent-based models (ABMs) is their empirical estimation. This paper describes a line of research that could resolve the issue by using machine learning techniques, using multi-layer artificial neural networks (ANNs), or so called Deep Nets. The seminal contribution by Hinton et al. (Neural Comput 18(7):1527–1554, 2006) introduced a fast and efficient training algorithm called Deep Learning, and there have been major breakthroughs in machine learning ever since. Economics has not yet benefited from these developments, and therefore we believe that now is the right time to apply multi-layered ANNs and Deep Learning to ABMs in economics.

Summary

We investigate the interplay between technological change and macro- economic dynamics in an agent-based model of the formation of production networks. On the one hand, production networks form the structure that determines economic dynamics in the short run. On the other hand, their evolution reflects the long-term impacts of competition and innovation on the economy. We account for process innovation via increasing variety in the input mix and hence increasing connectivity in the network. In turn, product innovation induces a direct growth of the firm’s productivity and the potential destruction of links. The interplay between both processes generates complex technological dynamics in which phases of process and product innovation successively dominate. The model reproduces a wealth of stylized facts about industrial dynamics and technological progress, in particular the persistence of heterogeneity among firms and Wright’s law for the growth of productivity within a technological paradigm. We illustrate the potential of the model for the analysis of industrial policy via a preliminary set of policy experiments in which we investigate the impact on innovators’ success of feed-in tariffs and of priority market access.