The attractiveness of spatial autoregressive models has increased significantly. The awareness of important spatial interactions arose in various fields. In economics, interactions can be due to interdependencies between entities such as states, firms, or consumers. Examples are spatial...

Time series with long-memory behavior have recently received much attention. Much interest attaches to parameter estimation in the ARFIMA model by considering different situations of this process, and specifically when there are missing observations. This is the focus of this paper. To estimate...

This paper considers the use of the long-memory, semi-parametric estimators to test unit-root and non-cointegrated processes under fractional alternatives. Critical-point values of the proposed tests are given for different sample sizes. The ADF test is used for comparison purposes. The...

This paper utilizes two different classification techniques to explore issues in the development of an early warning system for sovereign default. Specifically, the paper develops K-means clustering and logit models to illustrate how the optimal choice of parameters, such as assignment rule of...

We develop a new approach to valuing and hedging basket options. We consider baskets of assets with potentially negative portfolio weights (spread options are a subclass of such basket options). The basket distribution is approximated using a generalized family of log-normal distributions. This...

One of the most critical issues when using neural networks is how to select appropriate network architectures for the problem at hand. Practitioners usually refer to information criteria which might lead to over-parameterized models with heavy consequence on overfitting and poor ex-post forecast...

This paper deals with the analysis of a nonlinear time series model of the effects of advertising. Given the nonlinear nature of the process it is not possible to rely on the asymptotic inference. Furthermore, we can not provide an (asymptotic) pivotal statistic. Our solution is the application...

Using threshold autoregressive specifications, this paper develops new parametric tests for level asymmetries. It proposes bootstrap likelihood ratio statistics to test the symmetric adjustment null against sign and amplitude asymmetries or a combination of both. Monte Carlo simulations show...

In applied microeconometric panel data analyses, time-constant random effects and first-order Markov chains are the most prevalent structures to account for intertemporal correlations in limited dependent variable models. An example from health economics shows that the addition of a simple...