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...

This paper studies an agent-based model that bridges Keynesian theories of demand generation 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...

The performances of alternative two-stage estimators for the endogenous switching regression model with discrete dependent variables are compared, with regard to their usefulness as starting values for maximum likelihood estimation. This is especially important in the presence of large...

We simulate the performances of a standard derivatives portfolio to evaluate the relevance of benchmarking in terms of downside risk reduction. The simulation shows that benchmarking always leads to significantly more severe losses in average than those generated by letting the portfolio reach...

This paper discusses some problems possibly arising when approximating via Monte-Carlo simulations the distributions of goodness-of-fit test statistics based on the empirical distribution function. We argue that failing to re-estimate unknown parameters on each simulated Monte-Carlo sample —...

This paper considers the use of simulated cash flows to value assets in real estate investment. We motivate the use of Monte Carlo simulation methods for the measurement of complex cash generating assets such as real estate assets return distribution. Important simulation inputs, such as the...

In this paper we discuss how a regression model, with a non-continuous response variable, that allows for dependency between observations should be estimated when observations are clustered and there are repeated measurements on the subjects. The cluster sizes are assumed to be large. We …nd...

This note discusses some problems possibly arising when approximating via Monte-Carlo simulations the distributions of goodness-of-fit test statistics based on the empirical distribution function. We argue that failing to re-estimate unknown parameters on each simulated Monte-Carlo sample -- and...

This contribution revises Monte-Carlo based simulation techniques as used in BusinessTaxation and Accounting literature, most prominently proposed by fellows ofTherefore, we focus on a methodically orientated discussion. Our results suggestthe standard approach leads to biased estimates of...

In NMR experiments, self-diffusion of water molecules leads to a random spin phase distribution which is Gaussian in linear magnetic fields. The rate of convergence of the random phase distribution to the Gaussian distribution is very slow. Moreover, a small departure from linear magnetic fields...