Using a panel of 439 German regions we evaluate and compare the performance of various Neural Network (NN) models as forecasting tools for regional employment growth. Because of relevant differences in data availability between the former East and West Germany, NN models are computed separately...

This paper proposes an adaptive version for the Metropolis adjusted Langevin algorithm with a truncated drift (T-MALA). The scale parameter and the covariance matrix of the proposal kernel of the algorithm are simultaneously and recursively updated in order to reach the optimal acceptance rate...

In this paper, an agent-based computational capital asset pricing model is applied to address an issue, known as the elasticity puzzle, originating from a famous reciprocal relation between the elasticity of intertemporal substitution (EIS) and the relative risk aversion (RRA) coefficient. By...

We analyse the evolution of the business cycle in the new EU member countries, after a careful examination of the seasonal properties of the available series and the required modification of the cycle dating procedures. We then focus on the degree of cyclical concordance within the group of new...

The conditioning of strategies by market environment and the simultaneous emergence of market structure in the presence of evolving trading strategies are investigated with major international stock indexes. Models for price forecasting and trading strategies evolution are examined under...

This paper proposes an algorithm to obtain maximum likelihood estimates of structural parameters in discrete games with multiple equilibria. The method combines a genetic algorithm (GA) with a pseudo maximum likelihood (PML) procedure. The GA searches efficiently over the huge space of possible...

This work illustrates an approach to the study of labeling, aka 'object classification'. This kind of parallel computing problem well suites to AI applications (pattern recognition, edge detection, etc.) Our target consists in simplifying an overly computationally costly algorithm proposed by...

This paper proposes an algorithm to obtain maximum likelihood estimates of structural parameters in discrete games with multiple equilibria. The method combines a genetic algorithm (GA) with a pseudo maximum likelihood (PML) procedure. The GA searches efficiently over the huge space of possible...