Volume 16, Issue 1

A theory of band-limited linear stochastic processes is described and it is related to the familiar theory of ARMA models in discrete time. By ignoring the limitation on the frequencies of the forcing function, in the process of fitting a conventional ARMA model, one is liable to derive estimates that are severely biased. If the maximum frequency in the sampled data is less than the Nyquist value, then the underlying continuous function can be reconstituted by sinc function or Fourier interpolation. The estimation biases can be avoided by re-sampling the continuous process at a rate corresponding to the maximum frequency of the forcing function. Then, there is a direct correspondence between the parameters of the band-limited ARMA model and those of an equivalent continuous-time process.

We consider the impact of data revisions on the forecast performance of a SETAR regime-switching model of U.S. output growth. The impact of data uncertainty in real-time forecasting will affect a model's forecast performance via the effect on the model parameter estimates as well as via the forecast being conditioned on data measured with error. We find that benchmark revisions do affect the performance of the non-linear model of the growth rate, and that the performance relative to a linear comparator deteriorates in real-time compared to a pseudo out-of-sample forecasting exercise.

The unemployment rate in Australia is modelled as an asymmetric and nonlinear function of aggregate demand, productivity, real interest rates, the replacement ratio and the real exchange rate. If changes in unemployment are big, the management of of demand, real interest rates and the replacement ratio will be good instruments to start bringing it down. The model is developed by exploiting recent developments in automated model-selection procedures.

The paper suggests a nonlinear and multivariate time series model framework that enables the study of simultaneity in returns and in volatilities, as well as asymmetric effects arising from shocks and exogenous variables. The model is employed to study the three closely related Baltic States’ stock exchanges and the influence exerted by the Russian stock exchange. Using daily data, we find recursive structures with returns in Riga directly depending on returns in Tallinn and Vilnius, and Tallinn on Vilnius. For volatilities, both Riga and Vilnius depend on Tallinn. In addition, we find evidence of asymmetric effects of shocks arising in Moscow and in Baltic States on both returns and volatilities.

The intention of this paper is to demonstrate the flexibility and capacity of penalized spline smoothing as estimation routine for modelling duration time data. We investigate the unemployment behaviour in Germany and the UK between 1995 and 2005 based on data from national panel studies. Functional duration time models are used to investigate the dynamics of covariate effects. The focus of our analysis is on contrasting the two economies. The statistical model being employed is built upon the hazard function, where we allow all covariate effects to vary smoothly with time. As result of the analyses, we demonstrate that the most striking difference between the countries is that elderly unemployed in Germany have decreasing chances for reemployment compared to the UK.

This paper reexamines the pricing of exchange rate risk in the U.S. stock market. We first construct stock portfolios based on the Foreign Exchange Income (FEI), a measure of currency exposure of firms, reported in their annual reports. We then develop two-factor and multi-factor nonparametric models that allow time variation in risk exposure and risk premium, and nonlinearity in the return generating process. When we assume that risk exposure can be time-varying but risk premium is constant, the estimated premium for exchange rate risk is significant only for the most positive FEI-ranked portfolio and marginally significant for the most negative FEI-ranked portfolio. When we further assume that both risk exposure and risk premium can be time-varying, results suggest that exchange rate risk is significantly priced for all the FEI-ranked portfolios except the one with little exposure.