It is common practice to identify the number and sources of shocks that move implied volatilities across space and time by applying Principal Components Analysis (PCA) to pooled covariance matrices of changes in implied volatilities. This approach, however, is likely to result in a loss of...

This paper improves previous sufficient conditions for stationarity obtained in the context of a general nonlinear vector autoregressive model with nonlinear autoregressive conditional heteroskedasticity. The results are proved by using the stability theory developed for Markov chains....

The paper proposes a technique for the estimation of possibly nonlinear panel data models in the presence of heterogeneous unit nonresponse. Attrition or unit nonresponse in panel data usually renders parameter estimators inconsistent unless the unavailable information is missing completely at...

We propose information theoretic tests for serial independence and linearity in time series. The test statisticsare based on the conditional mutual information, a general measure of dependence between lagged variables. In caseof rejecting the null hypothesis, this readily provides insights into...

Previous research has shown that economic growth should help to reduce the rate of poverty. However, a number of recent studies find that the economic expansion of the 1980's had no statistically significant effect on aggregate poverty. We show that a Fourier approximation provides a better...

The focus of this paper is on the neural network modeling approach that has gained increasing recognition in GIScience in recent years. The novelty about neural networks lies in their ability to model non-linear processes with few, if any, a priori assumptions about the nature of the...