This paper is related to the choice of alternative types of public transport modes and its incidence in the Madrid Metropolitan Area. When planning transport facilities, two conditions are needed: efficient estimation of the users' response to changes in prices and in the characteristics of the...

In this paper we present an extensive study of annual GNP data for five European countries. We look for intercountry dependence and analyse how the different economies interact, using several univariate ARIMA and unobserved components models and a multivariate model for the GNP incorporating all...

This paper analyses the aggregate relationships between traffic accidents and real economic activity in Spain during the last 30 years. Our general approach is based on two basic assumptions: (1) the number of accidents depends on the use of cars and other exogenous variables, and (2) the level...

Espasa and Mayo-Burgos (2013) provide consistent forecasts for an aggregate economic indicator and its basic components as well as for useful sub-aggregates. To do this, they develop a procedure based on single-equation models that includes the restrictions arisen from the fact that some...

Although spectral analysis of stationary stochastic processes has solid mathematical foundations, this is not always so for some non-stationary cases. Here, we establish a rigorous mathematical extension of the classic Fourier spectrum to the case in which there are AR roots in the unit circle,...

Espasa and Mayo provide consistent forecasts for an aggregate economic indicator and its basic components as well as for useful sub-aggregates. To do so, they develop a procedure based on single-equation models that includes the restrictions arisen from the fact that some components share common...

Among the alternative Unobserved Components formulations within the stochastic state space setting, the Dynamic Harmonic Regression (DHR) has proved particularly useful for adaptive seasonal adjustment signal extraction, forecasting and back-casting of time series. Here, we show first how to...