Cultural diversity is a complex and multi-faceted concept. Commonly used quantitative measures of the spatial distribution of culturally-defined groups 'such as segregation, isolation or concentration indexes' are often only capable of identifying just one aspect of this distribution. The...

The empirical economic growth literature is criticized for its lack ofrobustness. For different definitions of robustness, conclusions vary from 'almost everycorrelation is fragile' to 'a substantial number of explanatory variables are robust.' Were-analyze the empirical results of the economic...

We present a multi-country theory of economic growth in which countries are connected by a network of mutual knowledge exchange. Growth is generated through human capital accumulation and knowledge externalities. The available knowledge in any country depends on its connections to the rest of...

Structural funds are the most intensively used policy instrument by the EuropeanUnion to promote economic growth in its member states and to speed up the process ofconvergence. This paper empirically explores the effectiveness of European Structural Fundsby means of a panel data analysis for 13...

This discussion paper resulted in a publication in <Stochastic Models</I> (2012). Volume 28(3), pages 478-502.<P> We apply the splitting method to three well-known counting problems, namely 3-SAT, random graphs with prescribed degrees, and binary contingency tables. We present an enhanced version of the splitting method...</p></stochastic>

We compare three stochastic user equilibrium traffic assignment models multinomial probit, nested logit, and generalized nested logit), using a congestible transport network. We test the models in two situations: one in which they have theoretically equivalent coefficients, and one in which they...

In this paper we study a challenging call center operation problem. The goal of our analysis is to identify an optimal policy for allocating tasks to agents. As a first step, we discuss promising randomized policies and use stochastic approximation for finding the optimal randomized policy when...

Kernel ridge regression is gaining popularity as a data-rich nonlinear forecasting tool, which is applicable in many different contexts. This paper investigates the influence of the choice of kernel and the setting of tuning parameters on forecast accuracy. We review several popular kernels,...