Education systems can be viewed as complex systems, by considering that learning, teaching, cognition and education are phenomena resulting from interactions between the heterogeneous agents that compose such systems. Given the complex nature of education systems, new approaches seem relevant,...

In this paper we apply statistical inference techniques to build neural network models which are able to explain the prices of call options written on the German stock index DAX. By testing for the explanatory power of several input variables serving as network inputs, some insight into the...

Complex systems' approach and methodologies emphasize interactions, diversity and dynamics. Complex systems perspectives also enable public policies to be considered comprehensively and simulated in all their multiplicity of sectors and scales, of cause and effect. This paper attempts to...

When banks choose similar investment strategies, the financial system becomes vulnerable to common shocks. Banks decide about their investment strategy ex-ante based on a private belief about the state of the world and a social belief formed from observing the actions of peers. When the social...

We study the statistical properties of heterogeneous agent models. Using aBewley-Hugget-Aiyagari model we compute the density function of wealth and in-come and use it for likelihood inference. We study the finite sample properties of themaximum likelihood estimator (MLE) using Monte Carlo...