Recent advances in evolutionary theory have some important implications for environmental economics. A short overview is offered of evolutionary thinking in economics. Subsequently, major concepts and approaches in evolutionary biology and evolutionary economics are presented and compared. Attention is devoted, among others, to Darwinian selection, punctuated equilibrium, sorting mechanisms, Lamarckian evolution, coevolution and self-organization. Basic features of evolution, such as sustained change, irreversible change, unpredictability, qualitative change and disequilibrium are examined. It is argued that there are a number of fundamental differences as well as similarities between biological and economic evolution. Next, some general implications of evolutionary thinking for environmental economics are outlined. This is followed by a more detailed examination of potential uses of evolutionary theories in specific areas of environmental economics, including sustainability and long run development theories, technology and environment, ecosystem management and resilience, spatial evolution and environmental processes, and design of environmental policy.

Abstract This paper proposes a multiactivity generalisation of the Nelson–Winter model, or the NW model, in order to turn the attention of evolutionary minded economists toward specialisation and exchange, the emergence of markets for intermediate goods, the specialisation of R&D, and other issues of multisectoral growth and development. The argument and the solution is presented in four steps. First, there is a discussion of some practical difficulties and core theoretical problems in relation to the standard NW model of Schumpeterian competition. The conclusion is that this model gives an ad hoc solution to the tendency of evolutionary models to produce monopoly and that is has not really confronted the ‘knife-edge ’ problems of the underlying Leontief technology. Thus there is still a need to confront what may be called the diversity paradox and the Leontief technology paradox of evolutionary modelling. Second, the paper develops a condensed version of the NW model that serves to highlight the theoretical problems and as a platform for the proposed generalisation. This version of the NW model, the LNW model, includes only labour and knowledge. With given technologies the LNW model shows standard replicator dynamics while it can also be used as a testbed for exploring different R&D regimes. Third, the bare bones of the multiactivity generalisation of the NW model, the MNW model, is presented. This presentation starts from firms

Evolutionary and environmental economics have a potentially close relationship. This paper reviews past and identifies potential applications of evolutionary concepts and methods to environmental economics. This covers a number of themes: resource use and ecosystem management; growth and environmental resources; economic and evolutionary progress; and individual behavior and environmental policy. The treatment will cover both biological and economic – including institutional, organizational and technological – evolutionary phenomena. Attention will be drawn to the fact that evolutionary economics shows a surprising neglect of environmental and natural resource factors.

In this paper, we study whether the most robust stylized facts characterizing the coupled dynamics of output and investment can be explained in terms of bounded rationality (i.e. “animal spirits”) in firm investment behavior and the ensuing lumpiness in investment patterns. We present an evolutionary, agent-based, model of industry dynamics describing an economy composed of consumers and firms. Firms belong to two industries. Firms in the first industry perform R&D and produce heterogeneous machine tools. Firms in the second industry invest in new machines and produce a consumption good. Manufacturing firms invest only if they expect a large growth in the demand for their product. Preliminary simulation results show that the model is able to reproduce the most important empirically-observed statistical properties of investment-output dynamics. More specifically, we find that a necessary condition for the economy to exhibit self-sustaining patterns of growth is the presence of some additional (exogenous or endogenous) component to private consumption. We also show that, in these cases, the model is able to generate simulated output-investment dynamics characterized by volatility, auto- and cross-correlation patterns similar to thoseobservedinreality.

The paper investigates the impact the Internet may have in the evolution of telecommunications networks. First, we show why the Internet, emerging from a different cognitive perception of the data communication problem, has led to a new network architecture based on: (i) the distribution of the 'network intelligence ' to the user equipment; (ii) the very cost-effective 'statistical sharing ' of the network resources (i.e. getting the whole bandwidth of the network fbr short periods of time); (Hi) the establishment of an Internet Protocol (IP) 'gateway ' facilitating interoperability between heterogeneous infrastructure facilities—instead of the operator-controlled homogeneity of the telecom networks; and (iv) an 'adaptative ' way for open standards-setting. Second, we suggest that two technological trajectories (telecom— 'creative accumulation ' and Internet—'creative destruction') should dynamically co-exist henceforth and compete for market shares—possibly during later evolutionary stages generating relatively different national or even localized (e.g. local providers) trajectories of evolution (with differing interfaces and standards). Furthermore, we 2 explore the question of whether the Internet's interoperability model may be a useful • * policy paradigm for future information infrastructures, and we start to discuss the I implications of requisite interoperability on the communications industry's structure z itself. Overall, our preliminary observations raise questions about the possibilities of two "2 'technological trajectories ' co-existing, and the relationship between the interoperability J and learning conditions in the network industries.

This paper studies an agent-based model that bridges Keynesian theories of demandg-eneration and Schumpeterian theories of technology-fueled economic growth. We employ the model to investigate the properties of macroeconomic dynamics and the impact of public polices on supply, demand and the “fundamentals” of the economy. We find that the complementarities between factors influencing aggregate demand and drivers of technological change affect both “short-run” fluctuations and long-term growth patterns. From a normative point of view, simulations show a corresponding complementarity between Keynesian and Schumpeterian policies in sustaining long-run growth paths characterized by mild fluctuations and acceptable unemployment levels. The matching or mismatching between innovative exploration of new technologies and the conditions of demand generation appear to suggest the presence of two distinct “regimes” of growth (or absence thereof) characterized by

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This paper studies an agent-based model that bridges Keynesian theories of demandgeneration and Schumpeterian theories of technology-fueled economic growth. We employ the model to investigate the properties of macroeconomic dynamics and the impact of public polices on supply, demand and the “fundamentals ” of the economy. We find that the complementarities between factors influencing aggregate demand and drivers of technological change affect both “short-run ” fluctuations and long-term growth patterns. From a normative point of view, simulations show a corresponding complementarity between Keynesian and Schumpeterian policies in sustaining long-run growth paths characterized by mild fluctuations and acceptable unemployment levels. The matching or mismatching between innovative exploration of new technologies and the conditions of demand generation appear to suggest the presence of two distinct “regimes ” of growth (or absence thereof) characterized by

This article aims to test the relevance of learning through Genetic Algorithms (GA) and Learning Classifier Systems (LCS), in opposition with fixed R&D rules, in a simplified version of the evolutionary industry model of Nelson and Winter. These three R&D strategies are compared from the points of view of industry performance (welfare): the results of simulations clearly show that learning is a source of