Estimation and modelling problems as they arise in many fields often turn out to be intractable by standard numerical methods. One way to deal with such a situation consists in simplifying models and procedures. However, the solutions to these simplified problems might not be satisfying. A...

This paper focuses on finding starting-values for the estimation of Vector STAR models. Based on a Monte Carlo study, different procedures are evaluated. Their performance is assessed with respect to model fit and computational effort. I employ (i) grid search algorithms and (ii) heuristic...

This paper considers an alternative way of structuring stochastic variables in a dynamic programming framework where the model structure dictates that numerical methods of solution are necessary. Rather than estimating integrals within a Bellman equation using quadrature nodes, we use nodes...

In the economics of joint production one often distinguishes between the two cases: the one in which a firm produces multiple products each produced under separate production process, and the other "true joint production" where a number of outputs are produced from a single production process,...

The optimized portfolio that is calculated by a covariance matrix has large sensitivities to small eigen values of the covariance matrix. Estimation of sampling errors for small eigen values is quite important for fund managers who construct their portfolios from estimated covariance matrixes....

A new tabu search algorithm is proposed for the maximum score estimator computation, where the focus is on large sample size and/or large number of parameters. The proposed algorithm shares the same solution representation with the Hyperplanes Intersection Simulated Annealing (HISA) previously...

We derive in a straightforward manner and through a unified framework the main known results related to the estimation of the ultimate prediction uncertainty within the famous Mack's distribution-free chain-ladder model, specifically, the Mack and BBMW formulas, and explain the deviation between...