Making use of restrictions imposed by equilibrium, theoretical progress has been made on the nonparametric and semiparametric estimation and identification of scalar additive hedonic models (Ekeland, Heckman, and Nesheim, 2002) and scalar nonadditive hedonic models (Heckman, Matzkin, and...

This paper presents a study of a coordinated production inventory-system. In the proposed model, any echelon considers its successors as part of its inventory system and generates the replenishment order on the basis of operational information of its partners. We show that the coordinated...

Textbooks on Design of Experiments invariably start by explaining why one-factor-at-a-time (OAT) is an inferior method. Here we will show that in a model with all interactions a variant of OAT is extremely efficient, provided that we only have non-negative parameters and that there are only a...

Monte Carlo methods are simulation algorithms to estimate a numerical quantity in a statistical model of a real system. These algorithms are executed by computer programs. Variance reduction techniques (VRT) are needed, even though computer speed has been increasing dramatically, ever since the...

This paper provides new evidence on the effects of banking sector recapitalization in Nigeria. It set up a simple model of the banking firm, to investigating the impact of capital regulation on banks behavior as well as having possible effects on the economy. Time series data covering the year...

This paper focuses on simulation-based inference for the time-deformation models directed by a duration process. In order to describe the heavy tail property of the time series of financial asset returns, the innovation of the observation equation is assumed to have a Student-t distribution....

The long-term development of the social security system is a crucial policy issue in terms of both financial sustainability and adequacy, which constitute a difficult trade-off facing the policy maker. The particular complexity of this issue, also in the light of demographic dynamics and the...

We present a simple method to generate scenarios from multivariate elliptical distributions where the sample mean and covariances match the respective population moments. This methodology easily applies to large numbers of scenarios and large-dimensional distributions. We show an application to...

Optimization of simulated systems is the goal of many methods, but most methods assume known environments. We, however, develop a `robust' methodology that accounts for uncertain environments. Our methodology uses Taguchi's view of the uncertain world, but replaces his statistical techniques by...

Design Of Experiments (DOE) is needed for experiments with real-life systems, and with either deterministic or random simulation models. This contribution discusses the different types of DOE for these three domains, but focusses on random simulation. DOE may have two goals: sensitivity analysis...