A auto-organização do progresso técnico e das mudanças climáticas num modelo simples de evolução

Abstract

This study examines the relationship between technical change and climate change in the micro level that has global consequences. For this purpose, we use the Bak-Sneppen model of Evolution, a model developed by Bak and Sneppen (1993) and used in biological systems. The model specifies a number N of agents on an ecosystem, each with a variable that determines the fitness adaptability on this environment. Furthermore, there behavioral rules that are repeated t times in time: 1) the agent with the lowest fitness is selected for mutation, and 2) mutations also occur in the neighboring agents with lower fitness. In this investigation has adapted to the Bak-Sneppen model for the economy, assuminga number N of firms that have two fitness variables, one that represents the technical change and another his care for the environment. To support technical change appealed to the Theory of Induced Technical Change, and climate change to the Theory of Sustainable Development in its complex aspect. From computer simulations of the highlights are three scenarios that describe the complex relationships between technical progress and climate change: the scenario has been called the most probable, and to incorporate the debate is one in which firms aim to maximize their technical and some of them can adopt clean technologies and not others, which makes both systems self-organize at a critical level approximately equal to 0.4 fitness. The adverse scenario is one in which the correlation between technical change and the environment is negative, and technical improvements are polluting and every company that wants to decrease their environmental externalities have to reduce technology. In this scenario, both systems and no changes its threshold is close to 0. Finally, the stage was called the ideal one in which the relationship between technical change and climate change is positive, it is assumed only firms adopt clean technologies. In this, both systems are evolving rapidly, reaching steady state at the threshold of 0.6.