Suchergebnisse

Like many developing countries, Nigeria, is faced with a number of tradeoffs that pit rapid economic development against environmental preservation. Environmentally sustainable,"green" economic development is slower, more costly, and more difficult than unrestricted, unregulated economic growth. In this paper we develop an agent-based computational model of agents (who can be individuals or organizations) in a population who make successive choices that have economic and environmental impacts. Simulations based on the model suggest that widespread public awareness of environmental issues is insufficient to prevent the tendency towards sacrificing the environment for the sake of growth. Even if people have an understanding of negative impacts and always choose to act in their own self-interest, they may still act collectively in such a way as to bring down the quality of life for the entire society. We conclude that besides raising public awareness, economic intervention by the government (in the form of incentives or penalties) may be the only way to achieve an optimal balance between economic and environmental factors.

Many agent-based models (ABMs) try to explain large-scale phenomena by reducing them to behaviors at lower scales. At these scales in social systems are functional groups such as households, religious congregations, coops and local governments. The intra-group dynamics of functional groups often generate inefficient or unexpected behavior that cannot be predicted by modeling groups as basic units. We introduce a framework for modeling intra-group decision-making and its interaction with social norms, using the household as our focus. We select phenomena related to women's empowerment in agriculture as examples influenced by both intra-household dynamics and gender norms. Our framework proves more capable of replicating these phenomena than two common types of ABMs. We conclude that it is not enough to build multi-scale models; explaining social behaviors entails modeling intra-scale dynamics.

I develop an agent-based computational economics (ACE) model with which I evaluate the aggregate impact of labor market policies. The findings are that governmentfinanced training measures increase the outflow rate from unemployment to employment. Although the overall effect is positive this effect is achieved by reducing the outflow rate for those who do not receive subsidies. Furthermore, the outflow rate would have been downward-biased had one supposed a matching function that is exogenous to policies. ; Im Folgenden wird ein agenten-basiertes Modell entwickelt, mit dem die aggregierten Wirkungen von Arbeitsmarktpolitiken evaluiert werde können. Ein Resultat ist, dass die Subvention von Trainingsmaßnahmen die Übergangsrate von Arbeitslosigkeit in Beschäftigung erhöht. Obwohl der Gesamteffekt positiv ist, reduziert sich die Übergangsrate für all jene Arbeitslose, deren Ausgaben nicht subventioniert werden. Der Verdrängungseffekt ist bei einer plausiblen Parametrisierung des Modells in seiner Höhe ökonomisch relevant. Ferner wäre die Messung der Übergangsrate aus Arbeitslosigkeit in Beschäftigung nach unten verzerrt gewesen, hätte man in der Wirkungsanalyse angenommen, dass die Matching-Funktion exogen zu den Arbeitsmarktpolitiken ist.