Support in R for state space estimation via Kalman filtering was limited to one package, until fairly recently. In the last five years, the situation has changed with no less than four additional packages offering general ...

This paper compares the performance of three different time-varying betas that have never previously been compared: the rolling OLS estimator, a nonparametric estimator and an estimator based on GARCH models. The study ...

In this paper we analyse the endogenous order of moves in a mixed duopoly for differentiated goods. Firms choose whether to set prices sequentially or simultaneously. The private firm maximises profits while the public ...

A spatio-temporal model is proposed aimed at producing an index of housing prices. A hedonic model with geographically varying coefficients is coupled with a non parametric estimation of the trend, whence a price index is derived.

We propose a two-dimensional Kalman filter approach that, additional to the information contained in futures prices evolution over time, makes use of information contained in the term structure of commodity futures along ...

When working with time series data observed at intervals smaller than a year, it is often necessary to test for the presence of seasonal unit roots. One of the most widely used methods for testing seasonal unit roots is ...

One of the main problems that public institutions face in the management of protected areas, such as the European Natura 2000 network, is how to design and implement sustainable management plans accounting both for the ...

In this paper we present a parallelizable scheme of the Branch-and-Fix Coordination algorithm for solving medium and large scale multi-stage mixed 0-1 optimization problems under uncertainty. The uncertainty is represented ...

Strong persistence is a common phenomenon that has been documented not only in the levels but also in the volatility of many time series. The class of doubly fractional models is extended to include the possibility of long ...

Statistical studies that consider multiscale relationships among several variables use wavelet correlations and cross-correlations between pairs of variables. This procedure needs to calculate and compare a large number ...